pax_global_header00006660000000000000000000000064136113122210014502gustar00rootroot0000000000000052 comment=28674b1605d2cc0bd66e5e608bf15c7b407b2b95 snakemake-5.10.0/000077500000000000000000000000001361131222100135245ustar00rootroot00000000000000snakemake-5.10.0/.dockerignore000066400000000000000000000000571361131222100162020ustar00rootroot00000000000000.eggs images misc docs tutorial tests examples snakemake-5.10.0/.gitattributes000066400000000000000000000004021361131222100164130ustar00rootroot00000000000000snakemake/_version.py export-subst snakemake/report/report.html linguist-vendored=true snakemake/gui.html linguist-vendored=true snakemake/report/table.html linguist-vendored=true tests/test_issue1046/expected-results/test_report.html linguist-vendored=true snakemake-5.10.0/.github/000077500000000000000000000000001361131222100150645ustar00rootroot00000000000000snakemake-5.10.0/.github/CODEOWNERS000066400000000000000000000000231361131222100164520ustar00rootroot00000000000000* @johanneskoester snakemake-5.10.0/.github/ISSUE_TEMPLATE/000077500000000000000000000000001361131222100172475ustar00rootroot00000000000000snakemake-5.10.0/.github/ISSUE_TEMPLATE/bug_report.md000066400000000000000000000012601361131222100217400ustar00rootroot00000000000000--- name: Bug report about: Create a report to help us improve title: '' labels: bug assignees: '' --- **Snakemake version** Note the Snakemake version for which you experience the bug. Always make sure to try out the latest version before creating a new bug report. **Describe the bug** A clear and concise description of what the bug is. **Logs** If applicable, any terminal output to help explain your problem. **Minimal example** Add a minimal example for reproducing the bug. **Additional context** Add any other context about the problem here. snakemake-5.10.0/.github/ISSUE_TEMPLATE/feature_request.md000066400000000000000000000011341361131222100227730ustar00rootroot00000000000000--- name: Feature request about: Suggest an idea for this project title: '' labels: enhancement assignees: '' --- **Is your feature request related to a problem? Please describe.** A clear and concise description of what the problem is. Ex. I'm always frustrated when [...] **Describe the solution you'd like** A clear and concise description of what you want to happen. **Describe alternatives you've considered** A clear and concise description of any alternative solutions or features you've considered. **Additional context** Add any other context or screenshots about the feature request here. snakemake-5.10.0/.github/workflows/000077500000000000000000000000001361131222100171215ustar00rootroot00000000000000snakemake-5.10.0/.github/workflows/main.yml000066400000000000000000000046331361131222100205760ustar00rootroot00000000000000name: CI on: push: branches: - master pull_request: branches_ignore: [] jobs: formatting: runs-on: ubuntu-latest steps: - uses: actions/checkout@v1 - name: Setup black environment run: conda create --quiet --name black black - name: Check formatting run: | export PATH="/usr/share/miniconda/bin:$PATH" source activate black black --check snakemake tests/*.py - name: Comment PR if: github.event_name == 'pull_request' && failure() uses: marocchino/sticky-pull-request-comment@v1.1.0 with: message: 'Please format your code with [black](https://black.readthedocs.io): `black snakemake tests/*.py`.' GITHUB_TOKEN: ${{ secrets.GITHUB_TOKEN }} testing: runs-on: ubuntu-latest needs: formatting steps: - uses: actions/checkout@v1 - name: Setup Snakemake environment run: conda env create --quiet --name snakemake --file test-environment.yml - name: Setup apt dependencies run: sudo apt install -y singularity-container stress - name: Setup iRODS run: | docker build -t irods-server tests/test_remote_irods docker run -d -p 1247:1247 --name provider irods-server -i run_irods sleep 10 docker exec -u irods provider iput /incoming/infile cp -r tests/test_remote_irods/setup-data ~/.irods - name: Run tests env: CI: true run: | # enable coverage recording for subprocesses echo -e "try:\n import coverage\n coverage.process_startup()\nexcept:\n pass" > sitecustomize.py export COVERAGE_PROCESS_START=.coveragerc # activate conda env export PATH="/usr/share/miniconda/bin:$PATH" source activate snakemake # run tests export AWS_DEFAULT_REGION=us-east-1 export AWS_ACCESS_KEY_ID=${{ secrets.AWS_ACCESS_KEY_ID }} export AWS_SECRET_ACCESS_KEY=${{ secrets.AWS_SECRET_ACCESS_KEY }} coverage run -m pytest tests/test*.py -v -x # collect coverage report #coverage combine #coverage xml #- name: Upload coverage report #uses: codecov/codecov-action@v1.0.3 #with: #token: ${{secrets.CODECOV_TOKEN}} - name: Build container image run: docker build . snakemake-5.10.0/.gitignore000066400000000000000000000002661361131222100155200ustar00rootroot00000000000000*~ *.pyc *.swp docs/_build build/ dist/ *.egg-info/ *.egg .eggs/ .snakemake* .venv .venv/* .idea .pytest* .cache .ipynb* .ropeproject .test* tests/test*/* playground/* tutorial/*snakemake-5.10.0/.readthedocs.yml000066400000000000000000000001771361131222100166170ustar00rootroot00000000000000version: 2 sphinx: configuration: docs/conf.py python: version: 3.6 install: - requirements: docs/requirements.txt snakemake-5.10.0/.sonarcloud.properties000066400000000000000000000000301361131222100200620ustar00rootroot00000000000000sonar.sources=snakemake snakemake-5.10.0/AUTHORS.rst000066400000000000000000000000001361131222100153710ustar00rootroot00000000000000snakemake-5.10.0/CHANGELOG.rst000066400000000000000000000712211361131222100155500ustar00rootroot00000000000000[5.10.0] - 2019-01-20 ===================== Added ----- - Jupyter notebook integration, see docs. This enables interactive development of certain data analysis parts (e.g. for plotting). - Ability to overwrite thread definitions at the command line (``--threads rulename=3``), thereby improving scalability. - Requester pays configuration for google storage remote files. - Add keyword ``allow_missing`` to expand function, thereby allowing partical expansion by skipping wildcards for which no keywords are defined. Changed ------- - Various bug fixes, e.g. for between workflow caching and script execution. [5.9.1] - 2019-12-20 ==================== Changed ------- - Added a missing module. [5.9.0] - 2019-12-20 ==================== Added ----- - Support for per-rule environment module definitions to enable HPC specific software deployment (see docs). - Allow custom log handler defitions via --log-handler-script (e.g. post errors and progress to a slack channel or send emails). - Allow setting threads as a function of the given cores (see docs). Changed ------- - Various minor fixes. [5.8.2] - 2019-12-16 ==================== Added ----- - Implemented a ``multiext`` helper, allowing to define a set of output files that just differ by extension. Changed ------- - Fixed a failure when caching jobs with conda environments. - Fixed various minor bugs. - Caching now allows to cache the output of rules using ``multiext``. [5.8.1] - 2019-11-15 ==================== Changed ------- - Fixed a bug by adding a missing module. [5.8.0] - 2019-11-15 ==================== Added ----- - Blockchain based caching between workflows (in collaboration with Sven Nahnsen from QBiC), see `the docs `_. - New flag --skip-cleanup-scripts, that leads to temporary scripts (coming from script or wrapper directive) are not deleted (by Vanessa Sochat). Changed ------- - Various bug fixes. [5.7.4] - 2019-10-23 ==================== Changed ------- - Various fixes and adaptations in the docker container image and the test suite. [5.7.1] - 2019-10-16 ==================== Added ----- - Ability to print log files of failed jobs with --show-failed-logs. Changed ------- - Fixed bugs in tibanna executor. - Fixed handling of symbolic links. - Fixed typos in help texts. - Fixed handling of default resources. - Fixed bugs in azure storage backend. [5.7.0] - 2019-10-07 ==================== Changed ------- - Fixed various corner case bugs. Many thanks to the community for pull requests and reporting! - Container execution adapted to latest singularity. Added ----- - First class support for Amazon cloud execution via a new `Tibanna backend `. Thanks to Soo Lee from Harvard Biomedical Informatics! - Allow multiple config files to be passed via the command line. - A new, more detailed way to visualize the DAG (--filegraph). Thanks to Henning Timm! - Pathlib compatibility added. Input and output files can now also be Path objects. Thanks to Frederik Boulund! - New azure storage remote provider. Transparently access input and output files on Microsoft Azure. Thanks to Sebastian Kurscheid! [5.6.0] - 2019-09-06 ==================== Changed ------- - Fix compatibility with latest singularity versions. - Various bug fixes (e.g. in cluster error handling, remote providers, kubernetes backend). Added ----- - Add --default-resources flag, that allows to define default resources for jobs (e.g. mem_mb, disk_mb), see `docs `_. - Accept ``--dry-run`` as a synonym of ``--dryrun``. Other Snakemake options are similarly hyphenated, so other documentation now refers to ``--dry-run`` but both (and also ``-n``) will always be accepted equivalently. [5.5.4] - 2019-07-21 ==================== Changed ------- - Reports now automatically include workflow code and configuration for improved transparency. [5.5.3] - 2019-07-11 ==================== Changed ------- - Various bug fixes. - Polished reports. [5.5.2] - 2019-06-25 ==================== Changed ------- - Various minor bug fixes in reports. - Speed improvements when using checkpoints. [5.5.1] - 2019-06-18 ==================== Changed ------- - Improved report interface. In particular for large files. - Small TSV tables are automatically rendered as HTML with datatables. - Be more permissive with Snakefile choices: allow "Snakefile", "snakefile", "workflow/Snakefile", "workflow/snakefile". [5.5.0] - 2019-05-31 ==================== Added ----- - Script directives now also support Julia. Changed ------- - Various small bug fixes. [5.4.5] - 2019-04-12 ==================== Changed ------- - Fixed a bug with pipe output. - Cleaned up error output. [5.4.4] - 2019-03-22 ==================== Changed ------- - Vastly improved performance of HTML reports generated with --report, via a more efficient encoding of dara-uri based download links. - Tighter layout, plus thumbnails and a lightbox for graphical results in HTML reports. - Bug fix for pipe groups. - Updated docs. - Better error handling in DRMAA executor. [5.4.3] - 2019-03-11 ==================== Changed ------- - More robust handling of conda environment activation that should work with all setups where the conda is available when starting snakemake. - Fixed bugs on windows. [5.4.2] - 2019-02-15 ==================== Changed ------- - Fixed a bug where git module cannot be imported from wrapper. [5.4.1] - 2019-02-14 ==================== Added ----- - Warning when R script is used in combination with conda and R_LIBS environment variable is set. This can cause unexpected results and should be avoided. Changed ------- - Improved quoting of paths in conda commands. - Fixed various issues with checkpoints. - Improved error messages when combining groups with cluster config. - Fixed bugs in group implementation. - Fixed singularity in combination with shadow. [5.4.0] - 2018-12-18 ==================== Added ----- - Snakemake now allows for data-dependent conditional re-evaluation of the job DAG via checkpoints. This feature also deprecates the ``dynamic`` flag. See `the docs `_. [5.3.1] - 2018-12-06 ==================== Changed ------- - Various fixed bugs and papercuts, e.g., in group handling, kubernetes execution, singularity support, wrapper and script usage, benchmarking, schema validation. [5.3.0] - 2018-09-18 ==================== Added ----- - Snakemake workflows can now be exported to CWL via the flag --export-cwl, see `the docs `_. Changed ------- - Fixed bug in script and wrapper execution when using ``--use-singularity --use-conda``. - Add host argument to S3RemoteProvider. - Various minor bug fixes. [5.2.4] - 2018-09-10 ==================== Added ----- - New command line flag --shadow-prefix Changed ------- - Fixed permission issue when using the script directive. This is a breaking change for scripts referring to files relative to the script directory (see the `docs `__). - Fixed various minor bugs and papercuts. - Allow URL to local git repo with wrapper directive (``git+file:///path/to/your/repo/path_to_file@@version``) [5.2.2] - 2018-08-01 ==================== Changed ------- - Always print timestamps, removed the --timestamps CLI option. - more robust detection of conda command - Fixed bug in RMarkdown script execution. - Fixed a bug in detection of group jobs. [5.2.0] - 2018-06-28 ==================== Changed ------- - Directory outputs have to marked with ``directory``. This ensures proper handling of timestamps and cleanup. This is a breaking change. Implemented by Rasmus Ågren. - Fixed kubernetes tests, fixed kubernetes volume handling. Implemented by Andrew Schriefer. - jinja2 and networkx are not optional dependencies when installing via pip. - When conda or singularity directives are used and the corresponding CLI flags are not specified, the user is notified at the beginning of the log output. - Fixed numerous small bugs and papercuts and extended documentation. [5.1.5] - 2018-06-24 ==================== Changed ------- - fixed missing version info in docker image. - several minor fixes to EGA support. [5.1.4] - 2018-05-28 ==================== Added ----- - Allow ``category`` to be set. Changed ------- - Various cosmetic changes to reports. - Fixed encoding issues in reports. [5.1.3] - 2018-05-22 ==================== Changed ------- - Fixed various bugs in job groups, shadow directive, singularity directive, and more. [5.1.2] - 2018-05-18 ==================== Changed ------- - Fixed a bug in the report stylesheet. [5.1.0] - 2018-05-17 ==================== Added ----- - A new framework for self-contained HTML reports, including results, statistics and topology information. In future releases this will be further extended. - A new utility snakemake.utils.validate() which allows to validate config and pandas data frames using JSON schemas. - Two new flags --cleanup-shadow and --cleanup-conda to clean up old unused conda and shadow data. Changed ------- - Benchmark repeats are now specified inside the workflow via a new flag repeat(). - Command line interface help has been refactored into groups for better readability. [5.0.0] - 2018-05-11 ==================== Added ----- - Group jobs for reduced queuing and network overhead, in particular with short running jobs. - Output files can be marked as pipes, such that producing and consuming job are executed simultaneously and interfomation is transferred directly without using disk. - Command line flags to clean output files. - Command line flag to list files in working directory that are not tracked by Snakemake. Changed ------- - Fix of --default-remote-prefix in case of input functions returning lists or dicts. - Scheduler no longer prefers jobs with many downstream jobs. [4.8.1] - 2018-04-25 ==================== Added ----- - Allow URLs for the conda directive. # Changed - Various minor updates in the docs. - Several bug fixes with remote file handling. - Fix ImportError occuring with script directive. - Use latest singularity. - Improved caching for file existence checks. We first check existence of parent directories and cache these results. By this, large parts of the generated FS tree can be pruned if files are not yet present. If files are present, the overhead is minimal, since the checks for the parents are cached. - Various minor bug fixes. [4.8.0] - 2018-03-13 ==================== Added ----- - Integration with CWL: the ``cwl`` directive allows to use CWL tool definitions in addition to shell commands or Snakemake wrappers. - A global ``singularity`` directive allows to define a global singularity container to be used for all rules that don't specify their own. - Singularity and Conda can now be combined. This can be used to specify the operating system (via singularity), and the software stack (via conda), without the overhead of creating specialized container images for workflows or tasks. [4.7.0] - 2018-02-19 ==================== Changed ------- - Speedups when calculating dry-runs. - Speedups for workflows with many rules when calculating the DAG. - Accept SIGTERM to gracefully finish all running jobs and exit. - Various minor bug fixes. [4.6.0] - 2018-02-06 ==================== Changed ------- - Log files can now be used as input files for other rules. - Adapted to changes in Kubernetes client API. - Fixed minor issues in --archive option. - Search path order in scripts was changed to fix a bug with leaked packages from root env when using script directive together with conda. [4.5.1] - 2018-02-01 ==================== Added ----- - Input and output files can now tag pathlib objects. # ## Changed - Various minor bug fixes. [4.5.0] - 2018-01-18 ==================== Added ----- - iRODS remote provider # ## Changed - Bug fix in shell usage of scripts and wrappers. - Bug fixes for cluster execution, --immediate-submit and subworkflows. [4.4.0] - 2017-12-21 -------------------- Added ----- - A new shadow mode (minimal) that only symlinks input files has been added. Changed ------- - The default shell is now bash on linux and macOS. If bash is not installed, we fall back to sh. Previously, Snakemake used the default shell of the user, which defeats the purpose of portability. If the developer decides so, the shell can be always overwritten using shell.executable(). - Snakemake now requires Singularity 2.4.1 at least (only when running with --use-singularity). - HTTP remote provider no longer automatically unpacks gzipped files. - Fixed various smaller bugs. [4.3.1] - 2017-11-16 -------------------- Added ----- - List all conda environments with their location on disk via --list-conda-envs. Changed ------- - Do not clean up shadow on dry-run. - Allow R wrappers. [4.3.0] - 2017-10-27 -------------------- Added ----- - GridFTP remote provider. This is a specialization of the GFAL remote provider that uses globus-url-copy to download or upload files. # ## Changed - Scheduling and execution mechanisms have undergone a major revision that removes several potential (but rare) deadlocks. - Several bugs and corner cases of the singularity support have been fixed. - Snakemake now requires singularity 2.4 at least. [4.2.0] - 2017-10-10 -------------------- Added ----- - Support for executing jobs in per-rule singularity images. This is meant as an alternative to the conda directive (see docs), providing even more guarantees for reproducibility. Changed ------- - In cluster mode, jobs that are still running after Snakemake has been killed are automatically resumed. - Various fixes to GFAL remote provider. - Fixed --summary and --list-code-changes. - Many other small bug fixes. [4.1.0] - 2017-09-26 -------------------- Added ----- - Support for configuration profiles. Profiles allow to specify default options, e.g., a cluster submission command. They can be used via 'snakemake --profile myprofile'. See the docs for details. - GFAL remote provider. This allows to use GridFTP, SRM and any other protocol supported by GFAL for remote input and output files. - Added --cluster-status flag that allows to specify a command that returns jobs status. # ## Changed - The scheduler now tries to get rid of the largest temp files first. - The Docker image used for kubernetes support can now be configured at the command line. - Rate-limiting for cluster interaction has been unified. - S3 remote provider uses boto3. - Resource functions can now use an additional ``attempt`` parameter, that contains the number of times this job has already been tried. - Various minor fixes. [4.0.0] - 2017-07-24 -------------------- Added ----- - Cloud computing support via Kubernetes. Snakemake workflows can be executed transparently in the cloud, while storing input and output files within the cloud storage (e.g. S3 or Google Storage). I.e., this feature does not need a shared filesystem between the cloud notes, and thereby makes the setup really simple. - WebDAV remote file support: Snakemake can now read and write from WebDAV. Hence, it can now, e.g., interact with Nextcloud or Owncloud. - Support for default remote providers: define a remote provider to implicitly use for all input and output files. - Added an option to only create conda environments instead of executing the workflow. # ## Changed - The number of files used for the metadata tracking of Snakemake (e.g., code, params, input changes) in the .snakemake directory has been reduced by a factor of 10, which should help with NFS and IO bottlenecks. This is a breaking change in the sense that Snakemake 4.x won't see the metadata of workflows executed with Snakemake 3.x. However, old metadata won't be overwritten, so that you can always go back and check things by installing an older version of Snakemake again. - The google storage (GS) remote provider has been changed to use the google SDK. This is a breaking change, since the remote provider invocation has been simplified (see docs). - Due to WebDAV support (which uses asyncio), Snakemake now requires Python 3.5 at least. - Various minor bug fixes (e.g. for dynamic output files). [3.13.3] - 2017-06-23 --------------------- Changed ------- - Fix a followup bug in Namedlist where a single item was not returned as string. [3.13.2] - 2017-06-20 --------------------- Changed ------- - The --wrapper-prefix flag now also affects where the corresponding environment definition is fetched from. - Fix bug where empty output file list was recognized as containing duplicates (issue #574). [3.13.1] - 2017-06-20 --------------------- Changed ------- - Fix --conda-prefix to be passed to all jobs. - Fix cleanup issue with scripts that fail to download. [3.13.0] - 2017-06-12 --------------------- Added ----- - An NCBI remote provider. By this, you can seamlessly integrate any NCBI resouce (reference genome, gene/protein sequences, ...) as input file. # ## Changed - Snakemake now detects if automatically generated conda environments have to be recreated because the workflow has been moved to a new path. - Remote functionality has been made more robust, in particular to avoid race conditions. - ``--config`` parameter evaluation has been fixed for non-string types. - The Snakemake docker container is now based on the official debian image. [3.12.0] - 2017-05-09 --------------------- Added ----- - Support for RMarkdown (.Rmd) in script directives. - New option --debug-dag that prints all decisions while building the DAG of jobs. This helps to debug problems like cycles or unexpected MissingInputExceptions. - New option --conda-prefix to specify the place where conda environments are stored. Changed ------- - Benchmark files now also include the maximal RSS and VMS size of the Snakemake process and all sub processes. - Speedup conda environment creation. - Allow specification of DRMAA log dir. - Pass cluster config to subworkflow. [3.11.2] - 2017-03-15 --------------------- Changed ------- - Fixed fix handling of local URIs with the wrapper directive. [3.11.1] - 2017-03-14 --------------------- Changed ------- - --touch ignores missing files - Fixed handling of local URIs with the wrapper directive. [3.11.0] - 2017-03-08 --------------------- Added ----- - Param functions can now also refer to threads. # ## Changed - Improved tutorial and docs. - Made conda integration more robust. - None is converted to NULL in R scripts. [3.10.2] - 2017-02-28 --------------------- Changed ------- - Improved config file handling and merging. - Output files can be referred in params functions (i.e. lambda wildcards, output: ...) - Improved conda-environment creation. - Jobs are cached, leading to reduced memory footprint. - Fixed subworkflow handling in input functions. [3.10.0] - 2017-01-18 --------------------- Added ----- - Workflows can now be archived to a tarball with ``snakemake --archive my-workflow.tar.gz``. The archive contains all input files, source code versioned with git and all software packages that are defined via conda environments. Hence, the archive allows to fully reproduce a workflow on a different machine. Such an archive can be uploaded to Zenodo, such that your workflow is secured in a self-contained, executable way for the future. # ## Changed - Improved logging. - Reduced memory footprint. - Added a flag to automatically unpack the output of input functions. - Improved handling of HTTP redirects with remote files. - Improved exception handling with DRMAA. - Scripts referred by the script directive can now use locally defined external python modules. [3.9.1] - 2016-12-23 -------------------- Added ----- - Jobs can be restarted upon failure (--restart-times). # ## Changed - The docs have been restructured and improved. Now available under snakemake.readthedocs.org. - Changes in scripts show up with --list-code-changes. - Duplicate output files now cause an error. - Various bug fixes. [3.9.0] - 2016-11-15 -------------------- Added ----- - Ability to define isolated conda software environments (YAML) per rule. Environments will be deployed by Snakemake upon workflow execution. - Command line argument --wrapper-prefix in order to overwrite the default URL for looking up wrapper scripts. # ## Changed - --summary now displays the log files correspoding to each output file. - Fixed hangups when using run directive and a large number of jobs - Fixed pickling errors with anonymous rules and run directive. - Various small bug fixes [3.8.2] - 2016-09-23 -------------------- Changed ------- - Add missing import in rules.py. - Use threading only in cluster jobs. [3.8.1] - 2016-09-14 -------------------- Changed ------- - Snakemake now warns when using relative paths starting with "./". - The option -R now also accepts an empty list of arguments. - Bug fix when handling benchmark directive. - Jobscripts exit with code 1 in case of failure. This should improve the error messages of cluster system. - Fixed a bug in SFTP remote provider. [3.8.0] - 2016-08-26 -------------------- Added ----- - Wildcards can now be constrained by rule and globally via the new ``wildcard_constraints`` directive (see the `docs `__). - Subworkflows now allow to overwrite their config file via the configfile directive in the calling Snakefile. - A method ``log_fmt_shell`` in the snakemake proxy object that is available in scripts and wrappers allows to obtain a formatted string to redirect logging output from STDOUT or STDERR. - Functions given to resources can now optionally contain an additional argument ``input`` that refers to the input files. - Functions given to params can now optionally contain additional arguments ``input`` (see above) and ``resources``. The latter refers to the resources. - It is now possible to let items in shell commands be automatically quoted (see the `docs `__). This is usefull when dealing with filenames that contain whitespaces. Changed ------- - Snakemake now deletes output files before job exection. Further, it touches output files after job execution. This solves various problems with slow NFS filesystems. - A bug was fixed that caused dynamic output rules to be executed multiple times when forcing their execution with -R. - A bug causing double uploads with remote files was fixed. Various additional bug fixes related to remote files. - Various minor bug fixes. [3.7.1] - 2016-05-16 -------------------- Changed ------- - Fixed a missing import of the multiprocessing module. [3.7.0] - 2016-05-05 -------------------- Added ----- - The entries in ``resources`` and the ``threads`` job attribute can now be callables that must return ``int`` values. - Multiple ``--cluster-config`` arguments can be given to the Snakemake command line. Later one override earlier ones. - In the API, multiple ``cluster_config`` paths can be given as a list, alternatively to the previous behaviour of expecting one string for this parameter. - When submitting cluster jobs (either through ``--cluster`` or ``--drmaa``), you can now use ``--max-jobs-per-second`` to limit the number of jobs being submitted (also available through Snakemake API). Some cluster installations have problems with too many jobs per second. - Wildcard values are now printed upon job execution in addition to input and output files. # ## Changed - Fixed a bug with HTTP remote providers. [3.6.1] - 2016-04-08 -------------------- Changed ------- - Work around missing RecursionError in Python < 3.5 - Improved conversion of numpy and pandas data structures to R scripts. - Fixed locking of working directory. [3.6.0] - 2016-03-10 -------------------- Added ----- - onstart handler, that allows to add code that shall be only executed before the actual workflow execution (not on dryrun). - Parameters defined in the cluster config file are now accessible in the job properties under the key "cluster". - The wrapper directive can be considered stable. # ## Changed - Allow to use rule/job parameters with braces notation in cluster config. - Show a proper error message in case of recursion errors. - Remove non-empty temp dirs. - Don't set the process group of Snakemake in order to allow kill signals from parent processes to be propagated. - Fixed various corner case bugs. - The params directive no longer converts a list ``l`` implicitly to ``" ".join(l)``. [3.5.5] - 2016-01-23 -------------------- Added ----- - New experimental wrapper directive, which allows to refer to re-usable `wrapper scripts `__. Wrappers are provided in the `Snakemake Wrapper Repository `__. - David Koppstein implemented two new command line options to constrain the execution of the DAG of job to sub-DAGs (--until and --omit-from). # ## Changed - Fixed various bugs, e.g. with shadow jobs and --latency-wait. [3.5.4] - 2015-12-04 -------------------- Changed ------- - The params directive now fully supports non-string parameters. Several bugs in the remote support were fixed. [3.5.3] - 2015-11-24 -------------------- Changed ------- - The missing remote module was added to the package. [3.5.2] - 2015-11-24 -------------------- Added ----- - Support for easy integration of external R and Python scripts via the new `script directive `__. - Chris Tomkins-Tinch has implemented support for remote files: Snakemake can now handle input and output files from Amazon S3, Google Storage, FTP, SFTP, HTTP and Dropbox. - Simon Ye has implemented support for sandboxing jobs with `shadow rules `__. Changed ------- - Manuel Holtgrewe has fixed dynamic output files in combination with multiple wildcards. - It is now possible to add suffixes to all shell commands with shell.suffix("mysuffix"). - Job execution has been refactored to spawn processes only when necessary, resolving several problems in combination with huge workflows consisting of thousands of jobs and reducing the memory footprint. - In order to reflect the new collaborative development model, Snakemake has moved from my personal bitbucket account to http://snakemake.bitbucket.org. [3.4.2] - 2015-09-12 -------------------- Changed ------- - Willem Ligtenberg has reduced the memory usage of Snakemake. - Per Unneberg has improved config file handling to provide a more intuitive overwrite behavior. - Simon Ye has improved the test suite of Snakemake and helped with setting up continuous integration via Codeship. - The cluster implementation has been rewritten to use only a single thread to wait for jobs. This avoids failures with large numbers of jobs. - Benchmarks are now writing tab-delimited text files instead of JSON. - Snakemake now always requires to set the number of jobs with -j when in cluster mode. Set this to a high value if your cluster does not have restrictions. - The Snakemake Conda package has been moved to the bioconda channel. - The handling of Symlinks was improved, which made a switch to Python 3.3 as the minimum required Python version necessary. [3.4.1] - 2015-08-05 -------------------- Changed ------- - This release fixes a bug that caused named input or output files to always be returned as lists instead of single files. [3.4] - 2015-07-18 ------------------ Added ----- - This release adds support for executing jobs on clusters in synchronous mode (e.g. qsub -sync). Thanks to David Alexander for implementing this. - There is now vim syntax highlighting support (thanks to Jay Hesselberth). - Snakemake is now available as Conda package. Changed ------- - Lots of bugs have been fixed. Thanks go to e.g. David Koppstein, Marcel Martin, John Huddleston and Tao Wen for helping with useful reports and debugging. See `here `__ for older changes. snakemake-5.10.0/Dockerfile000066400000000000000000000017601361131222100155220ustar00rootroot00000000000000FROM bitnami/minideb:stretch MAINTAINER Johannes Köster ADD . /tmp/repo WORKDIR /tmp/repo ENV PATH /opt/conda/bin:${PATH} ENV LANG C.UTF-8 ENV SHELL /bin/bash RUN /bin/bash -c "install_packages wget bzip2 ca-certificates gnupg2 squashfs-tools git && \ wget -O- http://neuro.debian.net/lists/xenial.us-ca.full > /etc/apt/sources.list.d/neurodebian.sources.list && \ wget -O- http://neuro.debian.net/_static/neuro.debian.net.asc | apt-key add - && \ install_packages singularity-container && \ wget https://repo.continuum.io/miniconda/Miniconda3-latest-Linux-x86_64.sh && \ bash Miniconda3-latest-Linux-x86_64.sh -b -p /opt/conda && \ rm Miniconda3-latest-Linux-x86_64.sh && \ conda env create -n snakemake --file /tmp/repo/environment.yml && \ conda clean --all -y && \ source activate snakemake && \ which python && \ pip install ." RUN echo "source activate snakemake" > ~/.bashrc ENV PATH /opt/conda/envs/snakemake/bin:${PATH} snakemake-5.10.0/LICENSE.md000066400000000000000000000021131361131222100151250ustar00rootroot00000000000000Copyright (c) 2012-2019 Johannes Köster Permission is hereby granted, free of charge, to any person obtaining a copy of this software and associated documentation files (the "Software"), to deal in the Software without restriction, including without limitation the rights to use, copy, modify, merge, publish, distribute, sublicense, and/or sell copies of the Software, and to permit persons to whom the Software is furnished to do so, subject to the following conditions: The above copyright notice and this permission notice shall be included in all copies or substantial portions of the Software. THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY, FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM, OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE SOFTWARE. snakemake-5.10.0/MANIFEST.in000066400000000000000000000001071361131222100152600ustar00rootroot00000000000000include versioneer.py include snakemake/_version.py include LICENSE.md snakemake-5.10.0/README.md000066400000000000000000000036071361131222100150110ustar00rootroot00000000000000[![GitHub actions status](https://github.com/snakemake/snakemake/workflows/CI/badge.svg?branch=master)](https://github.com/snakemake/snakemake/actions?query=branch%3Amaster+workflow%3ACI) [![Sonarcloud Status](https://sonarcloud.io/api/project_badges/measure?project=snakemake_snakemake&metric=alert_status)](https://sonarcloud.io/dashboard?id=snakemake_snakemake) [![Bioconda](https://img.shields.io/conda/dn/bioconda/snakemake.svg?label=Bioconda)](https://bioconda.github.io/recipes/snakemake/README.html) [![Pypi](https://img.shields.io/pypi/pyversions/snakemake.svg)](https://pypi.org/project/snakemake) [![Docker Cloud Build Status](https://img.shields.io/docker/cloud/build/snakemake/snakemake)](https://hub.docker.com/r/snakemake/snakemake) [![Stack Overflow](https://img.shields.io/badge/stack-overflow-orange.svg)](https://stackoverflow.com/questions/tagged/snakemake) [![Twitter](https://img.shields.io/twitter/follow/johanneskoester.svg?style=social&label=Follow)](https://twitter.com/search?l=&q=%23snakemake%20from%3Ajohanneskoester) [![Github stars](https://img.shields.io/github/stars/snakemake/snakemake?style=social)](https://github.com/snakemake/snakemake/stargazers) # Snakemake The Snakemake workflow management system is a tool to create **reproducible and scalable** data analyses. Workflows are described via a human readable, Python based language. They can be seamlessly scaled to server, cluster, grid and cloud environments without the need to modify the workflow definition. Finally, Snakemake workflows can entail a description of required software, which will be automatically deployed to any execution environment. **Homepage: https://snakemake.readthedocs.io** **Note: Snakemake has just (Oct 4 2019) moved from bitbucket.org/snakemake/snakemake to Github. Forks and stars are not yet insightful here!** Copyright (c) 2012-2019 Johannes Köster (see LICENSE) snakemake-5.10.0/doc-environment.yml000066400000000000000000000005141361131222100173560ustar00rootroot00000000000000channels: - conda-forge dependencies: - python >=3.5 - datrie - wrapt - pyyaml - requests - appdirs - docutils - ratelimiter - configargparse - jsonschema - gitpython - sphinx - pip: - sphinxcontrib-napoleon - sphinx-argparse - sphinx_rtd_theme - docutils==0.12 - recommonmark - commonmark snakemake-5.10.0/docs/000077500000000000000000000000001361131222100144545ustar00rootroot00000000000000snakemake-5.10.0/docs/Makefile000066400000000000000000000151661361131222100161250ustar00rootroot00000000000000# Makefile for Sphinx documentation # # You can set these variables from the command line. SPHINXOPTS = SPHINXBUILD = sphinx-build PAPER = BUILDDIR = _build # User-friendly check for sphinx-build ifeq ($(shell which $(SPHINXBUILD) >/dev/null 2>&1; echo $$?), 1) $(error The '$(SPHINXBUILD)' command was not found. Make sure you have Sphinx installed, then set the SPHINXBUILD environment variable to point to the full path of the '$(SPHINXBUILD)' executable. Alternatively you can add the directory with the executable to your PATH. If you don't have Sphinx installed, grab it from http://sphinx-doc.org/) endif # Internal variables. PAPEROPT_a4 = -D latex_paper_size=a4 PAPEROPT_letter = -D latex_paper_size=letter ALLSPHINXOPTS = -d $(BUILDDIR)/doctrees $(PAPEROPT_$(PAPER)) $(SPHINXOPTS) . # the i18n builder cannot share the environment and doctrees with the others I18NSPHINXOPTS = $(PAPEROPT_$(PAPER)) $(SPHINXOPTS) . .PHONY: help clean html dirhtml singlehtml pickle json htmlhelp qthelp devhelp epub latex latexpdf text man changes linkcheck doctest gettext help: @echo "Please use \`make ' where is one of" @echo " html to make standalone HTML files" @echo " dirhtml to make HTML files named index.html in directories" @echo " singlehtml to make a single large HTML file" @echo " pickle to make pickle files" @echo " json to make JSON files" @echo " htmlhelp to make HTML files and a HTML help project" @echo " qthelp to make HTML files and a qthelp project" @echo " devhelp to make HTML files and a Devhelp project" @echo " epub to make an epub" @echo " latex to make LaTeX files, you can set PAPER=a4 or PAPER=letter" @echo " latexpdf to make LaTeX files and run them through pdflatex" @echo " latexpdfja to make LaTeX files and run them through platex/dvipdfmx" @echo " text to make text files" @echo " man to make manual pages" @echo " texinfo to make Texinfo files" @echo " info to make Texinfo files and run them through makeinfo" @echo " gettext to make PO message catalogs" @echo " changes to make an overview of all changed/added/deprecated items" @echo " xml to make Docutils-native XML files" @echo " pseudoxml to make pseudoxml-XML files for display purposes" @echo " linkcheck to check all external links for integrity" @echo " doctest to run all doctests embedded in the documentation (if enabled)" clean: rm -rf $(BUILDDIR)/* html: $(SPHINXBUILD) -b html $(ALLSPHINXOPTS) $(BUILDDIR)/html @echo @echo "Build finished. The HTML pages are in $(BUILDDIR)/html." dirhtml: $(SPHINXBUILD) -b dirhtml $(ALLSPHINXOPTS) $(BUILDDIR)/dirhtml @echo @echo "Build finished. The HTML pages are in $(BUILDDIR)/dirhtml." singlehtml: $(SPHINXBUILD) -b singlehtml $(ALLSPHINXOPTS) $(BUILDDIR)/singlehtml @echo @echo "Build finished. The HTML page is in $(BUILDDIR)/singlehtml." pickle: $(SPHINXBUILD) -b pickle $(ALLSPHINXOPTS) $(BUILDDIR)/pickle @echo @echo "Build finished; now you can process the pickle files." json: $(SPHINXBUILD) -b json $(ALLSPHINXOPTS) $(BUILDDIR)/json @echo @echo "Build finished; now you can process the JSON files." htmlhelp: $(SPHINXBUILD) -b htmlhelp $(ALLSPHINXOPTS) $(BUILDDIR)/htmlhelp @echo @echo "Build finished; now you can run HTML Help Workshop with the" \ ".hhp project file in $(BUILDDIR)/htmlhelp." qthelp: $(SPHINXBUILD) -b qthelp $(ALLSPHINXOPTS) $(BUILDDIR)/qthelp @echo @echo "Build finished; now you can run "qcollectiongenerator" with the" \ ".qhcp project file in $(BUILDDIR)/qthelp, like this:" @echo "# qcollectiongenerator $(BUILDDIR)/qthelp/Snakemake.qhcp" @echo "To view the help file:" @echo "# assistant -collectionFile $(BUILDDIR)/qthelp/Snakemake.qhc" devhelp: $(SPHINXBUILD) -b devhelp $(ALLSPHINXOPTS) $(BUILDDIR)/devhelp @echo @echo "Build finished." @echo "To view the help file:" @echo "# mkdir -p $$HOME/.local/share/devhelp/Snakemake" @echo "# ln -s $(BUILDDIR)/devhelp $$HOME/.local/share/devhelp/Snakemake" @echo "# devhelp" epub: $(SPHINXBUILD) -b epub $(ALLSPHINXOPTS) $(BUILDDIR)/epub @echo @echo "Build finished. The epub file is in $(BUILDDIR)/epub." latex: $(SPHINXBUILD) -b latex $(ALLSPHINXOPTS) $(BUILDDIR)/latex @echo @echo "Build finished; the LaTeX files are in $(BUILDDIR)/latex." @echo "Run \`make' in that directory to run these through (pdf)latex" \ "(use \`make latexpdf' here to do that automatically)." latexpdf: $(SPHINXBUILD) -b latex $(ALLSPHINXOPTS) $(BUILDDIR)/latex @echo "Running LaTeX files through pdflatex..." $(MAKE) -C $(BUILDDIR)/latex all-pdf @echo "pdflatex finished; the PDF files are in $(BUILDDIR)/latex." latexpdfja: $(SPHINXBUILD) -b latex $(ALLSPHINXOPTS) $(BUILDDIR)/latex @echo "Running LaTeX files through platex and dvipdfmx..." $(MAKE) -C $(BUILDDIR)/latex all-pdf-ja @echo "pdflatex finished; the PDF files are in $(BUILDDIR)/latex." text: $(SPHINXBUILD) -b text $(ALLSPHINXOPTS) $(BUILDDIR)/text @echo @echo "Build finished. The text files are in $(BUILDDIR)/text." man: $(SPHINXBUILD) -b man $(ALLSPHINXOPTS) $(BUILDDIR)/man @echo @echo "Build finished. The manual pages are in $(BUILDDIR)/man." texinfo: $(SPHINXBUILD) -b texinfo $(ALLSPHINXOPTS) $(BUILDDIR)/texinfo @echo @echo "Build finished. The Texinfo files are in $(BUILDDIR)/texinfo." @echo "Run \`make' in that directory to run these through makeinfo" \ "(use \`make info' here to do that automatically)." info: $(SPHINXBUILD) -b texinfo $(ALLSPHINXOPTS) $(BUILDDIR)/texinfo @echo "Running Texinfo files through makeinfo..." make -C $(BUILDDIR)/texinfo info @echo "makeinfo finished; the Info files are in $(BUILDDIR)/texinfo." gettext: $(SPHINXBUILD) -b gettext $(I18NSPHINXOPTS) $(BUILDDIR)/locale @echo @echo "Build finished. The message catalogs are in $(BUILDDIR)/locale." changes: $(SPHINXBUILD) -b changes $(ALLSPHINXOPTS) $(BUILDDIR)/changes @echo @echo "The overview file is in $(BUILDDIR)/changes." linkcheck: $(SPHINXBUILD) -b linkcheck $(ALLSPHINXOPTS) $(BUILDDIR)/linkcheck @echo @echo "Link check complete; look for any errors in the above output " \ "or in $(BUILDDIR)/linkcheck/output.txt." doctest: $(SPHINXBUILD) -b doctest $(ALLSPHINXOPTS) $(BUILDDIR)/doctest @echo "Testing of doctests in the sources finished, look at the " \ "results in $(BUILDDIR)/doctest/output.txt." xml: $(SPHINXBUILD) -b xml $(ALLSPHINXOPTS) $(BUILDDIR)/xml @echo @echo "Build finished. The XML files are in $(BUILDDIR)/xml." pseudoxml: $(SPHINXBUILD) -b pseudoxml $(ALLSPHINXOPTS) $(BUILDDIR)/pseudoxml @echo @echo "Build finished. The pseudo-XML files are in $(BUILDDIR)/pseudoxml." snakemake-5.10.0/docs/_static/000077500000000000000000000000001361131222100161025ustar00rootroot00000000000000snakemake-5.10.0/docs/_static/sphinx-argparse.css000066400000000000000000000002011361131222100217200ustar00rootroot00000000000000.wy-table-responsive table td { white-space: normal !important; } .wy-table-responsive { overflow: visible !important; } snakemake-5.10.0/docs/api_reference/000077500000000000000000000000001361131222100172435ustar00rootroot00000000000000snakemake-5.10.0/docs/api_reference/internal/000077500000000000000000000000001361131222100210575ustar00rootroot00000000000000snakemake-5.10.0/docs/api_reference/internal/modules.rst000066400000000000000000000002021361131222100232530ustar00rootroot00000000000000Internal API ============ These pages document the entire internal API of Snakemake. .. toctree:: :maxdepth: 4 snakemake snakemake-5.10.0/docs/api_reference/internal/snakemake.remote.rst000066400000000000000000000045331361131222100250470ustar00rootroot00000000000000snakemake.remote package ======================== Submodules ---------- snakemake.remote.EGA module --------------------------- .. automodule:: snakemake.remote.EGA :members: :undoc-members: :show-inheritance: snakemake.remote.FTP module --------------------------- .. automodule:: snakemake.remote.FTP :members: :undoc-members: :show-inheritance: snakemake.remote.GS module -------------------------- .. automodule:: snakemake.remote.GS :members: :undoc-members: :show-inheritance: snakemake.remote.HTTP module ---------------------------- .. automodule:: snakemake.remote.HTTP :members: :undoc-members: :show-inheritance: snakemake.remote.NCBI module ---------------------------- .. automodule:: snakemake.remote.NCBI :members: :undoc-members: :show-inheritance: snakemake.remote.S3 module -------------------------- .. automodule:: snakemake.remote.S3 :members: :undoc-members: :show-inheritance: snakemake.remote.S3Mocked module -------------------------------- .. automodule:: snakemake.remote.S3Mocked :members: :undoc-members: :show-inheritance: snakemake.remote.SFTP module ---------------------------- .. automodule:: snakemake.remote.SFTP :members: :undoc-members: :show-inheritance: snakemake.remote.XRootD module ------------------------------ .. automodule:: snakemake.remote.XRootD :members: :undoc-members: :show-inheritance: snakemake.remote.dropbox module ------------------------------- .. automodule:: snakemake.remote.dropbox :members: :undoc-members: :show-inheritance: snakemake.remote.gfal module ---------------------------- .. automodule:: snakemake.remote.gfal :members: :undoc-members: :show-inheritance: snakemake.remote.gridftp module ------------------------------- .. automodule:: snakemake.remote.gridftp :members: :undoc-members: :show-inheritance: snakemake.remote.iRODS module ----------------------------- .. automodule:: snakemake.remote.iRODS :members: :undoc-members: :show-inheritance: snakemake.remote.webdav module ------------------------------ .. automodule:: snakemake.remote.webdav :members: :undoc-members: :show-inheritance: Module contents --------------- .. automodule:: snakemake.remote :members: :undoc-members: :show-inheritance: snakemake-5.10.0/docs/api_reference/internal/snakemake.report.rst000066400000000000000000000002561361131222100250650ustar00rootroot00000000000000snakemake.report package ======================== Module contents --------------- .. automodule:: snakemake.report :members: :undoc-members: :show-inheritance: snakemake-5.10.0/docs/api_reference/internal/snakemake.rst000066400000000000000000000073631361131222100235610ustar00rootroot00000000000000snakemake package ================= Subpackages ----------- .. toctree:: snakemake.remote snakemake.report Submodules ---------- snakemake.benchmark module -------------------------- .. automodule:: snakemake.benchmark :members: :undoc-members: :show-inheritance: snakemake.checkpoints module ---------------------------- .. automodule:: snakemake.checkpoints :members: :undoc-members: :show-inheritance: snakemake.common module ----------------------- .. automodule:: snakemake.common :members: :undoc-members: :show-inheritance: snakemake.conda module ---------------------- .. automodule:: snakemake.conda :members: :undoc-members: :show-inheritance: snakemake.cwl module -------------------- .. automodule:: snakemake.cwl :members: :undoc-members: :show-inheritance: snakemake.dag module -------------------- .. automodule:: snakemake.dag :members: :undoc-members: :show-inheritance: snakemake.decorators module --------------------------- .. automodule:: snakemake.decorators :members: :undoc-members: :show-inheritance: snakemake.exceptions module --------------------------- .. automodule:: snakemake.exceptions :members: :undoc-members: :show-inheritance: snakemake.executors module -------------------------- .. automodule:: snakemake.executors :members: :undoc-members: :show-inheritance: snakemake.gui module -------------------- .. automodule:: snakemake.gui :members: :undoc-members: :show-inheritance: snakemake.io module ------------------- .. automodule:: snakemake.io :members: :undoc-members: :show-inheritance: snakemake.jobs module --------------------- .. automodule:: snakemake.jobs :members: :undoc-members: :show-inheritance: snakemake.logging module ------------------------ .. automodule:: snakemake.logging :members: :undoc-members: :show-inheritance: snakemake.output\_index module ------------------------------ .. automodule:: snakemake.output_index :members: :undoc-members: :show-inheritance: snakemake.parser module ----------------------- .. automodule:: snakemake.parser :members: :undoc-members: :show-inheritance: snakemake.persistence module ---------------------------- .. automodule:: snakemake.persistence :members: :undoc-members: :show-inheritance: snakemake.rules module ---------------------- .. automodule:: snakemake.rules :members: :undoc-members: :show-inheritance: snakemake.scheduler module -------------------------- .. automodule:: snakemake.scheduler :members: :undoc-members: :show-inheritance: snakemake.script module ----------------------- .. automodule:: snakemake.script :members: :undoc-members: :show-inheritance: snakemake.shell module ---------------------- .. automodule:: snakemake.shell :members: :undoc-members: :show-inheritance: snakemake.singularity module ---------------------------- .. automodule:: snakemake.singularity :members: :undoc-members: :show-inheritance: snakemake.stats module ---------------------- .. automodule:: snakemake.stats :members: :undoc-members: :show-inheritance: snakemake.utils module ---------------------- .. automodule:: snakemake.utils :members: :undoc-members: :show-inheritance: snakemake.workflow module ------------------------- .. automodule:: snakemake.workflow :members: :undoc-members: :show-inheritance: snakemake.wrapper module ------------------------ .. automodule:: snakemake.wrapper :members: :undoc-members: :show-inheritance: Module contents --------------- .. automodule:: snakemake :members: :undoc-members: :show-inheritance: snakemake-5.10.0/docs/api_reference/snakemake.rst000066400000000000000000000001511361131222100217310ustar00rootroot00000000000000.. _api_reference_snakemake: The Snakemake API ================= .. autofunction:: snakemake.snakemake snakemake-5.10.0/docs/api_reference/snakemake_utils.rst000066400000000000000000000001411361131222100231500ustar00rootroot00000000000000.. _utils-api: Additional utils ================ .. automodule:: snakemake.utils :members: snakemake-5.10.0/docs/conf.py000066400000000000000000000206201361131222100157530ustar00rootroot00000000000000#!/usr/bin/env python3 # -*- coding: utf-8 -*- # # Snakemake documentation build configuration file, created by # sphinx-quickstart on Sat Feb 1 16:01:02 2014. # # This file is execfile()d with the current directory set to its # containing dir. # # Note that not all possible configuration values are present in this # autogenerated file. # # All configuration values have a default; values that are commented out # serve to show the default. import sys import os from recommonmark.parser import CommonMarkParser source_parsers = {'.md': CommonMarkParser} # If extensions (or modules to document with autodoc) are in another directory, # add these directories to sys.path here. If the directory is relative to the # documentation root, use os.path.abspath to make it absolute, like shown here. sys.path.insert(0, os.path.abspath('../')) # -- General configuration ------------------------------------------------ # If your documentation needs a minimal Sphinx version, state it here. #needs_sphinx = '1.0' # Add any Sphinx extension module names here, as strings. They can be # extensions coming with Sphinx (named 'sphinx.ext.*') or your custom # ones. extensions = [ 'sphinx.ext.autodoc', 'sphinx.ext.mathjax', 'sphinx.ext.viewcode', 'sphinxcontrib.napoleon', 'sphinxarg.ext' ] # Add any paths that contain templates here, relative to this directory. templates_path = ['_templates'] # The suffix of source filenames. source_suffix = ['.rst', '.md'] # The encoding of source files. #source_encoding = 'utf-8-sig' # The master toctree document. master_doc = 'index' # General information about the project. project = 'Snakemake' copyright = '2014-2016, Johannes Koester' import snakemake # The version info for the project you're documenting, acts as replacement for # |version| and |release|, also used in various other places throughout the # built documents. # # The short X.Y version. version = snakemake.__version__ # The full version, including alpha/beta/rc tags. release = snakemake.__version__ # The language for content autogenerated by Sphinx. Refer to documentation # for a list of supported languages. #language = None # There are two options for replacing |today|: either, you set today to some # non-false value, then it is used: #today = '' # Else, today_fmt is used as the format for a strftime call. #today_fmt = '%B %d, %Y' # List of patterns, relative to source directory, that match files and # directories to ignore when looking for source files. exclude_patterns = ['_build'] # The reST default role (used for this markup: `text`) to use for all # documents. #default_role = None # If true, '()' will be appended to :func: etc. cross-reference text. #add_function_parentheses = True # If true, the current module name will be prepended to all description # unit titles (such as .. function::). #add_module_names = True # If true, sectionauthor and moduleauthor directives will be shown in the # output. They are ignored by default. #show_authors = False # The name of the Pygments (syntax highlighting) style to use. pygments_style = 'sphinx' # A list of ignored prefixes for module index sorting. #modindex_common_prefix = [] # If true, keep warnings as "system message" paragraphs in the built documents. #keep_warnings = False # -- Options for HTML output ---------------------------------------------- # The theme to use for HTML and HTML Help pages. See the documentation for # a list of builtin themes. html_theme = 'sphinx_rtd_theme' # Theme options are theme-specific and customize the look and feel of a theme # further. For a list of options available for each theme, see the # documentation. #html_theme_options = {} # Add any paths that contain custom themes here, relative to this directory. #html_theme_path = sphinx_bootstrap_theme.get_html_theme_path() # The name for this set of Sphinx documents. If None, it defaults to # " v documentation". #html_title = None # A shorter title for the navigation bar. Default is the same as html_title. #html_short_title = None # The name of an image file (relative to this directory) to place at the top # of the sidebar. #html_logo = None # The name of an image file (within the static path) to use as favicon of the # docs. This file should be a Windows icon file (.ico) being 16x16 or 32x32 # pixels large. #html_favicon = None # Add any paths that contain custom static files (such as style sheets) here, # relative to this directory. They are copied after the builtin static files, # so a file named "default.css" will overwrite the builtin "default.css". html_static_path = ['_static'] # Add any extra paths that contain custom files (such as robots.txt or # .htaccess) here, relative to this directory. These files are copied # directly to the root of the documentation. #html_extra_path = [] # If not '', a 'Last updated on:' timestamp is inserted at every page bottom, # using the given strftime format. #html_last_updated_fmt = '%b %d, %Y' # If true, SmartyPants will be used to convert quotes and dashes to # typographically correct entities. #html_use_smartypants = True # Custom sidebar templates, maps document names to template names. #html_sidebars = {} # Additional templates that should be rendered to pages, maps page names to # template names. #html_additional_pages = {} # If false, no module index is generated. #html_domain_indices = True # If false, no index is generated. #html_use_index = True # If true, the index is split into individual pages for each letter. #html_split_index = False # If true, links to the reST sources are added to the pages. #html_show_sourcelink = True # If true, "Created using Sphinx" is shown in the HTML footer. Default is True. #html_show_sphinx = True # If true, "(C) Copyright ..." is shown in the HTML footer. Default is True. #html_show_copyright = True # If true, an OpenSearch description file will be output, and all pages will # contain a tag referring to it. The value of this option must be the # base URL from which the finished HTML is served. #html_use_opensearch = '' # This is the file name suffix for HTML files (e.g. ".xhtml"). #html_file_suffix = None # Output file base name for HTML help builder. htmlhelp_basename = 'Snakemakedoc' # -- Options for LaTeX output --------------------------------------------- latex_elements = { # The paper size ('letterpaper' or 'a4paper'). #'papersize': 'letterpaper', # The font size ('10pt', '11pt' or '12pt'). #'pointsize': '10pt', # Additional stuff for the LaTeX preamble. #'preamble': '', } # Grouping the document tree into LaTeX files. List of tuples # (source start file, target name, title, # author, documentclass [howto, manual, or own class]). latex_documents = [ ('index', 'Snakemake.tex', 'Snakemake Documentation', 'Johannes Koester', 'manual'), ] # The name of an image file (relative to this directory) to place at the top of # the title page. #latex_logo = None # For "manual" documents, if this is true, then toplevel headings are parts, # not chapters. #latex_use_parts = False # If true, show page references after internal links. #latex_show_pagerefs = False # If true, show URL addresses after external links. #latex_show_urls = False # Documents to append as an appendix to all manuals. #latex_appendices = [] # If false, no module index is generated. #latex_domain_indices = True # -- Options for manual page output --------------------------------------- # One entry per manual page. List of tuples # (source start file, name, description, authors, manual section). man_pages = [ ('index', 'snakemake', 'Snakemake Documentation', ['Johannes Koester'], 1) ] # If true, show URL addresses after external links. #man_show_urls = False # -- Options for Texinfo output ------------------------------------------- # Grouping the document tree into Texinfo files. List of tuples # (source start file, target name, title, author, # dir menu entry, description, category) texinfo_documents = [ ('index', 'Snakemake', 'Snakemake Documentation', 'Johannes Koester', 'Snakemake', 'One line description of project.', 'Miscellaneous'), ] # Documents to append as an appendix to all manuals. #texinfo_appendices = [] # If false, no module index is generated. #texinfo_domain_indices = True # How to display URL addresses: 'footnote', 'no', or 'inline'. #texinfo_show_urls = 'footnote' # If true, do not generate a @detailmenu in the "Top" node's menu. #texinfo_no_detailmenu = False def setup(app): app.add_stylesheet('sphinx-argparse.css') snakemake-5.10.0/docs/executing/000077500000000000000000000000001361131222100164475ustar00rootroot00000000000000snakemake-5.10.0/docs/executing/caching.rst000066400000000000000000000064571361131222100206110ustar00rootroot00000000000000.. _caching: ======================== Between workflow caching ======================== Within certain data analysis fields, there are certain intermediate results that reoccur in exactly the same way in many analysis. For example, in bioinformatics, reference genomes or annotations are downloaded, and read mapping indexes are built. Since such steps are independent of the actual data or measurements that are analyzed, but still computationally or timely expensive to conduct, it has been common practice to externalize their computation and assume the presence of the resulting files before execution of a workflow. From version 5.8.0 on, Snakemake offers a way to keep those steps inside the actual analysis without requiring from redundant computations. By hashing all steps, parameters, software stacks (in terms of conda environments or containers), and raw input required up to a certain step in a `blockchain `_, Snakemake is able to recognize **before** the computation whether a certain result is already available in a central cache on the same system. **Note that this is explicitly intended for caching results between workflows! There is no need to use this feature to avoid redundant computations within a workflow. Snakemake does this already out of the box.** Such caching has to be explitly activated per rule, which can be done via the command line interface. For example, .. code-block:: console $ export SNAKEMAKE_OUTPUT_CACHE=/mnt/snakemake-cache/ $ snakemake --cache download_reference create_index would instruct Snakemake to cache and reuse the results of the rules ``download_reference``and ``create_index``. The environment variable definition that happens in the first line (defining the location of the cache) should of course be done only once and system wide in reality. When Snakemake is executed without a shared filesystem (e.g., in the cloud, see :ref:`cloud`), the environment variable has to point to a location compatible with the given remote provider (e.g. an S3 or Google Storage bucket). In any case, the provided location should be shared between all workflows of your group, institute or computing environment, in order to benefit from the reuse of previously obtained intermediate results. Note that only rules with just a single output file (or directory) or with :ref:`multiext output files ` are eligible for caching. The reason is that for other rules it would be impossible to unambiguously assign the output files to cache entrys while being agnostic of the actual file names. Also note that the rules need to retrieve all their parameters via the ``params`` directive (except input files). It is not allowed to directly use ``wildcards``, ``config`` or any global variable in the shell command or script, because these are not captured in the hash (otherwise, reuse would be unnecessarily limited). Also note that Snakemake will store everything in the cache as readable and writeable for **all users** on the system (except in the remote case, where permissions are not enforced and depend on your storage configuration). Hence, caching is not intended for private data, just for steps that deal with publicly available resources. Finally, be aware that the implementation has to be considered **experimental** until this note is removed.snakemake-5.10.0/docs/executing/cli.rst000066400000000000000000000117431361131222100177560ustar00rootroot00000000000000.. _executable: ====================== Command line interface ====================== This part of the documentation describes the ``snakemake`` executable. Snakemake is primarily a command-line tool, so the ``snakemake`` executable is the primary way to execute, debug, and visualize workflows. .. user_manual-snakemake_options: ----------------------------- Useful Command Line Arguments ----------------------------- If called without parameters, i.e. .. code-block:: console $ snakemake Snakemake tries to execute the workflow specified in a file called ``Snakefile`` in the same directory (instead, the Snakefile can be given via the parameter ``-s``). By issuing .. code-block:: console $ snakemake -n a dry-run can be performed. This is useful to test if the workflow is defined properly and to estimate the amount of needed computation. Further, the reason for each rule execution can be printed via .. code-block:: console $ snakemake -n -r Importantly, Snakemake can automatically determine which parts of the workflow can be run in parallel. By specifying the number of available cores, i.e. .. code-block:: console $ snakemake --cores 4 one can tell Snakemake to use up to 4 cores and solve a binary knapsack problem to optimize the scheduling of jobs. If the number is omitted (i.e., only ``--cores`` is given), the number of used cores is determined as the number of available CPU cores in the machine. Snakemake workflows usually define the number of used threads of certain rules. Sometimes, it makes sense to overwrite the defaults given in the workflow definition. This can be done by using the ``--set-threads`` argument, e.g., .. code-block:: console $ snakemake --cores 4 --set-threads myrule=2 would overwrite whatever number of threads has been defined for the rule ``myrule`` and use ``2`` instead. This can be particularly handy when used in combination with :ref:`cluster execution `. Dealing with very large workflows --------------------------------- If your workflow has a lot of jobs, Snakemake might need some time to infer the dependencies (the job DAG) and which jobs are actually required to run. The major bottleneck involved is the filesystem, which has to be queried for existence and modification dates of files. To overcome this issue, Snakemake allows to run large workflows in batches. This way, fewer files have to be evaluated at once, and therefore the job DAG can be inferred faster. By running .. code-block:: console $ snakemake --cores 4 --batch myrule=1/3 you instruct to only compute the first of three batches of the inputs of the rule `myrule`. To generate the second batch, run .. code-block:: console $ snakemake --cores 4 --batch myrule=2/3 Finally, when running .. code-block:: console $ snakemake --cores 4 --batch myrule=3/3 Snakemake will process beyond the rule `myrule`, because all of its input files have been generated, and complete the workflow. Obviously, a good choice of the rule to perform the batching is a rule that has a lot of input files and upstream jobs, for example a central aggregation step within your workflow. We advice all workflow developers to inform potential users of the best suited batching rule. .. _profiles: -------- Profiles -------- Adapting Snakemake to a particular environment can entail many flags and options. Therefore, since Snakemake 4.1, it is possible to specify a configuration profile to be used to obtain default options: .. code-block:: console $ snakemake --profile myprofile Here, a folder ``myprofile`` is searched in per-user and global configuration directories (on Linux, this will be ``$HOME/.config/snakemake`` and ``/etc/xdg/snakemake``, you can find the answer for your system via ``snakemake --help``). Alternatively, an absolute or relative path to the folder can be given. The profile folder is expected to contain a file ``config.yaml`` that defines default values for the Snakemake command line arguments. For example, the file .. code-block:: yaml cluster: qsub jobs: 100 would setup Snakemake to always submit to the cluster via the ``qsub`` command, and never use more than 100 parallel jobs in total. Under https://github.com/snakemake-profiles/doc, you can find publicly available profiles. Feel free to contribute your own. The profile folder can additionally contain auxilliary files, e.g., jobscripts, or any kind of wrappers. See https://github.com/snakemake-profiles/doc for examples. .. _all_options: ----------- All Options ----------- .. argparse:: :module: snakemake :func: get_argument_parser :prog: snakemake All command line options can be printed by calling ``snakemake -h``. .. _getting_started-bash_completion: --------------- Bash Completion --------------- Snakemake supports bash completion for filenames, rulenames and arguments. To enable it globally, just append .. code-block:: bash `snakemake --bash-completion` including the accents to your ``.bashrc``. This only works if the ``snakemake`` command is in your path. snakemake-5.10.0/docs/executing/cluster-cloud.rst000066400000000000000000000261231361131222100217720ustar00rootroot00000000000000=========================== Cluster and cloud execution =========================== .. _cloud: ------------- Cloud Support ------------- Snakemake 4.0 and later supports execution in the cloud via Kubernetes. This is independent of the cloud provider, but we provide the setup steps for GCE below. Google cloud engine ~~~~~~~~~~~~~~~~~~~ First, install the `Google Cloud SDK `_. Then, run .. code-block:: console $ gcloud init to setup your access. Then, you can create a new kubernetes cluster via .. code-block:: console $ gcloud container clusters create $CLUSTER_NAME --num-nodes=$NODES --scopes storage-rw with ``$CLUSTER_NAME`` being the cluster name and ``$NODES`` being the number of cluster nodes. If you intent to use google storage, make sure that `--scopes storage-rw` is set. This enables Snakemake to write to the google storage from within the cloud nodes. Next, you configure Kubernetes to use the new cluster via .. code-block:: console $ gcloud container clusters get-credentials $CLUSTER_NAME If you are having issues with authentication, please refer to the help text: .. code-block:: console $ gcloud container clusters get-credentials --help You likely also want to use google storage for reading and writing files. For this, you will additionally need to authenticate with your google cloud account via .. code-block:: console $ gcloud auth application-default login This enables Snakemake to access google storage in order to check existence and modification dates of files. Now, Snakemake is ready to use your cluster. **Important:** After finishing your work, do not forget to delete the cluster with .. code-block:: console $ gcloud container clusters delete $CLUSTER_NAME in order to avoid unnecessary charges. .. _kubernetes: Executing a Snakemake workflow via kubernetes ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ Assuming that kubernetes has been properly configured (see above), you can execute a workflow via: .. code-block:: console snakemake --kubernetes --use-conda --default-remote-provider $REMOTE --default-remote-prefix $PREFIX In this mode, Snakemake will assume all input and output files to be stored in a given remote location, configured by setting ``$REMOTE`` to your provider of choice (e.g. ``GS`` for Google cloud storage or ``S3`` for Amazon S3) and ``$PREFIX`` to a bucket name or subfolder within that remote storage. After successful execution, you find your results in the specified remote storage. Of course, if any input or output already defines a different remote location, the latter will be used instead. Importantly, this means that Snakemake does **not** require a shared network filesystem to work in the cloud. .. sidebar:: Note Consider to :ref:`group jobs ` in order to minimize overhead, in particular for short-running jobs. Currently, this mode requires that the Snakemake workflow is stored in a git repository. Snakemake uses git to query necessary source files (the Snakefile, scripts, config, ...) for workflow execution and encodes them into the kubernetes job. It is further possible to forward arbitrary environment variables to the kubernetes jobs via the flag ``--kubernetes-env`` (see ``snakemake --help``). When executing, Snakemake will make use of the defined resources and threads to schedule jobs to the correct nodes. In particular, it will forward memory requirements defined as `mem_mb` to kubernetes. Further, it will propagate the number of threads a job intends to use, such that kubernetes can allocate it to the correct cloud computing node. Executing a Snakemake workflow via Tibanna on Amazon Web Services ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ First, install `Tibanna `_. .. code-block:: console $ pip install -U tibanna Set up aws configuration either by creating files ``~/.aws/credentials`` and ``~/.aws/config`` or by setting up environment variables as below (see Tibanna or AWS documentation for more details): .. code-block:: console $ export AWS_ACCESS_KEY_ID= $ export AWS_SECRET_ACCESS_KEY= $ export AWS_DEFAULT_REGION= As an AWS admin, deploy Tibanna Unicorn to Cloud with permissions to a specific S3 bucket. Name the Unicorn / Unicorn usergroup with the ``--usergroup`` option. Unicorn is a serverless scheduler, and keeping unicorn on the cloud does not incur extra cost. One may have many different unicorns with different names and different bucket permissions. Then, add other (IAM) users to the user group that has permission to use this unicorn / buckets. .. code-block:: console $ tibanna deploy_unicorn -g -b $ tibanna add_user -u -g As a user that has been added to the group (or as an admin), set up the default unicorn. .. code-block:: console $ export TIBANNA_DEFAULT_STEP_FUNCTION_NAME=tibanna_unicorn_ Then, you can run as many snakemake runs as you wish as below, inside a directory that contains Snakefile and other necessary components (e.g. ``env.yml``, ``config.json``, ...). .. code-block:: console $ snakemake --tibanna --default-remote-prefix=/ [] In this mode, Snakemake will assume all input and output files to be stored in the specified remote location (a subdirectory inside a given S3 bucket.) After successful execution, you find your results in the specified remote storage. Of course, if any input or output already defines a different remote location, the latter will be used instead. In that case, Tibanna Unicorn must be deployed with all the relevant buckets (``-b bucket1,bucket2,bucket3,...``) to allow access to the Unicorn serverless components. Snakemake will assign 3x of the total input size as the allocated space for each execution. The execution may fail if the total input + output + temp file sizes exceed this estimate. In addition to regular snakemake options, ``--precommand=`` option allows sending a command to execute before executing each step on an isolated environment. This kind of command could involve downloading or installing necessary files that cannot be handled using conda (e.g. the command may begin with ``wget``, ``git clone``, etc.) To check Tibanna execution logs, first use ``tibanna stat`` to see the list of all the individual runs. .. code-block:: console $ tibanna stat -n -l Then, check the detailed log for each job using the Tibanna job id that can be obtained from the first column of the output of ``tibanna stat``. .. code-block:: console $ tibanna log -j .. sidebar:: Note Consider to :ref:`group jobs ` in order to minimize overhead, in particular for short-running jobs. When executing, Snakemake will make use of the defined resources and threads to schedule jobs to the correct nodes. In particular, it will forward memory requirements defined as `mem_mb` to Tibanna. Further, it will propagate the number of threads a job intends to use, such that Tibanna can allocate it to the most cost-effective cloud compute instance available. .. _cluster: ----------------- Cluster Execution ----------------- Snakemake can make use of cluster engines that support shell scripts and have access to a common filesystem, (e.g. the Sun Grid Engine). In this case, Snakemake simply needs to be given a submit command that accepts a shell script as first positional argument: .. code-block:: console $ snakemake --cluster qsub -j 32 Here, ``-j`` denotes the number of jobs submitted being submitted to the cluster at the same time (here 32). The cluster command can be decorated with job specific information, e.g. .. sidebar:: Note Consider to :ref:`group jobs ` in order to minimize overhead, in particular for short-running jobs. .. code-block:: console $ snakemake --cluster "qsub {threads}" Thereby, all keywords of a rule are allowed (e.g. rulename, params, input, output, threads, priority, ...). For example, you could encode the expected running time into params: .. code-block:: python rule: input: ... output: ... params: runtime="4h" shell: ... and forward it to the cluster scheduler: .. code-block:: console $ snakemake --cluster "qsub --runtime {params.runtime}" If your cluster system supports `DRMAA `_, Snakemake can make use of that to increase the control over jobs. E.g. jobs can be cancelled upon pressing ``Ctrl+C``, which is not possible with the generic ``--cluster`` support. With DRMAA, no ``qsub`` command needs to be provided, but system specific arguments can still be given as a string, e.g. .. code-block:: console $ snakemake --drmaa " -q username" -j 32 Note that the string has to contain a leading whitespace. Else, the arguments will be interpreted as part of the normal Snakemake arguments, and execution will fail. Job Properties ~~~~~~~~~~~~~~ When executing a workflow on a cluster using the ``--cluster`` parameter (see below), Snakemake creates a job script for each job to execute. This script is then invoked using the provided cluster submission command (e.g. ``qsub``). Sometimes you want to provide a custom wrapper for the cluster submission command that decides about additional parameters. As this might be based on properties of the job, Snakemake stores the job properties (e.g. name, rulename, threads, input, output, params etc.) as JSON inside the job script (for group jobs, the rulename will be "GROUP", otherwise it will be the same as the job name). For convenience, there exists a parser function `snakemake.utils.read_job_properties` that can be used to access the properties. The following shows an example job submission wrapper: .. code-block:: python #!python #!/usr/bin/env python3 import os import sys from snakemake.utils import read_job_properties jobscript = sys.argv[1] job_properties = read_job_properties(jobscript) # do something useful with the threads threads = job_properties[threads] # access property defined in the cluster configuration file (Snakemake >=3.6.0) job_properties["cluster"]["time"] os.system("qsub -t {threads} {script}".format(threads=threads, script=jobscript)) .. _getting_started-visualization: ------------- Visualization ------------- To visualize the workflow, one can use the option ``--dag``. This creates a representation of the DAG in the graphviz dot language which has to be postprocessed by the graphviz tool ``dot``. E.g. to visualize the DAG that would be executed, you can issue: .. code-block:: console $ snakemake --dag | dot | display For saving this to a file, you can specify the desired format: .. code-block:: console $ snakemake --dag | dot -Tpdf > dag.pdf To visualize the whole DAG regardless of the eventual presence of files, the ``forceall`` option can be used: .. code-block:: console $ snakemake --forceall --dag | dot -Tpdf > dag.pdf Of course the visual appearance can be modified by providing further command line arguments to ``dot``. snakemake-5.10.0/docs/executing/interoperability.rst000066400000000000000000000032521361131222100225700ustar00rootroot00000000000000 ================ Interoperability ================ .. _cwl_export: ---------- CWL export ---------- Snakemake workflows can be exported to `CWL `_, such that they can be executed in any `CWL-enabled workflow engine `_. Since, CWL is less powerful for expressing workflows than Snakemake (most importantly Snakemake offers more flexible scatter-gather patterns, since full Python can be used), export works such that every Snakemake job is encoded into a single step in the CWL workflow. Moreover, every step of that workflow calls Snakemake again to execute the job. The latter enables advanced Snakemake features like scripts, benchmarks and remote files to work inside CWL. So, when exporting keep in mind that the resulting CWL file can become huge, depending on the number of jobs in your workflow. To export a Snakemake workflow to CWL, simply run .. code-block:: console $ snakemake --export-cwl workflow.cwl The resulting workflow will by default use the `Snakemake docker image `_ for every step, but this behavior can be overwritten via the CWL execution environment. Then, the workflow can be executed in the same working directory with, e.g., .. code-block:: console $ cwltool workflow.cwl Note that due to limitations in CWL, it seems currently impossible to avoid that all target files (output files of target jobs), are written directly to the workdir, regardless of their relative paths in the Snakefile. 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You can use one of the following ways for installing Snakemake. .. _conda-install: Installation via Conda ====================== This is the **recommended** way to install Snakemake, because it also enables Snakemake to :ref:`handle software dependencies of your workflow `. First, you have to install the Miniconda Python3 distribution. See `here `_ for installation instructions. Make sure to ... * Install the **Python 3** version of Miniconda. * Answer yes to the question whether conda shall be put into your PATH. Then, you can install Snakemake with .. code-block:: console $ conda install -c bioconda -c conda-forge snakemake from the `Bioconda `_ channel. Alternatively, Snakemake can be installed into an isolated software environment with .. code-block:: console $ conda create -c bioconda -c conda-forge -n snakemake snakemake The software environment has to be activated before using Snakemake: .. code-block:: console $ conda activate snakemake $ snakemake --help A minimal version of Snakemake which only depends on the bare necessities can be installed with .. code-block:: console $ conda install -c bioconda -c conda-forge snakemake-minimal Note that Snakemake is available via Bioconda for historical, reproducibility, and continuity reasons. However, it is easy to combine Snakemake installation with other channels, e.g., by prefixing the package name with ``::bioconda``, i.e., .. code-block:: console $ conda install -c conda-forge bioconda::snakemake bioconda::snakemake-minimal Global Installation =================== With a working Python ``>=3.5`` setup, installation of Snakemake can be performed by issuing .. code-block:: console $ easy_install3 snakemake or .. code-block:: console $ pip3 install snakemake in your terminal. Installing in Virtualenv ======================== To create an installation in a virtual environment, use the following commands: .. code-block:: console $ virtualenv -p python3 .venv $ source .venv/bin/activate $ pip install snakemake Installing from Source ====================== We recommend installing Snakemake into a virtualenv or a conda environment instead of globally. Use the following commands to create a virtualenv and install Snakemake. Note that this will install the development version and as you are installing from the source code, we trust that you know what you are doing and how to checkout individual versions/tags. .. code-block:: console $ git clone https://github.com/snakemake/snakemake.git $ cd snakemake $ virtualenv -p python3 .venv $ source .venv/bin/activate $ python setup.py install You can also use ``python setup.py develop`` to create a "development installation" in which no files are copied but a link is created and changes in the source code are immediately visible in your ``snakemake`` commands. snakemake-5.10.0/docs/index.rst000066400000000000000000000375361361131222100163330ustar00rootroot00000000000000.. _manual-main: ========= Snakemake ========= .. image:: https://img.shields.io/conda/dn/bioconda/snakemake.svg?label=Bioconda :target: https://bioconda.github.io/recipes/snakemake/README.html .. image:: https://img.shields.io/pypi/pyversions/snakemake.svg :target: https://www.python.org .. image:: https://img.shields.io/pypi/v/snakemake.svg :target: https://pypi.python.org/pypi/snakemake .. image:: https://img.shields.io/docker/cloud/build/snakemake/snakemake :target: https://hub.docker.com/r/snakemake/snakemake .. image:: https://github.com/snakemake/snakemake/workflows/CI/badge.svg?branch=master :target: https://github.com/snakemake/snakemake/actions?query=branch%3Amaster+workflow%3ACI .. image:: https://img.shields.io/badge/stack-overflow-orange.svg :target: https://stackoverflow.com/questions/tagged/snakemake .. image:: https://img.shields.io/twitter/follow/johanneskoester.svg?style=social&label=Follow :target: https://twitter.com/search?l=&q=%23snakemake%20from%3Ajohanneskoester .. image:: https://img.shields.io/github/stars/snakemake/snakemake?style=social :alt: GitHub stars :target: https://github.com/snakemake/snakemake/stargazers .. .. raw:: html The Snakemake workflow management system is a tool to create **reproducible and scalable** data analyses. Workflows are described via a human readable, Python based language. They can be seamlessly scaled to server, cluster, grid and cloud environments, without the need to modify the workflow definition. Finally, Snakemake workflows can entail a description of required software, which will be automatically deployed to any execution environment. Snakemake is **highly popular** with, `~3 new citations per week `_. .. _manual-quick_example: ------------- Quick Example ------------- Snakemake workflows are essentially Python scripts extended by declarative code to define **rules**. Rules describe how to create **output files** from **input files**. .. code-block:: python rule targets: input: "plots/myplot.pdf" rule transform: input: "raw/{dataset}.csv" output: "transformed/{dataset}.csv" singularity: "docker://somecontainer:v1.0" shell: "somecommand {input} {output}" rule aggregate_and_plot: input: expand("transformed/{dataset}.csv", dataset=[1, 2]) output: "plots/myplot.pdf" conda: "envs/matplotlib.yaml" script: "scripts/plot.py" * Similar to GNU Make, you specify targets in terms of a pseudo-rule at the top. * For each target and intermediate file, you create rules that define how they are created from input files. * Snakemake determines the rule dependencies by matching file names. * Input and output files can contain multiple named wildcards. * Rules can either use shell commands, plain Python code or external Python or R scripts to create output files from input files. * Snakemake workflows can be easily executed on **workstations**, **clusters**, **the grid**, and **in the cloud** without modification. The job scheduling can be constrained by arbitrary resources like e.g. available CPU cores, memory or GPUs. * Snakemake can automatically deploy required software dependencies of a workflow using `Conda `_ or `Singularity `_. * Snakemake can use Amazon S3, Google Storage, Dropbox, FTP, WebDAV, SFTP and iRODS to access input or output files and further access input files via HTTP and HTTPS. .. _main-getting-started: --------------- Getting started --------------- To get a first impression, see our `introductory slides `_ or watch the `live demo video `_. News about Snakemake are published via `Twitter `_. To learn Snakemake, please do the :ref:`tutorial`, and see the :ref:`FAQ `. .. _main-support: ------- Support ------- * For releases, see :ref:`Changelog `. * Check :ref:`frequently asked questions (FAQ) `. * In case of questions, please post on `stack overflow `_. * To discuss with other Snakemake users, you can use the `mailing list `_. **Please do not post questions there. Use stack overflow for questions.** * For bugs and feature requests, please use the `issue tracker `_. * For contributions, visit Snakemake on `Github `_ and read the :ref:`guidelines `. -------- Citation -------- `Köster, Johannes and Rahmann, Sven. "Snakemake - A scalable bioinformatics workflow engine". Bioinformatics 2012. `_ See :doc:`Citations ` for more information. --------- Resources --------- `Snakemake Wrappers Repository `_ The Snakemake Wrapper Repository is a collection of reusable wrappers that allow to quickly use popular tools from Snakemake rules and workflows. `Snakemake Workflows Project `_ This project provides a collection of high quality modularized and re-usable workflows. The provided code should also serve as a best-practices of how to build production ready workflows with Snakemake. Everybody is invited to contribute. `Snakemake Profiles Project `_ This project provides Snakemake configuration profiles for various execution environments. Please consider contributing your own if it is still missing. `Bioconda `_ Bioconda can be used from Snakemake for creating completely reproducible workflows by defining the used software versions and providing binaries. .. project_info-publications_using: ---------------------------- Publications using Snakemake ---------------------------- In the following you find an **incomplete list** of publications making use of Snakemake for their analyses. Please consider to add your own. * Kuzniar et al. 2020. `sv-callers: a highly portable parallel workflow for structural variant detection in whole-genome sequence data `_. PeerJ. * Doris et al. 2018. `Spt6 is required for the fidelity of promoter selection `_. Molecular Cell. * Karlsson et al. 2018. `Four evolutionary trajectories underlie genetic intratumoral variation in childhood cancer `_. Nature Genetics. * Planchard et al. 2018. `The translational landscape of Arabidopsis mitochondria `_. Nucleic acids research. * Schult et al. 2018. `Effect of UV irradiation on Sulfolobus acidocaldarius and involvement of the general transcription factor TFB3 in the early UV response `_. Nucleic acids research. * Goormaghtigh et al. 2018. `Reassessing the Role of Type II Toxin-Antitoxin Systems in Formation of Escherichia coli Type II Persister Cells `_. mBio. * Ramirez et al. 2018. `Detecting macroecological patterns in bacterial communities across independent studies of global soils `_. Nature microbiology. * Amato et al. 2018. `Evolutionary trends in host physiology outweigh dietary niche in structuring primate gut microbiomes `_. The ISME journal. * Uhlitz et al. 2017. `An immediate–late gene expression module decodes ERK signal duration `_. Molecular Systems Biology. * Akkouche et al. 2017. `Piwi Is Required during Drosophila Embryogenesis to License Dual-Strand piRNA Clusters for Transposon Repression in Adult Ovaries `_. Molecular Cell. * Beatty et al. 2017. `Giardia duodenalis induces pathogenic dysbiosis of human intestinal microbiota biofilms `_. International Journal for Parasitology. * Meyer et al. 2017. `Differential Gene Expression in the Human Brain Is Associated with Conserved, but Not Accelerated, Noncoding Sequences `_. Molecular Biology and Evolution. * Lonardo et al. 2017. `Priming of soil organic matter: Chemical structure of added compounds is more important than the energy content `_. Soil Biology and Biochemistry. * Beisser et al. 2017. `Comprehensive transcriptome analysis provides new insights into nutritional strategies and phylogenetic relationships of chrysophytes `_. PeerJ. * Piro et al 2017. `MetaMeta: integrating metagenome analysis tools to improve taxonomic profiling `_. Microbiome. * Dimitrov et al 2017. `Successive DNA extractions improve characterization of soil microbial communities `_. PeerJ. * de Bourcy et al. 2016. `Phylogenetic analysis of the human antibody repertoire reveals quantitative signatures of immune senescence and aging `_. PNAS. * Bray et al. 2016. `Near-optimal probabilistic RNA-seq quantification `_. Nature Biotechnology. * Etournay et al. 2016. `TissueMiner: a multiscale analysis toolkit to quantify how cellular processes create tissue dynamics `_. eLife Sciences. * Townsend et al. 2016. `The Public Repository of Xenografts Enables Discovery and Randomized Phase II-like Trials in Mice `_. Cancer Cell. * Burrows et al. 2016. `Genetic Variation, Not Cell Type of Origin, Underlies the Majority of Identifiable Regulatory Differences in iPSCs `_. PLOS Genetics. * Ziller et al. 2015. `Coverage recommendations for methylation analysis by whole-genome bisulfite sequencing `_. Nature Methods. * Li et al. 2015. `Quality control, modeling, and visualization of CRISPR screens with MAGeCK-VISPR `_. Genome Biology. * Schmied et al. 2015. `An automated workflow for parallel processing of large multiview SPIM recordings `_. Bioinformatics. * Chung et al. 2015. `Whole-Genome Sequencing and Integrative Genomic Analysis Approach on Two 22q11.2 Deletion Syndrome Family Trios for Genotype to Phenotype Correlations `_. Human Mutation. * Kim et al. 2015. `TUT7 controls the fate of precursor microRNAs by using three different uridylation mechanisms `_. The EMBO Journal. * Park et al. 2015. `Ebola Virus Epidemiology, Transmission, and Evolution during Seven Months in Sierra Leone `_. Cell. * Břinda et al. 2015. `RNF: a general framework to evaluate NGS read mappers `_. Bioinformatics. * Břinda et al. 2015. `Spaced seeds improve k-mer-based metagenomic classification `_. Bioinformatics. * Spjuth et al. 2015. `Experiences with workflows for automating data-intensive bioinformatics `_. Biology Direct. * Schramm et al. 2015. `Mutational dynamics between primary and relapse neuroblastomas `_. Nature Genetics. * Berulava et al. 2015. `N6-Adenosine Methylation in MiRNAs `_. PLOS ONE. * The Genome of the Netherlands Consortium 2014. `Whole-genome sequence variation, population structure and demographic history of the Dutch population `_. Nature Genetics. * Patterson et al. 2014. `WhatsHap: Haplotype Assembly for Future-Generation Sequencing Reads `_. Journal of Computational Biology. * Fernández et al. 2014. `H3K4me1 marks DNA regions hypomethylated during aging in human stem and differentiated cells `_. Genome Research. * Köster et al. 2014. `Massively parallel read mapping on GPUs with the q-group index and PEANUT `_. PeerJ. * Chang et al. 2014. `TAIL-seq: Genome-wide Determination of Poly(A) Tail Length and 3′ End Modifications `_. Molecular Cell. * Althoff et al. 2013. `MiR-137 functions as a tumor suppressor in neuroblastoma by downregulating KDM1A `_. International Journal of Cancer. * Marschall et al. 2013. `MATE-CLEVER: Mendelian-Inheritance-Aware Discovery and Genotyping of Midsize and Long Indels `_. Bioinformatics. * Rahmann et al. 2013. `Identifying transcriptional miRNA biomarkers by integrating high-throughput sequencing and real-time PCR data `_. Methods. * Martin et al. 2013. `Exome sequencing identifies recurrent somatic mutations in EIF1AX and SF3B1 in uveal melanoma with disomy 3 `_. Nature Genetics. * Czeschik et al. 2013. `Clinical and mutation data in 12 patients with the clinical diagnosis of Nager syndrome `_. Human Genetics. * Marschall et al. 2012. `CLEVER: Clique-Enumerating Variant Finder `_. Bioinformatics. .. toctree:: :caption: Getting started :name: getting_started :hidden: :maxdepth: 1 getting_started/installation tutorial/tutorial tutorial/short .. toctree:: :caption: Executing workflows :name: execution :hidden: :maxdepth: 1 executing/cli executing/cluster-cloud executing/caching executing/interoperability .. toctree:: :caption: Defining workflows :name: snakefiles :hidden: :maxdepth: 1 snakefiles/writing_snakefiles snakefiles/rules snakefiles/configuration snakefiles/modularization snakefiles/remote_files snakefiles/utils snakefiles/deployment snakefiles/reporting .. toctree:: :caption: API Reference :name: api-reference :hidden: :maxdepth: 1 api_reference/snakemake api_reference/snakemake_utils api_reference/internal/modules .. toctree:: :caption: Project Info :name: project-info :hidden: :maxdepth: 1 project_info/citations project_info/more_resources project_info/faq project_info/contributing project_info/authors project_info/history project_info/license snakemake-5.10.0/docs/project_info/000077500000000000000000000000001361131222100171355ustar00rootroot00000000000000snakemake-5.10.0/docs/project_info/authors.rst000066400000000000000000000015201361131222100213520ustar00rootroot00000000000000.. project_info-authors: ======= Credits ======= Development Lead ---------------- - Johannes Köster Development Team ---------------- - Christopher Tomkins-Tinch - David Koppstein - Tim Booth - Manuel Holtgrewe - Christian Arnold - Wibowo Arindrarto - Rasmus Ågren - Soohyun Lee Contributors ------------ In alphabetical order - Andreas Wilm - Anthony Underwood - Ryan Dale - David Alexander - Elias Kuthe - Elmar Pruesse - Hyeshik Chang - Jay Hesselberth - Jesper Foldager - John Huddleston - Joona Lehtomäki - Karel Brinda - Karl Gutwin - Kemal Eren - Kostis Anagnostopoulos - Kyle A. Beauchamp - Kyle Meyer - Lance Parsons - Manuel Holtgrewe - Marcel Martin - Matthew Shirley - Mattias Franberg - Matt Shirley - Paul Moore - Per Unneberg - Ryan C. Thompson - Ryan Dale - Sean Davis - Simon Ye - Tobias Marschall - Willem Ligtenberg snakemake-5.10.0/docs/project_info/citations.rst000066400000000000000000000032171361131222100216670ustar00rootroot00000000000000.. _project_info-citations: ==================== Citing and Citations ==================== This section gives instructions on how to cite Snakemake and lists citing articles. .. project_info-citing_snakemake: ---------------- Citing Snakemake ---------------- When using Snakemake for a publication, **please cite the following article** in you paper: Cite This ========= `Köster, Johannes and Rahmann, Sven. "Snakemake - A scalable bioinformatics workflow engine". Bioinformatics 2012. `_ More References =============== Another publication describing more of Snakemake internals: `Köster, Johannes and Rahmann, Sven. "Building and Documenting Bioinformatics Workflows with Python-based Snakemake". Proceedings of the GCB 2012. `_ And my PhD thesis which describes all algorithmic details: `Johannes Köster, "Parallelization, Scalability, and Reproducibility in Next-Generation Sequencing Analysis", TU Dortmund 2014 `_ Project Pages ============= If you publish a Snakemake workflow, consider to add this badge to your project page: .. image:: https://img.shields.io/badge/snakemake-≥5.6.0-brightgreen.svg?style=flat :target: https://snakemake.readthedocs.io The markdown syntax is .. sourcecode:: text [![Snakemake](https://img.shields.io/badge/snakemake-≥5.6.0-brightgreen.svg?style=flat)](https://snakemake.readthedocs.io) Replace the ``3.5.2`` with the minimum required Snakemake version. You can also `change the style `_. snakemake-5.10.0/docs/project_info/contributing.rst000066400000000000000000000245471361131222100224120ustar00rootroot00000000000000.. _project_info-contributing: ============ Contributing ============ Contributions are welcome, and they are greatly appreciated! Every little bit helps, and credit will always be given. You can contribute in many ways: ---------------------- Types of Contributions ---------------------- Report Bugs =========== Report bugs at https://github.com/snakemake/snakemake/issues If you are reporting a bug, please include: * Your operating system name and version. * Any details about your local setup that might be helpful in troubleshooting. * Detailed steps to reproduce the bug. Fix Bugs ======== Look through the Github issues for bugs. If you want to start working on a bug then please write short message on the issue tracker to prevent duplicate work. Implement Features ================== Look through the Github issues for features. If you want to start working on an issue then please write short message on the issue tracker to prevent duplicate work. Contributing a new cluster or cloud execution backend ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ Execution backends are added by implementing a so-called ``Executor``. All executors are located in `snakemake/executors.py `_. In order to implement a new executor, you have to inherit from the class ``ClusterExecutor``. Below you find a skeleton .. code-block:: python class SkeletonExecutor(ClusterExecutor): def __init__(self, workflow, dag, cores, jobname="snakejob.{name}.{jobid}.sh", printreason=False, quiet=False, printshellcmds=False, latency_wait=3, cluster_config=None, local_input=None, restart_times=None, exec_job=None, assume_shared_fs=True, max_status_checks_per_second=1): # overwrite the command to execute a single snakemake job if necessary # exec_job = "..." super().__init__(workflow, dag, None, jobname=jobname, printreason=printreason, quiet=quiet, printshellcmds=printshellcmds, latency_wait=latency_wait, cluster_config=cluster_config, local_input=local_input, restart_times=restart_times, exec_job=exec_job, assume_shared_fs=False, max_status_checks_per_second=10) # add additional attributes def shutdown(self): # perform additional steps on shutdown if necessary super().shutdown() def cancel(self): for job in self.active_jobs: # cancel active jobs here self.shutdown() def run(self, job, callback=None, submit_callback=None, error_callback=None): import kubernetes.client super()._run(job) # obtain job execution command exec_job = self.format_job( self.exec_job, job, _quote_all=True, use_threads="--force-use-threads" if not job.is_group() else "") # submit job here, and obtain job ids from the backend # register job as active, using your own namedtuple. # The namedtuple must at least contain the attributes # job, jobid, callback, error_callback. self.active_jobs.append(MyJob( job, jobid, callback, error_callback)) def _wait_for_jobs(self): # busy wait on job completion # This is only needed if your backend does not allow to use callbacks # for obtaining job status. while True: # always use self.lock to avoid race conditions with self.lock: if not self.wait: return active_jobs = self.active_jobs self.active_jobs = list() still_running = list() for j in active_jobs: # use self.status_rate_limiter to avoid too many API calls. with self.status_rate_limiter: # Retrieve status of job j from your backend via j.jobid # Handle completion and errors, calling either j.callback(j.job) # or j.error_callback(j.job) # In case of error, add job j to still_running. with self.lock: self.active_jobs.extend(still_running) sleep() Write Documentation =================== Snakemake could always use more documentation, whether as part of the official vcfpy docs, in docstrings, or even on the web in blog posts, articles, and such. Snakemake uses `Sphinx `_ for the user manual (that you are currently reading). See `project_info-doc_guidelines` on how the documentation reStructuredText is used. Submit Feedback =============== The best way to send feedback is to file an issue at https://github.com/snakemake/snakemake/issues If you are proposing a feature: * Explain in detail how it would work. * Keep the scope as narrow as possible, to make it easier to implement. * Remember that this is a volunteer-driven project, and that contributions are welcome :) ----------------------- Pull Request Guidelines ----------------------- To update the documentation, fix bugs or add new features you need to create a Pull Request . A PR is a change you make to your local copy of the code for us to review and potentially integrate into the code base. To create a Pull Request you need to do these steps: 1. Create a Github account. 2. Fork the repository. 3. Clone your fork locally. 4. Go to the created snakemake folder with :code:`cd snakemake`. 5. Create a new branch with :code:`git checkout -b `. 6. Make your changes to the code or documentation. 7. Run :code:`git add .` to add all the changed files to the commit (to see what files will be added you can run :code:`git add . --dry-run`). 8. To commit the added files use :code:`git commit`. (This will open a command line editor to write a commit message. These should have a descriptive 80 line header, followed by an empty line, and then a description of what you did and why. To use your command line text editor of choice use (for example) :code:`export GIT_EDITOR=vim` before running :code:`git commit`). 9. Now you can push your changes to your Github copy of Snakemake by running :code:`git push origin `. 10. If you now go to the webpage for your Github copy of Snakemake you should see a link in the sidebar called "Create Pull Request". 11. Now you need to choose your PR from the menu and click the "Create pull request" button. Be sure to change the pull request target branch to ! If you want to create more pull requests, first run :code:`git checkout master` and then start at step 5. with a new branch name. Feel free to ask questions about this if you want to contribute to Snakemake :) ------------------ Testing Guidelines ------------------ To ensure that you do not introduce bugs into Snakemake, you should test your code thouroughly. To have integration tests run automatically when commiting code changes to Github, you need to sign up on wercker.com and register a user. The easiest way to run your development version of Snakemake is perhaps to go to the folder containing your local copy of Snakemake and call: .. code-block:: console $ conda env create -f environment.yml -n snakemake-testing $ conda activate snakemake-testing $ pip install -e . This will make your development version of Snakemake the one called when running snakemake. You do not need to run this command after each time you make code changes. From the base snakemake folder you call :code:`nosetests` to run all the tests, or choose one specific test. For this to work, Nose (the testing framework we use) can be installed to the conda environment using pip: .. code-block:: console $ pip install nose $ nosetests $ nosetests tests.tests:test_log_input If you introduce a new feature you should add a new test to the tests directory. See the folder for examples. .. project_info-doc_guidelines: ------------------------ Documentation Guidelines ------------------------ For the documentation, please adhere to the following guidelines: - Put each sentence on its own line, this makes tracking changes through Git SCM easier. - Provide hyperlink targets, at least for the first two section levels. For this, use the format ``-``, e.g., ``project_info-doc_guidelines``. - Use the section structure from below. :: .. document_part-heading_1: ========= Heading 1 ========= .. document_part-heading_2: --------- Heading 2 --------- .. document_part-heading_3: Heading 3 ========= .. document_part-heading_4: Heading 4 --------- .. document_part-heading_5: Heading 5 ~~~~~~~~~ .. document_part-heading_6: Heading 6 ::::::::: .. _doc_setup: ------------------- Documentation Setup ------------------- For building the documentation, you have to install the Sphinx. If you have already installed Conda, all you need to do is to create a Snakemake development environment via .. code-block:: console $ git clone git@github.com:snakemake/snakemake.git $ cd snakemake $ conda env create -f environment.yml -n snakemake Then, the docs can be built with .. code-block:: console $ source activate snakemake $ cd docs $ make html $ make clean && make html # force rebuild Alternatively, you can use virtualenv. The following assumes you have a working Python 3 setup. .. code-block:: console $ git clone git@github.org:snakemake/snakemake.git $ cd snakemake/docs $ virtualenv -p python3 .venv $ source .venv/bin/activate $ pip install --upgrade -r requirements.txt Afterwards, the docs can be built with .. code-block:: console $ source .venv/bin/activate $ make html # rebuild for changed files only $ make clean && make html # force rebuild snakemake-5.10.0/docs/project_info/faq.rst000066400000000000000000000704711361131222100204470ustar00rootroot00000000000000.. _project_info-faq: ========================== Frequently Asked Questions ========================== .. contents:: What is the key idea of Snakemake workflows? -------------------------------------------- The key idea is very similar to GNU Make. The workflow is determined automatically from top (the files you want) to bottom (the files you have), by applying very general rules with wildcards you give to Snakemake: .. image:: img/idea.png :alt: Snakemake idea When you start using Snakemake, please make sure to walk through the :ref:`official tutorial `. It is crucial to understand how to properly use the system. My shell command fails with with errors about an "unbound variable", what's wrong? ---------------------------------------------------------------------------------- This happens often when calling virtual environments from within Snakemake. Snakemake is using `bash strict mode `_, to ensure e.g. proper error behavior of shell scripts. Unfortunately, virtualenv and some other tools violate bash strict mode. The quick fix for virtualenv is to temporarily deactivate the check for unbound variables .. code-block:: bash set +u; source /path/to/venv/bin/activate; set -u For more details on bash strict mode, see the `here `_. My shell command fails with exit code != 0 from within a pipe, what's wrong? ---------------------------------------------------------------------------- Snakemake is using `bash strict mode `_ to ensure best practice error reporting in shell commands. This entails the pipefail option, which reports errors from within a pipe to outside. If you don't want this, e.g., to handle empty output in the pipe, you can disable pipefail via prepending .. code-block:: bash set +o pipefail; to your shell command in the problematic rule. I don't want Snakemake to detect an error if my shell command exits with an exitcode > 1. What can I do? --------------------------------------------------------------------------------------------------------- Sometimes, tools encode information in exit codes bigger than 1. Snakemake by default treats anything > 0 as an error. Special cases have to be added by yourself. For example, you can write .. code-block:: python shell: """ set +e somecommand ... exitcode=$? if [ $exitcode -eq 1 ] then exit 1 else exit 0 fi """ This way, Snakemake only treats exit code 1 as an error, and thinks that everything else is fine. Note that such tools are an excellent use case for contributing a `wrapper `_. .. _glob-wildcards: How do I run my rule on all files of a certain directory? --------------------------------------------------------- In Snakemake, similar to GNU Make, the workflow is determined from the top, i.e. from the target files. Imagine you have a directory with files ``1.fastq, 2.fastq, 3.fastq, ...``, and you want to produce files ``1.bam, 2.bam, 3.bam, ...`` you should specify these as target files, using the ids ``1,2,3,...``. You could end up with at least two rules like this (or any number of intermediate steps): .. code-block:: python IDS = "1 2 3 ...".split() # the list of desired ids # a pseudo-rule that collects the target files rule all: input: expand("otherdir/{id}.bam", id=IDS) # a general rule using wildcards that does the work rule: input: "thedir/{id}.fastq" output: "otherdir/{id}.bam" shell: "..." Snakemake will then go down the line and determine which files it needs from your initial directory. In order to infer the IDs from present files, Snakemake provides the ``glob_wildcards`` function, e.g. .. code-block:: python IDS, = glob_wildcards("thedir/{id}.fastq") The function matches the given pattern against the files present in the filesystem and thereby infers the values for all wildcards in the pattern. A named tuple that contains a list of values for each wildcard is returned. Here, this named tuple has only one item, that is the list of values for the wildcard ``{id}``. I don't want expand to use the product of every wildcard, what can I do? ------------------------------------------------------------------------ By default the expand function uses ``itertools.product`` to create every combination of the supplied wildcards. Expand takes an optional, second positional argument which can customize how wildcards are combined. To create the list ``["a_1.txt", "b_2.txt", "c_3.txt"]``, invoke expand as: ``expand("{sample}_{id}.txt", zip, sample=["a", "b", "c"], id=["1", "2", "3"])`` I don't want expand to use every wildcard, what can I do? --------------------------------------------------------- Sometimes partially expanding wildcards is useful to define inputs which still depend on some wildcards. Expand takes an optional keyword argument, allow_missing=True, that will format only wildcards which are supplied, leaving others as is. To create the list ``["{sample}_1.txt", "{sample}_2.txt"]``, invoke expand as: ``expand("{sample}_{id}.txt", id=["1", "2"], allow_missing=True)`` If the filename contains the wildcard ``allow_missing``, it will be formatted normally: ``expand("{allow_missing}.txt", allow_missing=True)`` returns ``["True.txt"]``. Snakemake complains about a cyclic dependency or a PeriodicWildcardError. What can I do? ---------------------------------------------------------------------------------------- One limitation of Snakemake is that graphs of jobs have to be acyclic (similar to GNU Make). This means, that no path in the graph may be a cycle. Although you might have considered this when designing your workflow, Snakemake sometimes runs into situations where a cyclic dependency cannot be avoided without further information, although the solution seems obvious for the developer. Consider the following example: .. code-block:: text rule all: input: "a" rule unzip: input: "{sample}.tar.gz" output: "{sample}" shell: "tar -xf {input}" If this workflow is executed with .. code-block:: console snakemake -n two things may happen. 1. If the file ``a.tar.gz`` is present in the filesystem, Snakemake will propose the following (expected and correct) plan: .. code-block:: text rule a: input: a.tar.gz output: a wildcards: sample=a localrule all: input: a Job counts: count jobs 1 a 1 all 2 2. If the file ``a.tar.gz`` is not present and cannot be created by any other rule than rule ``a``, Snakemake will try to run rule ``a`` again, with ``{sample}=a.tar.gz``. This would infinitely go on recursively. Snakemake detects this case and produces a ``PeriodicWildcardError``. In summary, ``PeriodicWildcardErrors`` hint to a problem where a rule or a set of rules can be applied to create its own input. If you are lucky, Snakemake can be smart and avoid the error by stopping the recursion if a file exists in the filesystem. Importantly, however, bugs upstream of that rule can manifest as ``PeriodicWildcardError``, although in reality just a file is missing or named differently. In such cases, it is best to restrict the wildcard of the output file(s), or follow the general rule of putting output files of different rules into unique subfolders of your working directory. This way, you can discover the true source of your error. Is it possible to pass variable values to the workflow via the command line? ---------------------------------------------------------------------------- Yes, this is possible. Have a look at :ref:`snakefiles_configuration`. Previously it was necessary to use environment variables like so: E.g. write .. code-block:: bash $ SAMPLES="1 2 3 4 5" snakemake and have in the Snakefile some Python code that reads this environment variable, i.e. .. code-block:: python SAMPLES = os.environ.get("SAMPLES", "10 20").split() I get a NameError with my shell command. Are braces unsupported? ---------------------------------------------------------------- You can use the entire Python `format minilanguage `_ in shell commands. Braces in shell commands that are not intended to insert variable values thus have to be escaped by doubling them: This: .. code-block:: python ... shell: "awk '{print $1}' {input}" becomes: .. code-block:: python ... shell: "awk '{{print $1}}' {input}" Here the double braces are escapes, i.e. there will remain single braces in the final command. In contrast, ``{input}`` is replaced with an input filename. In addition, if your shell command has literal backslashes, ``\\``, you must escape them with a backslash, ``\\\\``. For example: This: .. code-block:: python shell: """printf \">%s\"" {{input}}""" becomes: .. code-block:: python shell: """printf \\">%s\\"" {{input}}""" How do I incorporate files that do not follow a consistent naming scheme? ------------------------------------------------------------------------- The best solution is to have a dictionary that translates a sample id to the inconsistently named files and use a function (see :ref:`snakefiles-input_functions`) to provide an input file like this: .. code-block:: python FILENAME = dict(...) # map sample ids to the irregular filenames here rule: # use a function as input to delegate to the correct filename input: lambda wildcards: FILENAME[wildcards.sample] output: "somefolder/{sample}.csv" shell: ... How do I force Snakemake to rerun all jobs from the rule I just edited? ----------------------------------------------------------------------- This can be done by invoking Snakemake with the ``--forcerules`` or ``-R`` flag, followed by the rules that should be re-executed: .. code-block:: console $ snakemake -R somerule This will cause Snakemake to re-run all jobs of that rule and everything downstream (i.e. directly or indirectly depending on the rules output). How do I enable syntax highlighting in Vim for Snakefiles? ---------------------------------------------------------- A vim syntax highlighting definition for Snakemake is available `here `_. You can copy that file to ``$HOME/.vim/syntax`` directory and add .. code-block:: vim au BufNewFile,BufRead Snakefile set syntax=snakemake au BufNewFile,BufRead *.smk set syntax=snakemake to your ``$HOME/.vimrc`` file. Highlighting can be forced in a vim session with ``:set syntax=snakemake``. I want to import some helper functions from another python file. Is that possible? ---------------------------------------------------------------------------------- Yes, from version 2.4.8 on, Snakemake allows to import python modules (and also simple python files) from the same directory where the Snakefile resides. How can I run Snakemake on a cluster where its main process is not allowed to run on the head node? --------------------------------------------------------------------------------------------------- This can be achived by submitting the main Snakemake invocation as a job to the cluster. If it is not allowed to submit a job from a non-head cluster node, you can provide a submit command that goes back to the head node before submitting: .. code-block:: bash qsub -N PIPE -cwd -j yes python snakemake --cluster "ssh user@headnode_address 'qsub -N pipe_task -j yes -cwd -S /bin/sh ' " -j This hint was provided by Inti Pedroso. Can the output of a rule be a symlink? -------------------------------------- Yes. As of Snakemake 3.8, output files are removed before running a rule and then touched after the rule completes to ensure they are newer than the input. Symlinks are treated just the same as normal files in this regard, and Snakemake ensures that it only modifies the link and not the target when doing this. Here is an example where you want to merge N files together, but if N == 1 a symlink will do. This is easier than attempting to implement workflow logic that skips the step entirely. Note the **-r** flag, supported by modern versions of ln, is useful to achieve correct linking between files in subdirectories. .. code-block:: python rule merge_files: output: "{foo}/all_merged.txt" input: my_input_func # some function that yields 1 or more files to merge run: if len(input) > 1: shell("cat {input} | sort > {output}") else: shell("ln -sr {input} {output}") Do be careful with symlinks in combination with :ref:`tutorial_temp-and-protected-files`. When the original file is deleted, this can cause various errors once the symlink does not point to a valid file any more. If you get a message like ``Unable to set utime on symlink .... Your Python build does not support it.`` this means that Snakemake is unable to properly adjust the modification time of the symlink. In this case, a workaround is to add the shell command `touch -h {output}` to the end of the rule. Can the input of a rule be a symlink? ------------------------------------- Yes. In this case, since Snakemake 3.8, one extra consideration is applied. If *either* the link itself or the target of the link is newer than the output files for the rule then it will trigger the rule to be re-run. I would like to receive a mail upon snakemake exit. How can this be achieved? ----------------------------------------------------------------------------- On unix, you can make use of the commonly pre-installed `mail` command: .. code-block:: bash snakemake 2> snakemake.log mail -s "snakemake finished" youremail@provider.com < snakemake.log In case your administrator does not provide you with a proper configuration of the sendmail framework, you can configure `mail` to work e.g. via Gmail (see `here `_). I want to pass variables between rules. Is that possible? --------------------------------------------------------- Because of the cluster support and the ability to resume a workflow where you stopped last time, Snakemake in general should be used in a way that information is stored in the output files of your jobs. Sometimes it might though be handy to have a kind of persistent storage for simple values between jobs and rules. Using plain python objects like a global dict for this will not work as each job is run in a separate process by snakemake. What helps here is the `PersistentDict` from the `pytools `_ package. Here is an example of a Snakemake workflow using this facility: .. code-block:: python from pytools.persistent_dict import PersistentDict storage = PersistentDict("mystorage") rule a: input: "test.in" output: "test.out" run: myvar = storage.fetch("myvar") # do stuff rule b: output: temp("test.in") run: storage.store("myvar", 3.14) Here, the output rule b has to be temp in order to ensure that ``myvar`` is stored in each run of the workflow as rule a relies on it. In other words, the PersistentDict is persistent between the job processes, but not between different runs of this workflow. If you need to conserve information between different runs, use output files for them. Why do my global variables behave strangely when I run my job on a cluster? --------------------------------------------------------------------------- This is closely related to the question above. Any Python code you put outside of a rule definition is normally run once before Snakemake starts to process rules, but on a cluster it is re-run again for each submitted job, because Snakemake implements jobs by re-running itself. Consider the following... .. code-block:: python from mydatabase import get_connection dbh = get_connection() latest_parameters = dbh.get_params().latest() rule a: input: "{foo}.in" output: "{foo}.out" shell: "do_op -params {latest_parameters} {input} {output}" When run a single machine, you will see a single connection to your database and get a single value for *latest_parameters* for the duration of the run. On a cluster you will see a connection attempt from the cluster node for each job submitted, regardless of whether it happens to involve rule a or not, and the parameters will be recalculated for each job. I want to configure the behavior of my shell for all rules. How can that be achieved with Snakemake? ---------------------------------------------------------------------------------------------------- You can set a prefix that will prepended to all shell commands by adding e.g. .. code-block:: python shell.prefix("set -o pipefail; ") to the top of your Snakefile. Make sure that the prefix ends with a semicolon, such that it will not interfere with the subsequent commands. To simulate a bash login shell, you can do the following: .. code-block:: python shell.executable("/bin/bash") shell.prefix("source ~/.bashrc; ") Some command line arguments like --config cannot be followed by rule or file targets. Is that intended behavior? ---------------------------------------------------------------------------------------------------------------- This is a limitation of the argparse module, which cannot distinguish between the perhaps next arg of ``--config`` and a target. As a solution, you can put the `--config` at the end of your invocation, or prepend the target with a single ``--``, i.e. .. code-block:: console $ snakemake --config foo=bar -- mytarget $ snakemake mytarget --config foo=bar How do I enforce config values given at the command line to be interpreted as strings? -------------------------------------------------------------------------------------- When passing config values like this .. code-block:: console $ snakemake --config version=2018_1 Snakemake will first try to interpret the given value as number. Only if that fails, it will interpret the value as string. Here, it does not fail, because the underscore `_` is interpreted as thousand separator. In order to ensure that the value is interpreted as string, you have to pass it in quotes. Since bash otherwise automatically removes quotes, you have to also wrap the entire entry into quotes, e.g.: .. code-block:: console $ snakemake --config 'version="2018_1"' How do I make my rule fail if an output file is empty? ------------------------------------------------------ Snakemake expects shell commands to behave properly, meaning that failures should cause an exit status other than zero. If a command does not exit with a status other than zero, Snakemake assumes everything worked fine, even if output files are empty. This is because empty output files are also a reasonable tool to indicate progress where no real output was produced. However, sometimes you will have to deal with tools that do not properly report their failure with an exit status. Here, the recommended way is to use bash to check for non-empty output files, e.g.: .. code-block:: python rule: input: ... output: "my/output/file.txt" shell: "somecommand {input} {output} && [[ -s {output} ]]" How does Snakemake lock the working directory? ---------------------------------------------- Per default, Snakemake will lock a working directory by output and input files. Two Snakemake instances that want to create the same output file are not possible. Two instances creating disjoint sets of output files are possible. With the command line option ``--nolock``, you can disable this mechanism on your own risk. With ``--unlock``, you can be remove a stale lock. Stale locks can appear if your machine is powered off with a running Snakemake instance. Snakemake does not trigger re-runs if I add additional input files. What can I do? ---------------------------------------------------------------------------------- Snakemake has a kind of "lazy" policy about added input files if their modification date is older than that of the output files. One reason is that information what to do cannot be inferred just from the input and output files. You need additional information about the last run to be stored. Since behaviour would be inconsistent between cases where that information is available and where it is not, this functionality has been encoded as an extra switch. To trigger updates for jobs with changed input files, you can use the command line argument --list-input-changes in the following way: .. code-block:: console $ snakemake -n -R `snakemake --list-input-changes` Here, ``snakemake --list-input-changes`` returns the list of output files with changed input files, which is fed into ``-R`` to trigger a re-run. How do I trigger re-runs for rules with updated code or parameters? ------------------------------------------------------------------- Similar to the solution above, you can use .. code-block:: console $ snakemake -n -R `snakemake --list-params-changes` and .. code-block:: console $ snakemake -n -R `snakemake --list-code-changes` Again, the list commands in backticks return the list of output files with changes, which are fed into ``-R`` to trigger a re-run. How do I remove all files created by snakemake, i.e. like ``make clean`` ------------------------------------------------------------------------ To remove all files created by snakemake as output files to start from scratch, you can use .. code-block:: console $ snakemake some_target --delete-all-output Only files that are output of snakemake rules will be removed, not those that serve as primary inputs to the workflow. Note that this will only affect the files involved in reaching the specified target(s). It is strongly advised to first run together with ``--dry-run`` to list the files that would be removed without actually deleting anything. The flag ``--delete-temp-output`` can be used in a similar manner to only delete files flagged as temporary. Why can't I use the conda directive with a run block? ----------------------------------------------------- The run block of a rule (see :ref:`snakefiles-rules`) has access to anything defined in the Snakefile, outside of the rule. Hence, it has to share the conda environment with the main Snakemake process. To avoid confusion we therefore disallow the conda directive together with the run block. It is recommended to use the script directive instead (see :ref:`snakefiles-external_scripts`). My workflow is very large, how do I stop Snakemake from printing all this rule/job information in a dry-run? ------------------------------------------------------------------------------------------------------------ Indeed, the information for each individual job can slow down a dry-run if there are tens of thousands of jobs. If you are just interested in the final summary, you can use the ``--quiet`` flag to suppress this. .. code-block:: console $ snakemake -n --quiet Git is messing up the modification times of my input files, what can I do? -------------------------------------------------------------------------- When you checkout a git repository, the modification times of updated files are set to the time of the checkout. If you rely on these files as input **and** output files in your workflow, this can cause trouble. For example, Snakemake could think that a certain (git-tracked) output has to be re-executed, just because its input has been checked out a bit later. In such cases, it is advisable to set the file modification dates to the last commit date after an update has been pulled. See `here `_ for a solution to achieve this. How do I exit a running Snakemake workflow? ------------------------------------------- There are two ways to exit a currently running workflow. 1. If you want to kill all running jobs, hit Ctrl+C. Note that when using ``--cluster``, this will only cancel the main Snakemake process. 2. If you want to stop the scheduling of new jobs and wait for all running jobs to be finished, you can send a TERM signal, e.g., via .. code-block:: bash killall -TERM snakemake How can I make use of node-local storage when running cluster jobs? ------------------------------------------------------------------- When running jobs on a cluster you might want to make use of a node-local scratch directory in order to reduce cluster network traffic and/or get more efficient disk storage for temporary files. There is currently no way of doing this in Snakemake, but a possible workaround involves the ``shadow`` directive and setting the ``--shadow-prefix`` flag to e.g. ``/scratch``. .. code-block:: python rule: output: "some_summary_statistics.txt" shadow: "minimal" shell: """ generate huge_file.csv summarize huge_file.csv > {output} """ The following would then lead to the job being executed in ``/scratch/shadow/some_unique_hash/``, and the temporary file ``huge_file.csv`` could be kept at the compute node. .. code-block:: console $ snakemake --shadow-prefix /scratch some_summary_statistics.txt --cluster ... How do I access elements of input or output by a variable index? ---------------------------------------------------------------- Assuming you have something like the following rule .. code-block:: python rule a: output: expand("test.{i}.out", i=range(20)) run: for i in range(20): shell("echo test > {output[i]}") Snakemake will fail upon execution with the error ``'OutputFiles' object has no attribute 'i'``. The reason is that the shell command is using the `Python format mini language `_, which does only allow indexing via constants, e.g., ``output[1]``, but not via variables. Variables are treated as attribute names instead. The solution is to write .. code-block:: python rule a: output: expand("test.{i}.out", i=range(20)) run: for i in range(20): f = output[i] shell("echo test > {f}") or, more concise in this special case: .. code-block:: python rule a: output: expand("test.{i}.out", i=range(20)) run: for f in output: shell("echo test > {f}") There is a compiler error when installing Snakemake with pip or easy_install, what shall I do? ---------------------------------------------------------------------------------------------- Snakemake itself is plain Python, hence the compiler error must come from one of the dependencies, like e.g., datrie. You should have a look if maybe you are missing some library or a certain compiler package. If everything seems fine, please report to the upstream developers of the failing dependency. Note that in general it is recommended to install Snakemake via `Conda `_ which gives you precompiled packages and the additional benefit of having :ref:`automatic software deployment ` integrated into your workflow execution. How to enable autocompletion for the zsh shell? ----------------------------------------------- For users of the `Z shell `_ (zsh), just run the following (assuming an activated zsh) to activate autocompletion for snakemake: .. code-block:: console compdef _gnu_generic snakemake Example: Say you have forgotten how to use the various options starting ``force``, just type the partial match i.e. ``--force`` which results in a list of all potential hits along with a description: .. code-block:: console $snakemake --force**pressing tab** --force -- Force the execution of the selected target or the --force-use-threads -- Force threads rather than processes. Helpful if shared --forceall -- Force the execution of the selected (or the first) --forcerun -- (TARGET (TARGET ...)), -R (TARGET (TARGET ...)) 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ę..'aH,i ty@~+iFN׋t@1\W<> /i-`͊0"l^1^aP}]0 jK-~G[qgi+j mgf `mId"/e])pg<<1Z%B|`G`<8I6i xa1X$ie߿j渢PZ,3%~*;Xrf•>zH=@xtpv=JZiy$iZm$I7o.ڛWZ̮#I[τW{[h[ci1G%} 8]d =q]|rG\ͬs: I䕅1Mx-urz? _^XU JjI*aXe!3'Ѷ:Q<|`6};^UwbΔm̝A.o\י-II[Tbk?(f6^]x|&FIf$-h ђvHi+I 3#VG᪛@?6VAҶ#]/^y`؋q ! lJwO2 ?љZ``%Ieh,ħ\v+ ⲲJ}g]duEUw,qMrGfvʼ"IqS$~&t|T,wCw(^`3%I$@: IZ i8l~^mppSYƶՐ"=^ӺUǭѿS43/3vpe$I$%$INUp ﭙ[x"a\]m058^jmI$I{I$6y\Vxh~kMXxuG҆xb\TJ$i^I$YA$OF xfF {ף,“5-I$t@$IVIEI`{P . p( p~_%I$N: I$U++҄bx}k>^z$I&$IB@Yx{Uqݕ4~/#i|0`h~sKYn:I$i-I$:Q(`h^w}vi+.p7t4ƺ$I'I$I }UAk)0=~{D#pǣ`  *s;$IV?I$#"Dk`?`_ * `Invited talk by Johannes Köster at the Broad Institute, Boston 2015. `_ * `Introduction to Snakemake. Tutorial Slides presented by Johannes Köster at the GCB 2015, Dortmund, Germany. `_ * `Invited talk by Johannes Köster at the DTL Focus Meeting: "NGS Production Pipelines", Dutch Techcentre for Life Sciences, Utrecht 2014. `_ * `Taming Snakemake by Jeremy Leipzig, Bioinformatics software developer at Children's Hospital of Philadelphia, 2014. `_ * `"Snakemake makes ... snakes?" - An Introduction by Marcel Martin from SciLifeLab, Stockholm 2015 `_ * `"Workflow Management with Snakemake" by Johannes Köster, 2015. Held at the Department of Biostatistics and Computational Biology, Dana-Farber Cancer Institute `_ .. _project_info-external_resources: ------------------ External Resources ------------------ These resources are not part of the official documentation. * `A number of tutorials on the subject "Tools for reproducible research" `_ * `Snakemake workflow used for the Kallisto paper `_ * `An alternative tutorial for Snakemake `_ * `An Emacs mode for Snakemake `_ * `Flexible bioinformatics pipelines with Snakemake `_ * `Sandwiches with Snakemake `_ * `A visualization of the past years of Snakemake development `_ * `Japanese version of the Snakemake tutorial `_ * `Basic `_ and `advanced `_ french Snakemake tutorial. * `Mini tutorial on Snakemake and Bioconda `_ * `Snakeparse: a utility to expose Snakemake workflow configuation via a command line interface `_ snakemake-5.10.0/docs/requirements.txt000066400000000000000000000001621361131222100177370ustar00rootroot00000000000000sphinx sphinxcontrib-napoleon sphinx-argparse sphinx_rtd_theme docutils==0.12 recommonmark configargparse appdirs snakemake-5.10.0/docs/snakefiles/000077500000000000000000000000001361131222100166005ustar00rootroot00000000000000snakemake-5.10.0/docs/snakefiles/configuration.rst000066400000000000000000000214651361131222100222110ustar00rootroot00000000000000.. _snakefiles_configuration: ============= Configuration ============= Snakemake allows you to use configuration files for making your workflows more flexible and also for abstracting away direct dependencies to a fixed HPC cluster scheduler. .. _snakefiles_standard_configuration: ---------------------- Standard Configuration ---------------------- Snakemake directly supports the configuration of your workflow. A configuration is provided as a JSON or YAML file and can be loaded with: .. code-block:: python configfile: "path/to/config.json" The config file can be used to define a dictionary of configuration parameters and their values. In the workflow, the configuration is accessible via the global variable `config`, e.g. .. code-block:: python rule all: input: expand("{sample}.{param}.output.pdf", sample=config["samples"], param=config["yourparam"]) If the `configfile` statement is not used, the config variable provides an empty array. In addition to the `configfile` statement, config values can be overwritten via the command line or the :ref:`api_reference_snakemake`, e.g.: .. code-block:: console $ snakemake --config yourparam=1.5 Further, you can manually alter the config dictionary using any Python code **outside** of your rules. Changes made from within a rule won't be seen from other rules. Finally, you can use the `--configfile` command line argument to overwrite values from the `configfile` statement. Note that any values parsed into the `config` dictionary with any of above mechanisms are merged, i.e., all keys defined via a `configfile` statement, or the `--configfile` and `--config` command line arguments will end up in the final `config` dictionary, but if two methods define the same key, command line overwrites the `configfile` statement. For adding config placeholders into a shell command, Python string formatting syntax requires you to leave out the quotes around the key name, like so: .. code-block:: python shell: "mycommand {config[foo]} ..." --------------------- Tabular configuration --------------------- It is usually advisable to complement YAML based configuration (see above) by a sheet based approach for meta-data that is of tabular form. For example, such a sheet can contain per-sample information. With the `Pandas library `_ such data can be read and used with minimal overhead, e.g., .. code-block:: python import pandas as pd samples = pd.read_table("samples.tsv").set_index("samples", drop=False) reads in a table ``samples.tsv`` in TSV format and makes every record accessible by the sample name. For details, see the `Pandas documentation `_. A fully working real-world example containing both types of configuration can be found `here `_. ---------- Validation ---------- With Snakemake 5.1, it is possible to validate both types of configuration via `JSON schemas `_. The function ``snakemake.utils.validate`` takes a loaded configuration (a config dictionary or a Pandas data frame) and validates it with a given JSON schema. Thereby, the schema can be provided in JSON or YAML format. Also, by using the defaults property it is possible to populate entries with default values. See `jsonschema FAQ on setting default values `_ for details. In case of the data frame, the schema should model the record that is expected in each row of the data frame. In the following example, .. code-block:: python import pandas as pd from snakemake.utils import validate configfile: "config.yaml" validate(config, "config.schema.yaml") samples = pd.read_table(config["samples"]).set_index("sample", drop=False) validate(samples, "samples.schema.yaml") rule all: input: expand("test.{sample}.txt", sample=samples.index) rule a: output: "test.{sample}.txt" shell: "touch {output}" the schema for validating the samples data frame looks like this: .. code-block:: yaml $schema: "http://json-schema.org/draft-06/schema#" description: an entry in the sample sheet properties: sample: type: string description: sample name/identifier condition: type: string description: sample condition that will be compared during differential expression analysis (e.g. a treatment, a tissue time, a disease) case: type: boolean default: true description: boolean that indicates if sample is case or control required: - sample - condition Here, in case the case column is missing, the validate function will populate it with True for all entries. .. _snakefiles-cluster_configuration: ---------------------------------- Cluster Configuration (deprecated) ---------------------------------- While still being possible, **cluster configuration has been deprecated** by the introduction of :ref:`profiles`. Snakemake supports a separate configuration file for execution on a cluster. A cluster config file allows you to specify cluster submission parameters outside the Snakefile. The cluster config is a JSON- or YAML-formatted file that contains objects that match names of rules in the Snakefile. The parameters in the cluster config are then accessed by the ``cluster.*`` wildcard when you are submitting jobs. Note that a workflow shall never depend on a cluster configuration, because this would limit its portability. Therefore, it is also not intended to access the cluster configuration from **within** the workflow. For example, say that you have the following Snakefile: .. code-block:: python rule all: input: "input1.txt", "input2.txt" rule compute1: output: "input1.txt" shell: "touch input1.txt" rule compute2: output: "input2.txt" shell: "touch input2.txt" This Snakefile can then be configured by a corresponding cluster config, say "cluster.json": .. code-block:: json { "__default__" : { "account" : "my account", "time" : "00:15:00", "n" : 1, "partition" : "core" }, "compute1" : { "time" : "00:20:00" } } Any string in the cluster configuration can be formatted in the same way as shell commands, e.g. ``{rule}.{wildcards.sample}`` is formatted to ``a.xy`` if the rulename is ``a`` and the wildcard value is ``xy``. Here ``__default__`` is a special object that specifies default parameters, these will be inherited by the other configuration objects. The ``compute1`` object here changes the ``time`` parameter, but keeps the other parameters from ``__default__``. The rule ``compute2`` does not have any configuration, and will therefore use the default configuration. You can then run the Snakefile with the following command on a SLURM system. .. code-block:: console $ snakemake -j 999 --cluster-config cluster.json --cluster "sbatch -A {cluster.account} -p {cluster.partition} -n {cluster.n} -t {cluster.time}" For cluster systems using LSF/BSUB, a cluster config may look like this: .. code-block:: json { "__default__" : { "queue" : "medium_priority", "nCPUs" : "16", "memory" : 20000, "resources" : "\"select[mem>20000] rusage[mem=20000] span[hosts=1]\"", "name" : "JOBNAME.{rule}.{wildcards}", "output" : "logs/cluster/{rule}.{wildcards}.out", "error" : "logs/cluster/{rule}.{wildcards}.err" }, "trimming_PE" : { "memory" : 30000, "resources" : "\"select[mem>30000] rusage[mem=30000] span[hosts=1]\"", } } The advantage of this setup is that it is already pretty general by exploiting the wildcard possibilities that Snakemake provides via ``{rule}`` and ``{wildcards}``. So job names, output and error files all have reasonable and trackable default names, only the directies (``logs/cluster``) and job names (``JOBNAME``) have to adjusted accordingly. If a rule named ``bamCoverage`` is executed with the wildcard ``basename = sample1``, for example, the output and error files will be ``bamCoverage.basename=sample1.out`` and ``bamCoverage.basename=sample1.err``, respectively. --------------------------- Configure Working Directory --------------------------- All paths in the snakefile are interpreted relative to the directory snakemake is executed in. This behaviour can be overridden by specifying a workdir in the snakefile: .. code-block:: python workdir: "path/to/workdir" Usually, it is preferred to only set the working directory via the command line, because above directive limits the portability of Snakemake workflows. snakemake-5.10.0/docs/snakefiles/deployment.rst000066400000000000000000000247631361131222100215260ustar00rootroot00000000000000 ================================ Distribution and Reproducibility ================================ It is recommended to store each workflow in a dedicated git repository of the following structure: .. code-block:: none ├── .gitignore ├── README.md ├── LICENSE.md ├── workflow │ ├── scripts | │ ├── script1.py | │ └── script2.R │ ├── rules | │ ├── module1.smk | │ └── module2.smk │ ├── report | │ ├── plot1.smk | │ └── plot2.smk │ └── envs | │ ├── tool1.smk | │ └── tool2.smk ├── config │ ├── config.yaml │ └── some-sheet.tsv └── Snakefile Then, a workflow can be deployed to a new system via the following steps .. code-block:: python # clone workflow into working directory git clone https://github.com/user/myworkflow.git path/to/workdir cd path/to/workdir # edit config and workflow as needed vim config/config.yaml # execute workflow, deploy software dependencies via conda snakemake -n --use-conda Importantly, git branching and pull requests can be used to modify and possibly re-integrate workflows. A `cookiecutter `_ template for creating this structure can be found `here `_. Given that cookiecutter is installed, you can use it via: .. code-block:: bash cookiecutter gh:snakemake-workflows/cookiecutter-snakemake-workflow Visit the `Snakemake Workflows Project `_ for best-practice workflows. .. _integrated_package_management: ----------------------------- Integrated Package Management ----------------------------- With Snakemake 3.9.0 it is possible to define isolated software environments per rule. Upon execution of a workflow, the `Conda package manager `_ is used to obtain and deploy the defined software packages in the specified versions. Packages will be installed into your working directory, without requiring any admin/root priviledges. Given that conda is available on your system (see `Miniconda `_), to use the Conda integration, add the ``--use-conda`` flag to your workflow execution command, e.g. ``snakemake --cores 8 --use-conda``. When ``--use-conda`` is activated, Snakemake will automatically create software environments for any used wrapper (see :ref:`snakefiles-wrappers`). Further, you can manually define environments via the ``conda`` directive, e.g.: .. code-block:: python rule NAME: input: "table.txt" output: "plots/myplot.pdf" conda: "envs/ggplot.yaml" script: "scripts/plot-stuff.R" with the following `environment definition `_: .. code-block:: yaml channels: - r dependencies: - r=3.3.1 - r-ggplot2=2.1.0 The path to the environment definition is interpreted as **relative to the Snakefile that contains the rule** (unless it is an absolute path, which is discouraged). .. sidebar:: Note Note that conda environments are only used with ``shell``, ``script`` and the ``wrapper`` directive, not the ``run`` directive. The reason is that the ``run`` directive has access to the rest of the Snakefile (e.g. globally defined variables) and therefore must be executed in the same process as Snakemake itself. Snakemake will store the environment persistently in ``.snakemake/conda/$hash`` with ``$hash`` being the MD5 hash of the environment definition file content. This way, updates to the environment definition are automatically detected. Note that you need to clean up environments manually for now. However, in many cases they are lightweight and consist of symlinks to your central conda installation. Conda deployment also works well for offline or air-gapped environments. Running ``snakemake -n --use-conda --create-envs-only`` will only install the required conda environments without running the full workflow. Subsequent runs with ``--use-conda`` will make use of the local environments without requiring internet access. .. _singularity: -------------------------- Running jobs in containers -------------------------- As an alternative to using Conda (see above), it is possible to define, for each rule, a docker or singularity container to use, e.g., .. code-block:: python rule NAME: input: "table.txt" output: "plots/myplot.pdf" singularity: "docker://joseespinosa/docker-r-ggplot2" script: "scripts/plot-stuff.R" When executing Snakemake with .. code-block:: bash snakemake --use-singularity it will execute the job within a singularity container that is spawned from the given image. Allowed image urls entail everything supported by singularity (e.g., ``shub://`` and ``docker://``). .. sidebar:: Note Note that singularity integration is only used with ``shell``, ``script`` and the ``wrapper`` directive, not the ``run`` directive. The reason is that the ``run`` directive has access to the rest of the Snakefile (e.g. globally defined variables) and therefore must be executed in the same process as Snakemake itself. When ``--use-singularity`` is combined with ``--kubernetes`` (see :ref:`kubernetes`), cloud jobs will be automatically configured to run in priviledged mode, because this is a current requirement of the singularity executable. Importantly, those privileges won't be shared by the actual code that is executed in the singularity container though. -------------------------------------------------- Combining Conda package management with containers -------------------------------------------------- While :ref:`integrated_package_management` provides control over the used software in exactly the desired versions, it does not control the underlying operating system. Here, it becomes handy that Snakemake >=4.8.0 allows to combine Conda-based package management with :ref:`singularity`. For example, you can write .. code-block:: python singularity: "docker://continuumio/miniconda3:4.4.10" rule NAME: input: "table.txt" output: "plots/myplot.pdf" conda: "envs/ggplot.yaml" script: "scripts/plot-stuff.R" in other words, a global definition of a container image can be combined with a per-rule conda directive. Then, upon invocation with .. code-block:: bash snakemake --use-conda --use-singularity Snakemake will first pull the defined container image, and then create the requested conda environment from within the container. The conda environments will still be stored in your working environment, such that they don't have to be recreated unless they have changed. The hash under which the environments are stored includes the used container image url, such that changes to the container image also lead to new environments to be created. When a job is executed, Snakemake will first enter the container and then activate the conda environment. By this, both packages and OS can be easily controlled without the overhead of creating and distributing specialized container images. Of course, it is also possible (though less common) to define a container image per rule in this scenario. The user can, upon execution, freely choose the desired level of reproducibility: * no package management (use whatever is on the system) * Conda based package management (use versions defined by the workflow developer) * Conda based package management in containerized OS (use versions and OS defined by the workflow developer) ------------------------- Using environment modules ------------------------- In high performace cluster systems (HPC), it can be preferable to use environment modules for deployment of optimized versions of certain standard tools. Snakemake allows to define environment modules per rule: .. code-block:: python rule bwa: input: "genome.fa" "reads.fq" output: "mapped.bam" conda: "envs/bwa.yaml" envmodules: "bio/bwa/0.7.9", "bio/samtools/1.9" shell: "bwa mem {input} | samtools view -Sbh - > {output}" Here, when Snakemake is executed with `snakemake --use-envmodules`, it will load the defined modules in the given order, instead of using the also defined conda environment. Note that although not mandatory, one should always provide either a conda environment or a container (see above), along with environment module definitions. The reason is that environment modules are often highly platform specific, and cannot be assumed to be available somewhere else, thereby limiting reproducibility. By definition an equivalent conda environment or container as a fallback, people outside of the HPC system where the workflow has been designed can still execute it, e.g. by running `snakemake --use-conda` instead of `snakemake --use-envmodules`. -------------------------------------- Sustainable and reproducible archiving -------------------------------------- With Snakemake 3.10.0 it is possible to archive a workflow into a `tarball `_ (`.tar`, `.tar.gz`, `.tar.bz2`, `.tar.xz`), via .. code-block:: bash snakemake --archive my-workflow.tar.gz If above layout is followed, this will archive any code and config files that is under git version control. Further, all input files will be included into the archive. Finally, the software packages of each defined conda environment are included. This results in a self-contained workflow archive that can be re-executed on a vanilla machine that only has Conda and Snakemake installed via .. code-block:: bash tar -xf my-workflow.tar.gz snakemake -n Note that the archive is platform specific. For example, if created on Linux, it will run on any Linux newer than the minimum version that has been supported by the used Conda packages at the time of archiving (e.g. CentOS 6). A useful pattern when publishing data analyses is to create such an archive, upload it to `Zenodo `_ and thereby obtain a `DOI `_. Then, the DOI can be cited in manuscripts, and readers are able to download and reproduce the data analysis at any time in the future. snakemake-5.10.0/docs/snakefiles/modularization.rst000066400000000000000000000156511361131222100224030ustar00rootroot00000000000000.. snakefiles-modularization: .. _Snakemake Wrapper Repository: https://snakemake-wrappers.readthedocs.io ============== Modularization ============== Modularization in Snakemake comes at different levels. 1. The most fine-grained level are wrappers. They are available and can be published at the `Snakemake Wrapper Repository`_. These wrappers can then be composed and customized according to your needs, by copying skeleton rules into your workflow. In combination with conda integration, wrappers also automatically deploy the needed software dependencies into isolated environments. 2. For larger, reusable parts that shall be integrated into a common workflow, it is recommended to write small Snakefiles and include them into a master Snakefile via the include statement. In such a setup, all rules share a common config file. 3. The third level of separation are subworkflows. Importantly, these are rather meant as links between otherwise separate data analyses. .. _snakefiles-wrappers: -------- Wrappers -------- The wrapper directive allows to have re-usable wrapper scripts around e.g. command line tools. In contrast to modularization strategies like ``include`` or subworkflows, the wrapper directive allows to re-wire the DAG of jobs. For example .. code-block:: python rule samtools_sort: input: "mapped/{sample}.bam" output: "mapped/{sample}.sorted.bam" params: "-m 4G" threads: 8 wrapper: "0.0.8/bio/samtools_sort" Refers to the wrapper ``"0.0.8/bio/samtools_sort"`` to create the output from the input. Snakemake will automatically download the wrapper from the `Snakemake Wrapper Repository`_. Thereby, 0.0.8 can be replaced with the git `version tag `_ you want to use, or a `commit id `_. This ensures reproducibility since changes in the wrapper implementation won't be propagated automatically to your workflow. Alternatively, e.g., for development, the wrapper directive can also point to full URLs, including URLs to local files with absolute paths ``file://`` or relative paths ``file:``. Examples for each wrapper can be found in the READMEs located in the wrapper subdirectories at the `Snakemake Wrapper Repository`_. The `Snakemake Wrapper Repository`_ is meant as a collaborative project and pull requests are very welcome. .. _cwl: -------------------------------------- Common-Workflow-Language (CWL) support -------------------------------------- With Snakemake 4.8.0, it is possible to refer to `CWL `_ tool definitions in rules instead of specifying a wrapper or a plain shell command. A CWL tool definition can be used as follows. .. code-block:: python rule samtools_sort: input: input="mapped/{sample}.bam" output: output_name="mapped/{sample}.sorted.bam" params: threads=lambda wildcards, threads: threads, memory="4G" threads: 8 cwl: "https://github.com/common-workflow-language/workflows/blob/" "fb406c95/tools/samtools-sort.cwl" It is advisable to use a github URL that includes the commit as above instead of a branch name, in order to ensure reproducible results. Snakemake will execute the rule by invoking `cwltool`, which has to be available via your `$PATH` variable, and can be, e.g., installed via `conda` or `pip`. When using in combination with :ref:`--use-singularity `, Snakemake will instruct `cwltool` to execute the command via Singularity in user space. Otherwise, `cwltool` will in most cases use a Docker container, which requires Docker to be set up properly. The advantage is that predefined tools available via any `repository of CWL tool definitions `_ can be used in any supporting workflow management system. In contrast to a :ref:`Snakemake wrapper `, CWL tool definitions are in general not suited to alter the behavior of a tool, e.g., by normalizing output names or special input handling. As you can see in comparison to the analog :ref:`wrapper declaration ` above, the rule becomes slightly more verbose, because input, output, and params have to be dispatched to the specific expectations of the CWL tool definition. .. _snakefiles-includes: -------- Includes -------- Another Snakefile with all its rules can be included into the current: .. code-block:: python include: "path/to/other/snakefile" The default target rule (often called the ``all``-rule), won't be affected by the include. I.e. it will always be the first rule in your Snakefile, no matter how many includes you have above your first rule. Includes are relative to the directory of the Snakefile in which they occur. For example, if above Snakefile resides in the directory ``my/dir``, then Snakemake will search for the include at ``my/dir/path/to/other/snakefile``, regardless of the working directory. .. _snakefiles-sub_workflows: ------------- Sub-Workflows ------------- In addition to including rules of another workflow, Snakemake allows to depend on the output of other workflows as sub-workflows. A sub-workflow is executed independently before the current workflow is executed. Thereby, Snakemake ensures that all files the current workflow depends on are created or updated if necessary. This allows to create links between otherwise separate data analyses. .. code-block:: python subworkflow otherworkflow: workdir: "../path/to/otherworkflow" snakefile: "../path/to/otherworkflow/Snakefile" configfile: "path/to/custom_configfile.yaml" rule a: input: otherworkflow("test.txt") output: ... shell: ... Here, the subworkflow is named "otherworkflow" and it is located in the working directory ``../path/to/otherworkflow``. The snakefile is in the same directory and called ``Snakefile``. If ``snakefile`` is not defined for the subworkflow, it is assumed be located in the workdir location and called ``Snakefile``, hence, above we could have left the ``snakefile`` keyword out as well. If ``workdir`` is not specified, it is assumed to be the same as the current one. The (optional) definition of a ``configfile`` allows to parameterize the subworkflow as needed. Files that are output from the subworkflow that we depend on are marked with the ``otherworkflow`` function (see the input of rule a). This function automatically determines the absolute path to the file (here ``../path/to/otherworkflow/test.txt``). When executing, snakemake first tries to create (or update, if necessary) ``test.txt`` (and all other possibly mentioned dependencies) by executing the subworkflow. Then the current workflow is executed. This can also happen recursively, since the subworkflow may have its own subworkflows as well. snakemake-5.10.0/docs/snakefiles/remote_files.rst000066400000000000000000000770211361131222100220160ustar00rootroot00000000000000.. _snakefiles-remote_files: ============ Remote files ============ In versions ``snakemake>=3.5``. The ``Snakefile`` supports a wrapper function, ``remote()``, indicating a file is on a remote storage provider (this is similar to ``temp()`` or ``protected()``). In order to use all types of remote files, the Python packages ``boto``, ``moto``, ``filechunkio``, ``pysftp``, ``dropbox``, ``requests``, ``ftputil``, ``XRootD``, and ``biopython`` must be installed. During rule execution, a remote file (or object) specified is downloaded to the local ``cwd``, within a sub-directory bearing the same name as the remote provider. This sub-directory naming lets you have multiple remote origins with reduced likelihood of name collisions, and allows Snakemake to easily translate remote objects to local file paths. You can think of each local remote sub-directory as a local mirror of the remote system. The ``remote()`` wrapper is mutually-exclusive with the ``temp()`` and ``protected()`` wrappers. Snakemake includes the following remote providers, supported by the corresponding classes: * Amazon Simple Storage Service (AWS S3): ``snakemake.remote.S3`` * Google Cloud Storage (GS): ``snakemake.remote.GS`` * Microsoft Azure Storage: ``snakemake.remote.AzureStorage`` * File transfer over SSH (SFTP): ``snakemake.remote.SFTP`` * Read-only web (HTTP[S]): ``snakemake.remote.HTTP`` * File transfer protocol (FTP): ``snakemake.remote.FTP`` * Dropbox: ``snakemake.remote.dropbox`` * XRootD: ``snakemake.remote.XRootD`` * GenBank / NCBI Entrez: ``snakemake.remote.NCBI`` * WebDAV: ``snakemake.remote.webdav`` * GFAL: ``snakemake.remote.gfal`` * GridFTP: ``snakemake.remote.gridftp`` * iRODS: ``snakemake.remote.iRODS`` * EGA: ``snakemake.remote.EGA`` Amazon Simple Storage Service (S3) ================================== This section describes usage of the S3 RemoteProvider, and also provides an intro to remote files and their usage. It is important to note that you must have credentials (``access_key_id`` and ``secret_access_key``) which permit read/write access. If a file only serves as input to a Snakemake rule, read access is sufficient. You may specify credentials as environment variables or in the file ``=/.aws/credentials``, prefixed with ``AWS_*``, as with a standard `boto config `_. Credentials may also be explicitly listed in the ``Snakefile``, as shown below: For the Amazon S3 and Google Cloud Storage providers, the sub-directory used must be the bucket name. Using remote files is easy (AWS S3 shown): .. code-block:: python from snakemake.remote.S3 import RemoteProvider as S3RemoteProvider S3 = S3RemoteProvider(access_key_id="MYACCESSKEY", secret_access_key="MYSECRET") rule all: input: S3.remote("bucket-name/file.txt") Expand still works as expected, just wrap the expansion: .. code-block:: python from snakemake.remote.S3 import RemoteProvider as S3RemoteProvider S3 = S3RemoteProvider() rule all: input: S3.remote(expand("bucket-name/{letter}-2.txt", letter=["A", "B", "C"])) Only remote files needed to satisfy the DAG build are downloaded for the workflow. By default, remote files are downloaded prior to rule execution and are removed locally as soon as no rules depend on them. Remote files can be explicitly kept by setting the ``keep_local=True`` keyword argument: .. code-block:: python from snakemake.remote.S3 import RemoteProvider as S3RemoteProvider S3 = S3RemoteProvider(access_key_id="MYACCESSKEY", secret_access_key="MYSECRET") rule all: input: S3.remote('bucket-name/prefix{split_id}.txt', keep_local=True) If you wish to have a rule to simply download a file to a local copy, you can do so by declaring the same file path locally as is used by the remote file: .. code-block:: python from snakemake.remote.S3 import RemoteProvider as S3RemoteProvider S3 = S3RemoteProvider(access_key_id="MYACCESSKEY", secret_access_key="MYSECRET") rule all: input: S3.remote("bucket-name/out.txt") output: "bucket-name/out.txt" run: shell("cp {output[0]} ./") In some cases the rule can use the data directly on the remote provider, in these cases ``stay_on_remote=True`` can be set to avoid downloading/uploading data unnecessarily. Additionally, if the backend supports it, any potentially corrupt output files will be removed from the remote. The default for ``stay_on_remote`` and ``keep_local`` can be configured by setting these properties on the remote provider object: .. code-block:: python from snakemake.remote.S3 import RemoteProvider as S3RemoteProvider S3 = S3RemoteProvider(access_key_id="MYACCESSKEY", secret_access_key="MYSECRET", keep_local=True, stay_on_remote=True) The remote provider also supports a new ``glob_wildcards()`` (see :ref:`glob-wildcards`) which acts the same as the local version of ``glob_wildcards()``, but for remote files: .. code-block:: python from snakemake.remote.S3 import RemoteProvider as S3RemoteProvider S3 = S3RemoteProvider(access_key_id="MYACCESSKEY", secret_access_key="MYSECRET") S3.glob_wildcards("bucket-name/{file_prefix}.txt") # (result looks just like as if the local glob_wildcards() function were used on a locally with a folder called "bucket-name") If the AWS CLI is installed it is possible to configure your keys globally. This removes the necessity of hardcoding the keys in the Snakefile. The interactive AWS credentials setup can be done using the following command: .. code-block:: python aws configure S3 then can be used without the keys. .. code-block:: python from snakemake.remote.S3 import RemoteProvider as S3RemoteProvider S3 = S3RemoteProvider() Finally, it is also possible to overwrite the S3 host via adding a ``host`` argument (taking a URL string) to ``S3RemoteProvider``. Google Cloud Storage (GS) ========================= Usage of the GS provider is the same as the S3 provider. For authentication, one simply needs to login via the ``gcloud`` tool before executing Snakemake, i.e.: .. code-block:: console $ gcloud auth application-default login In the Snakefile, no additional authentication information has to be provided: .. code-block:: python from snakemake.remote.GS import RemoteProvider as GSRemoteProvider GS = GSRemoteProvider() rule all: input: GS.remote("bucket-name/file.txt") Microsoft Azure Storage ======================= Usage of the Azure Storage provider is similar to the S3 provider. For authentication, one needs to provide an account name and a key, which can e.g. be taken from environment variables. .. code-block:: python from snakemake.remote.AzureStorage import RemoteProvider as AzureRemoteProvider account_key=os.environ['AZURE_KEY'] account_name=os.environ['AZURE_ACCOUNT'] AS = AzureRemoteProvider(account_name=account_name, account_key=account_key) rule a: input: AS.remote("path/to/file.txt") File transfer over SSH (SFTP) ============================= Snakemake can use files on remove servers accessible via SFTP (i.e. most \*nix servers). It uses `pysftp `_ for the underlying support of SFTP, so the same connection options exist. Assuming you have SSH keys already set up for the server you are using in the ``Snakefile``, usage is simple: .. code-block:: python from snakemake.remote.SFTP import RemoteProvider SFTP = RemoteProvider() rule all: input: SFTP.remote("example.com/path/to/file.bam") The remote file addresses used must be specified with the host (domain or IP address) and the absolute path to the file on the remote server. A port may be specified if the SSH daemon on the server is listening on a port other than 22, in either the ``RemoteProvider`` or in each instance of ``remote()``: .. code-block:: python from snakemake.remote.SFTP import RemoteProvider SFTP = RemoteProvider(port=4040) rule all: input: SFTP.remote("example.com/path/to/file.bam") .. code-block:: python from snakemake.remote.SFTP import RemoteProvider SFTP = RemoteProvider() rule all: input: SFTP.remote("example.com:4040/path/to/file.bam") The standard keyword arguments used by `pysftp `_ may be provided to the RemoteProvider to specify credentials (either password or private key): .. code-block:: python from snakemake.remote.SFTP import RemoteProvider SFTP = RemoteProvider(username="myusername", private_key="/Users/myusername/.ssh/particular_id_rsa") rule all: input: SFTP.remote("example.com/path/to/file.bam") .. code-block:: python from snakemake.remote.SFTP import RemoteProvider SFTP = RemoteProvider(username="myusername", password="mypassword") rule all: input: SFTP.remote("example.com/path/to/file.bam") If you share credentials between servers but connect to one on a different port, the alternate port may be specified in the ``remote()`` wrapper: .. code-block:: python from snakemake.remote.SFTP import RemoteProvider SFTP = RemoteProvider(username="myusername", password="mypassword") rule all: input: SFTP.remote("some-example-server-1.com/path/to/file.bam"), SFTP.remote("some-example-server-2.com:2222/path/to/file.bam") There is a ``glob_wildcards()`` function: .. code-block:: python from snakemake.remote.SFTP import RemoteProvider SFTP = RemoteProvider() SFTP.glob_wildcards("example.com/path/to/{sample}.bam") Read-only web (HTTP[s]) ======================= Snakemake can access web resources via a read-only HTTP(S) provider. This provider can be helpful for including public web data in a workflow. Web addresses must be specified without protocol, so if your URI looks like this: .. code-block:: text http://server3.example.com/path/to/myfile.tar.gz The URI used in the ``Snakefile`` must look like this: .. code-block:: text server3.example.com/path/to/myfile.tar.gz It is straightforward to use the HTTP provider to download a file to the `cwd`: .. code-block:: python import os from snakemake.remote.HTTP import RemoteProvider as HTTPRemoteProvider HTTP = HTTPRemoteProvider() rule all: input: HTTP.remote("www.example.com/path/to/document.pdf", keep_local=True) run: outputName = os.path.basename(input[0]) shell("mv {input} {outputName}") To connect on a different port, specify the port as part of the URI string: .. code-block:: python from snakemake.remote.HTTP import RemoteProvider as HTTPRemoteProvider HTTP = HTTPRemoteProvider() rule all: input: HTTP.remote("www.example.com:8080/path/to/document.pdf", keep_local=True) By default, the HTTP provider always uses HTTPS (TLS). If you need to connect to a resource with regular HTTP (no TLS), you must explicitly include ``insecure`` as a ``kwarg`` to ``remote()``: .. code-block:: python from snakemake.remote.HTTP import RemoteProvider as HTTPRemoteProvider HTTP = HTTPRemoteProvider() rule all: input: HTTP.remote("www.example.com/path/to/document.pdf", insecure=True, keep_local=True) If the URI used includes characters not permitted in a local file path, you may include them as part of the ``additional_request_string`` in the ``kwargs`` for ``remote()``. This may also be useful for including additional parameters you don not want to be part of the local filename (since the URI string becomes the local file name). .. code-block:: python from snakemake.remote.HTTP import RemoteProvider as HTTPRemoteProvider HTTP = HTTPRemoteProvider() rule all: input: HTTP.remote("example.com/query.php", additional_request_string="?range=2;3") If the file requires authentication, you can specify a username and password for HTTP Basic Auth with the Remote Provider, or with each instance of `remote()`. For different types of authentication, you can pass in a Python ```requests.auth`` object (see `here `_) the `auth` ``kwarg``. .. code-block:: python from snakemake.remote.HTTP import RemoteProvider as HTTPRemoteProvider HTTP = HTTPRemoteProvider(username="myusername", password="mypassword") rule all: input: HTTP.remote("example.com/interactive.php", keep_local=True) .. code-block:: python from snakemake.remote.HTTP import RemoteProvider as HTTPRemoteProvider HTTP = HTTPRemoteProvider() rule all: input: HTTP.remote("example.com/interactive.php", username="myusername", password="mypassword", keep_local=True) .. code-block:: python from snakemake.remote.HTTP import RemoteProvider as HTTPRemoteProvider HTTP = HTTPRemoteProvider() rule all: input: HTTP.remote("example.com/interactive.php", auth=requests.auth.HTTPDigestAuth("myusername", "mypassword"), keep_local=True) Since remote servers do not present directory contents uniformly, ``glob_wildcards()`` is __not__ supported by the HTTP provider. File Transfer Protocol (FTP) ============================ Snakemake can work with files stored on regular FTP. Currently supported are authenticated FTP and anonymous FTP, excluding FTP via TLS. Usage is similar to the SFTP provider, however the paths specified are relative to the FTP home directory (since this is typically a chroot): .. code-block:: python from snakemake.remote.FTP import RemoteProvider as FTPRemoteProvider FTP = FTPRemoteProvider(username="myusername", password="mypassword") rule all: input: FTP.remote("example.com/rel/path/to/file.tar.gz") The port may be specified in either the provider, or in each instance of `remote()`: .. code-block:: python from snakemake.remote.FTP import RemoteProvider as FTPRemoteProvider FTP = FTPRemoteProvider(username="myusername", password="mypassword", port=2121) rule all: input: FTP.remote("example.com/rel/path/to/file.tar.gz") .. code-block:: python from snakemake.remote.FTP import RemoteProvider as FTPRemoteProvider FTP = FTPRemoteProvider(username="myusername", password="mypassword") rule all: input: FTP.remote("example.com:2121/rel/path/to/file.tar.gz") Anonymous download of FTP resources is possible: .. code-block:: python from snakemake.remote.FTP import RemoteProvider as FTPRemoteProvider FTP = FTPRemoteProvider() rule all: input: # only keeping the file so we can move it out to the cwd FTP.remote("example.com/rel/path/to/file.tar.gz", keep_local=True) run: shell("mv {input} ./") ``glob_wildcards()``: .. code-block:: python from snakemake.remote.FTP import RemoteProvider as FTPRemoteProvider FTP = FTPRemoteProvider(username="myusername", password="mypassword") print(FTP.glob_wildcards("example.com/somedir/{file}.txt")) Setting `immediate_close=True` allows the use of a large number of remote FTP input files in a job where the endpoint server limits the number of concurrent connections. When `immediate_close=True`, Snakemake will terminate FTP connections after each remote file action (`exists()`, `size()`, `download()`, `mtime()`, etc.). This is in contrast to the default behavior which caches FTP details and leaves the connection open across actions to improve performance (closing the connection upon job termination). : .. code-block:: python from snakemake.remote.FTP import RemoteProvider as FTPRemoteProvider FTP = FTPRemoteProvider() rule all: input: # only keep the file so we can move it out to the cwd # This server limits the number of concurrent connections so we need to have Snakemake close each after each FTP action. FTP.remote(expand("ftp.example.com/rel/path/to/{file}", file=large_list), keep_local=True, immediate_close=True) run: shell("mv {input} ./") ``glob_wildcards()``: .. code-block:: python from snakemake.remote.FTP import RemoteProvider as FTPRemoteProvider FTP = FTPRemoteProvider(username="myusername", password="mypassword") print(FTP.glob_wildcards("example.com/somedir/{file}.txt")) Dropbox ======= The Dropbox remote provider allows you to upload and download from your `Dropbox `_ account without having the client installed on your machine. In order to use the provider you first need to register an "app" on the `Dropbox developer website `_, with access to the Full Dropbox. After registering, generate an OAuth2 access token. You will need the token to use the Snakemake Dropbox remote provider. Using the Dropbox provider is straightforward: .. code-block:: python from snakemake.remote.dropbox import RemoteProvider as DropboxRemoteProvider DBox = DropboxRemoteProvider(oauth2_access_token="mytoken") rule all: input: DBox.remote("path/to/input.txt") ``glob_wildcards()`` is supported: .. code-block:: python from snakemake.remote.dropbox import RemoteProvider as DropboxRemoteProvider DBox = DropboxRemoteProvider(oauth2_access_token="mytoken") DBox.glob_wildcards("path/to/{title}.txt") Note that Dropbox paths are case-insensitive. XRootD ======= Snakemake can be used with `XRootD `_ backed storage provided the python bindings are installed. This is typically most useful when combined with the ``stay_on_remote`` flag to minimise local storage requirements. This flag can be overridden on a file by file basis as described in the S3 remote. Additionally ``glob_wildcards()`` is supported: .. code-block:: python from snakemake.remote.XRootD import RemoteProvider as XRootDRemoteProvider XRootD = XRootDRemoteProvider(stay_on_remote=True) file_numbers = XRootD.glob_wildcards("root://eospublic.cern.ch//eos/opendata/lhcb/MasterclassDatasets/D0lifetime/2014/mclasseventv2_D0_{n}.root") rule all: input: XRootD.remote(expand("local_data/mclasseventv2_D0_{n}.root", n=file_numbers)) rule make_data: input: XRootD.remote("root://eospublic.cern.ch//eos/opendata/lhcb/MasterclassDatasets/D0lifetime/2014/mclasseventv2_D0_{n}.root") output: 'local_data/mclasseventv2_D0_{n}.root' shell: 'xrdcp {input[0]} {output[0]}' GenBank / NCBI Entrez ===================== Snakemake can directly source input files from `GenBank `_ and other `NCBI Entrez databases `_ if the Biopython library is installed. .. code-block:: python from snakemake.remote.NCBI import RemoteProvider as NCBIRemoteProvider NCBI = NCBIRemoteProvider(email="someone@example.com") # email required by NCBI to prevent abuse rule all: input: "size.txt" rule download_and_count: input: NCBI.remote("KY785484.1.fasta", db="nuccore") output: "size.txt" run: shell("wc -c {input} > {output}") The output format and source database of a record retrieved from GenBank is inferred from the file extension specified. For example, ``NCBI.RemoteProvider().remote("KY785484.1.fasta", db="nuccore")`` will download a FASTA file while ``NCBI.RemoteProvider().remote("KY785484.1.gb", db="nuccore")`` will download a GenBank-format file. If the options are ambiguous, Snakemake will raise an exception and inform the user of possible format choices. To see available formats, consult the `Entrez EFetch documentation `_. To view the valid file extensions for these formats, access ``NCBI.RemoteProvider()._gb.valid_extensions``, or instantiate an ``NCBI.NCBIHelper()`` and access ``NCBI.NCBIHelper().valid_extensions`` (this is a property). When used in conjunction with ``NCBI.RemoteProvider().search()``, Snakemake and ``NCBI.RemoteProvider().remote()`` can be used to find accessions by query and download them: .. code-block:: python from snakemake.remote.NCBI import RemoteProvider as NCBIRemoteProvider NCBI = NCBIRemoteProvider(email="someone@example.com") # email required by NCBI to prevent abuse # get accessions for the first 3 results in a search for full-length Zika virus genomes # the query parameter accepts standard GenBank search syntax query = '"Zika virus"[Organism] AND (("9000"[SLEN] : "20000"[SLEN]) AND ("2017/03/20"[PDAT] : "2017/03/24"[PDAT])) ' accessions = NCBI.search(query, retmax=3) # give the accessions a file extension to help the RemoteProvider determine the # proper output type. input_files = expand("{acc}.fasta", acc=accessions) rule all: input: "sizes.txt" rule download_and_count: input: # Since *.fasta files could come from several different databases, specify the database here. # if the input files are ambiguous, the provider will alert the user with possible options # standard options like "seq_start" are supported NCBI.remote(input_files, db="nuccore", seq_start=5000) output: "sizes.txt" run: shell("wc -c {input} > sizes.txt") Normally, all accessions for a query are returned from ``NCBI.RemoteProvider.search()``. To truncate the results, specify ``retmax=``. Standard Entrez `fetch query options `_ are supported as kwargs, and may be passed in to ``NCBI.RemoteProvider.remote()`` and ``NCBI.RemoteProvider.search()``. WebDAV ====== WebDAV support is currently ``experimental`` and available in Snakemake 4.0 and later. Snakemake supports reading and writing WebDAV remote files. The protocol defaults to ``https://``, but insecure connections can be used by specifying ``protocol=="http://"``. Similarly, the port defaults to 443, and can be overridden by specifying ``port=##`` or by including the port as part of the file address. .. code-block:: python from snakemake.remote import webdav webdav = webdav.RemoteProvider(username="test", password="test", protocol="http://") rule a: input: webdav.remote("example.com:8888/path/to/input_file.csv"), shell: # do something GFAL ==== GFAL support is available in Snakemake 4.1 and later. Snakemake supports reading and writing remote files via the `GFAL `_ command line client (gfal-* commands). By this, it supports various grid storage protocols like `GridFTP `_. In general, if you are able to use the `gfal-*` commands directly, Snakemake support for GFAL will work as well. .. code-block:: python from snakemake.remote import gfal gfal = gfal.RemoteProvider(retry=5) rule a: input: gfal.remote("gridftp.grid.sara.nl:2811/path/to/infile.txt") output: gfal.remote("gridftp.grid.sara.nl:2811/path/to/outfile.txt") shell: # do something Authentication has to be setup in the system, e.g. via certificates in the ``.globus`` directory. Usually, this is already the case and no action has to be taken. The keyword argument to the remote provider allows to set the number of retries (10 per default) in case of failed commands (the GRID is usually relatively unreliable). The latter may be unsupported depending on the system configuration. Note that GFAL support used together with the flags ``--no-shared-fs`` and ``--default-remote-provider`` enables you to transparently use Snakemake in a grid computing environment without a shared network filesystem. For an example see the `surfsara-grid configuration profile `_. GridFTP ======= GridFTP support is available in Snakemake 4.3.0 and later. As a more specialized alternative to the GFAL remote provider, Snakemake provides a `GridFTP `_ remote provider. This provider only supports the GridFTP protocol. Internally, it uses the `globus-url-copy `_ command for downloads and uploads, while all other tasks are delegated to the GFAL remote provider. .. code-block:: python from snakemake.remote import gridftp gridftp = gridftp.RemoteProvider(retry=5) rule a: input: gridftp.remote("gridftp.grid.sara.nl:2811/path/to/infile.txt") output: gridftp.remote("gridftp.grid.sara.nl:2811/path/to/outfile.txt") shell: # do something Authentication has to be setup in the system, e.g. via certificates in the ``.globus`` directory. Usually, this is already the case and no action has to be taken. The keyword argument to the remote provider allows to set the number of retries (10 per default) in case of failed commands (the GRID is usually relatively unreliable). The latter may be unsupported depending on the system configuration. Note that GridFTP support used together with the flags ``--no-shared-fs`` and ``--default-remote-provider`` enables you to transparently use Snakemake in a grid computing environment without a shared network filesystem. For an example see the `surfsara-grid configuration profile `_. Remote cross-provider transfers =============================== It is possible to use Snakemake to transfer files between remote providers (using the local machine as an intermediary), as long as the sub-directory (bucket) names differ: .. code-block:: python from snakemake.remote.GS import RemoteProvider as GSRemoteProvider from snakemake.remote.S3 import RemoteProvider as S3RemoteProvider GS = GSRemoteProvider(access_key_id="MYACCESSKEYID", secret_access_key="MYSECRETACCESSKEY") S3 = S3RemoteProvider(access_key_id="MYACCESSKEYID", secret_access_key="MYSECRETACCESSKEY") fileList, = S3.glob_wildcards("source-bucket/{file}.bam") rule all: input: GS.remote( expand("destination-bucket/{file}.bam", file=fileList) ) rule transfer_S3_to_GS: input: S3.remote( expand("source-bucket/{file}.bam", file=fileList) ) output: GS.remote( expand("destination-bucket/{file}.bam", file=fileList) ) run: shell("cp {input} {output}") iRODS ===== You can access an iRODS server to retrieve data from and upload data to it. If your iRODS server is not set to a certain timezone, it is using UTC. It is advised to shift the modification time provided by iRODS (``modify_time``) then to your timezone by providing the ``timezone`` parameter such that timestamps coming from iRODS are converted to the correct time. iRODS actually does not save the timestamp from your original file but creates its own timestamp of the upload time. When iRODS downloads the file for processing, it does not take the timestamp from the remote file. Instead, the file will have the timestamp when it was downloaded. To get around this, we create a metadata entry to store the original file stamp from your system and alter the timestamp of the downloaded file accordingly. While uploading, the metadata entries ``atime``, ``ctime`` and ``mtime`` are added. When this entry does not exist (because this module didn't upload the file), we fall back to the timestamp provided by iRODS with the above mentioned strategy. To access the iRODS server you need to have an iRODS environment configuration file available and in this file the authentication needs to be configured. The iRODS configuration file can be created by following the `official instructions `_). The default location for the configuration file is ``~/.irods/irods_environment.json``. The ``RemoteProvider()`` class accepts the parameter ``irods_env_file`` where an alternative path to the ``irods_environment.json`` file can be specified. Another way is to export the environment variable ``IRODS_ENVIRONMENT_FILE`` in your shell to specify the location. There are several ways to configure the authentication against the iRODS server, depending on what your iRODS server offers. If you are using the authentication via password, the default location of the authentication file is ``~/.irods/.irodsA``. Usually this file is generated with the ``iinit`` command from the ``iCommands`` program suite. Inside the ``irods_environment.json`` file, the parameter ``"irods_authentication_file"`` can be set to specifiy an alternative location for the ``.irodsA`` file. Another possibility to change the location is to export the environment variable ``IRODS_AUTHENTICATION_FILE``. The ``glob_wildcards()`` function is supported. .. code-block:: python from snakemake.remote.iRODS import RemoteProvider irods = RemoteProvider(irods_env_file='setup-data/irods_environment.json', timezone="Europe/Berlin") # all parameters are optional # please note the comma after the variable name! # access: irods.remote(expand('home/rods/{f}), f=files)) files, = irods.glob_wildcards('home/rods/{files}) rule all: input: irods.remote('home/rods/testfile.out'), rule gen: input: irods.remote('home/rods/testfile.in') output: irods.remote('home/rods/testfile.out') shell: r""" touch {output} """ An example for the iRODS configuration file (``irods_environment.json``): .. code-block:: json { "irods_host": "localhost", "irods_port": 1247, "irods_user_name": "rods", "irods_zone_name": "tempZone", "irods_authentication_file": "setup-data/.irodsA" } Please note that the ``zone`` folder is not included in the path as it will be taken from the configuration file. The path also must not start with a ``/``. By default, temporarily stored local files are removed. You can specify anyway the parameter ``overwrite`` to tell iRODS to overwrite existing files that are downloaded, because iRODS complains if a local file already exists when a download attempt is issued (uploading is not a problem, though). In the Snakemake source directory in ``snakemake/tests/test_remote_irods`` you can find a working example. EGA === The European Genome-phenome Archive (EGA) is a service for permanent archiving and sharing of all types of personally identifiable genetic and phenotypic data resulting from biomedical research projects. From version 5.2 on, Snakemake provides experimental support to use EGA as a remote provider, such that EGA hosted files can be transparently used as input. For this to work, you need to define your username and password as environment variables ``EGA_USERNAME`` and ``EGA_PASSWORD``. Files in a dataset are addressed via the pattern ``ega//``. Note that the filename should not include the ``.cip`` ending that is sometimes displayed in EGA listings: .. code-block:: python import snakemake.remote.EGA as EGA ega = EGA.RemoteProvider() rule a: input: ega.remote("ega/EGAD00001002142/COLO_829_EPleasance_TGENPipe.bam.bai") output: "data/COLO_829BL_BCGSC_IlluminaPipe.bam.bai" shell: "cp {input} {output}" Upon download, Snakemake will automatically decrypt the file and check the MD5 hash. snakemake-5.10.0/docs/snakefiles/reporting.rst000066400000000000000000000102411361131222100213410ustar00rootroot00000000000000.. _snakefiles-reports: ------- Reports ------- From Snakemake 5.1 on, it is possible to automatically generate detailed self-contained HTML reports that encompass runtime statistics, provenance information, workflow topology and results. **A realistic example report from a real workflow can be found** `here `_. For including results into the report, the Snakefile has to be annotated with additional information. Each output file that shall be part of the report has to be marked with the ``report`` flag, which optionally points to a caption in `restructured text format `_ and allows to define a ``category`` for grouping purposes. Moreover, a global workflow description can be defined via the ``report`` directive. Consider the following example: .. code-block:: python report: "report/workflow.rst" rule all: input: ["fig1.svg", "fig2.png"] rule c: output: "test.{i}.out" singularity: "docker://continuumio/miniconda3:4.4.10" conda: "envs/test.yaml" shell: "sleep `shuf -i 1-3 -n 1`; touch {output}" rule a: input: expand("test.{i}.out", i=range(10)) output: report("fig1.svg", caption="report/fig1.rst", category="Step 1") shell: "sleep `shuf -i 1-3 -n 1`; cp data/fig1.svg {output}" rule b: input: expand("test.{i}.out", i=range(10)) output: report("fig2.png", caption="report/fig2.rst", category="Step 2") shell: "sleep `shuf -i 1-3 -n 1`; cp data/fig2.png {output}" As can be seen, we define a global description which is contained in the file ``report/workflow.rst``. In addition, we mark ``fig1.svg`` and ``fig2.png`` for inclusion into the report, while in both cases specifying a caption text via again referring to a restructured text file. Note the paths to the ``.rst``-files are interpreted relative to the current Snakefile. Inside the ``.rst``-files you can use `Jinja2 `_ templating to access context information. In case of the global description, you can access the config dictionary via ``{{ snakemake.config }}``, (e.g., use ``{{ snakemake.config["mykey"] }}`` to access the key ``mykey``). In case of output files, you can access the same values as available with the :ref:`script directive `. Moreover, in every ``.rst`` document, you can link to * the **Rules** section (with ``Rules_``), * the **Statistics** section (with ``Statistics_``), * the **Results** section (with ``Results_``), * any **category** section (with ``Mycategory_``, while ``Mycategory`` is the name given for the category argument of the report flag). E.g., with above example, you could write ``see `Step 2`_`` in order to link to the section with the results that have been assigned to the category ``Step 2``. * any **file** marked with the report flag (with ``myfile.txt_``, while ``myfile.txt`` is the basename of the file, without any leading directories). E.g., with above example, you could write ``see fig2.png_`` in order to link to the result in the report document. For details about the hyperlink mechanism of restructured text see `here `_. To create the report simply run .. code-block:: bash snakemake --report report.html after your workflow has finished. All other information contained in the report (e.g. runtime statistics) is automatically collected during creation. These statistics are obtained from the metadata that is stored in the ``.snakemake`` directory inside your working directory. The report for above example can be found :download:`here <../../tests/test_report/report.html>`. The full example source code can be found `here `_. Note that the report can be restricted to particular jobs and results by specifying targets at the command line, analog to normal Snakemake execution. For example, with .. code-block:: bash snakemake fig1.svg --report report-short.html the report contains only ``fig1.svg``. snakemake-5.10.0/docs/snakefiles/rules.rst000066400000000000000000001576101361131222100204760ustar00rootroot00000000000000.. _snakefiles-rules: ===== Rules ===== Most importantly, a rule can consist of a name (the name is optional and can be left out, creating an anonymous rule), input files, output files, and a shell command to generate the output from the input, i.e. .. code-block:: python rule NAME: input: "path/to/inputfile", "path/to/other/inputfile" output: "path/to/outputfile", "path/to/another/outputfile" shell: "somecommand {input} {output}" Inside the shell command, all local and global variables, especially input and output files can be accessed via their names in the `python format minilanguage `_. Here input and output (and in general any list or tuple) automatically evaluate to a space-separated list of files (i.e. ``path/to/inputfile path/to/other/inputfile``). From Snakemake 3.8.0 on, adding the special formatting instruction ``:q`` (e.g. ``"somecommand {input:q} {output:q}")``) will let Snakemake quote each of the list or tuple elements that contains whitespace. Instead of a shell command, a rule can run some python code to generate the output: .. code-block:: python rule NAME: input: "path/to/inputfile", "path/to/other/inputfile" output: "path/to/outputfile", somename = "path/to/another/outputfile" run: for f in input: ... with open(output[0], "w") as out: out.write(...) with open(output.somename, "w") as out: out.write(...) As can be seen, instead of accessing input and output as a whole, we can also access by index (``output[0]``) or by keyword (``output.somename``). Note that, when adding keywords or names for input or output files, their order won't be preserved when accessing them as a whole via e.g. ``{output}`` in a shell command. Shell commands like above can also be invoked inside a python based rule, via the function ``shell`` that takes a string with the command and allows the same formatting like in the rule above, e.g.: .. code-block:: python shell("somecommand {output.somename}") Further, this combination of python and shell commands, allows to iterate over the output of the shell command, e.g.: .. code-block:: python for line in shell("somecommand {output.somename}", iterable=True): ... # do something in python Note that shell commands in Snakemake use the bash shell in `strict mode `_ by default. .. _snakefiles-wildcards: Wildcards --------- Usually, it is useful to generalize a rule to be applicable to a number of e.g. datasets. For this purpose, wildcards can be used. Automatically resolved multiple named wildcards are a key feature and strength of Snakemake in comparison to other systems. Consider the following example. .. code-block:: python rule complex_conversion: input: "{dataset}/inputfile" output: "{dataset}/file.{group}.txt" shell: "somecommand --group {wildcards.group} < {input} > {output}" Here, we define two wildcards, ``dataset`` and ``group``. By this, the rule can produce all files that follow the regular expression pattern ``.+/file\..+\.txt``, i.e. the wildcards are replaced by the regular expression ``.+``. If the rule's output matches a requested file, the substrings matched by the wildcards are propagated to the input files and to the variable wildcards, that is here also used in the shell command. The wildcards object can be accessed in the same way as input and output, which is described above. For example, if another rule in the workflow requires the file ``101/file.A.txt``, Snakemake recognizes that this rule is able to produce it by setting ``dataset=101`` and ``group=A``. Thus, it requests file ``101/inputfile`` as input and executes the command ``somecommand --group A < 101/inputfile > 101/file.A.txt``. Of course, the input file might have to be generated by another rule with different wildcards. Importantly, the wildcard names in input and output must be named identically. Most typically, the same wildcard is present in both input and output, but it is of course also possible to have wildcards only in the output but not the input section. Multiple wildcards in one filename can cause ambiguity. Consider the pattern ``{dataset}.{group}.txt`` and assume that a file ``101.B.normal.txt`` is available. It is not clear whether ``dataset=101.B`` and ``group=normal`` or ``dataset=101`` and ``group=B.normal`` in this case. Hence wildcards can be constrained to given regular expressions. Here we could restrict the wildcard ``dataset`` to consist of digits only using ``\d+`` as the corresponding regular expression. With Snakemake 3.8.0, there are three ways to constrain wildcards. First, a wildcard can be constrained within the file pattern, by appending a regular expression separated by a comma: .. code-block:: python output: "{dataset,\d+}.{group}.txt" Second, a wildcard can be constrained within the rule via the keyword ``wildcard_constraints``: .. code-block:: python rule complex_conversion: input: "{dataset}/inputfile" output: "{dataset}/file.{group}.txt" wildcard_constraints: dataset="\d+" shell: "somecommand --group {wildcards.group} < {input} > {output}" Finally, you can also define global wildcard constraints that apply for all rules: .. code-block:: python wildcard_constraints: dataset="\d+" rule a: ... rule b: ... See the `Python documentation on regular expressions `_ for detailed information on regular expression syntax. Aggregation ----------- Input files can be Python lists, allowing to easily aggregate over parameters or samples: .. code-block:: python rule aggregate: input: ["{dataset}/a.txt".format(dataset=dataset) for dataset in DATASETS] output: "aggregated.txt" shell: ... Above expression can be simplified in two ways. The expand function ~~~~~~~~~~~~~~~~~~~ .. code-block:: python rule aggregate: input: expand("{dataset}/a.txt", dataset=DATASETS) output: "aggregated.txt" shell: ... Note that *dataset* is NOT a wildcard here because it is resolved by Snakemake due to the ``expand`` statement. The ``expand`` function thereby allows also to combine different variables, e.g. .. code-block:: python rule aggregate: input: expand("{dataset}/a.{ext}", dataset=DATASETS, ext=FORMATS) output: "aggregated.txt" shell: ... If now ``FORMATS=["txt", "csv"]`` contains a list of desired output formats then expand will automatically combine any dataset with any of these extensions. Further, the first argument can also be a list of strings. In that case, the transformation is applied to all elements of the list. E.g. .. code-block:: python expand(["{dataset}/a.{ext}", "{dataset}/b.{ext}"], dataset=DATASETS, ext=FORMATS) leads to .. code-block:: python ["ds1/a.txt", "ds1/b.txt", "ds2/a.txt", "ds2/b.txt", "ds1/a.csv", "ds1/b.csv", "ds2/a.csv", "ds2/b.csv"] Per default, ``expand`` uses the python itertools function ``product`` that yields all combinations of the provided wildcard values. However by inserting a second positional argument this can be replaced by any combinatoric function, e.g. ``zip``: .. code-block:: python expand(["{dataset}/a.{ext}", "{dataset}/b.{ext}"], zip, dataset=DATASETS, ext=FORMATS) leads to .. code-block:: python ["ds1/a.txt", "ds1/b.txt", "ds2/a.csv", "ds2/b.csv"] You can also mask a wildcard expression in expand such that it will be kept, e.g. .. code-block:: python expand("{{dataset}}/a.{ext}", ext=FORMATS) will create strings with all values for ext but starting with the wildcard ``"{dataset}"``. .. _snakefiles-multiext: The multiext function ~~~~~~~~~~~~~~~~~~~~~ ``multiext`` provides a simplified variant of ``expand`` that allows to define a set of output or input files that just differ by their extension: .. code-block:: python rule plot: input: ... output: multiext("some/plot", ".pdf", ".svg", ".png") shell: ... The effect is the same as if you would write ``expand("some/plot.{ext}", ext=[".pdf", ".svg", ".png"])``, however, using a simpler syntax. Moreover, defining output with ``multiext`` is the only way to use :ref:`between workflow caching ` for rules with multiple output files. .. _snakefiles-targets: Targets and aggregation ----------------------- By default snakemake executes the first rule in the snakefile. This gives rise to pseudo-rules at the beginning of the file that can be used to define build-targets similar to GNU Make: .. code-block:: python rule all: input: ["{dataset}/file.A.txt".format(dataset=dataset) for dataset in DATASETS] Here, for each dataset in a python list ``DATASETS`` defined before, the file ``{dataset}/file.A.txt`` is requested. In this example, Snakemake recognizes automatically that these can be created by multiple applications of the rule ``complex_conversion`` shown above. .. _snakefiles-threads: Threads ------- Further, a rule can be given a number of threads to use, i.e. .. code-block:: python rule NAME: input: "path/to/inputfile", "path/to/other/inputfile" output: "path/to/outputfile", "path/to/another/outputfile" threads: 8 shell: "somecommand --threads {threads} {input} {output}" .. sidebar:: Note On a cluster node, Snakemake uses as many cores as available on that node. Hence, the number of threads used by a rule never exceeds the number of physically available cores on the node. Note: This behavior is not affected by ``--local-cores``, which only applies to jobs running on the master node. Snakemake can alter the number of cores available based on command line options. Therefore it is useful to propagate it via the built in variable ``threads`` rather than hardcoding it into the shell command. In particular, it should be noted that the specified threads have to be seen as a maximum. When Snakemake is executed with fewer cores, the number of threads will be adjusted, i.e. ``threads = min(threads, cores)`` with ``cores`` being the number of cores specified at the command line (option ``--cores``). Hardcoding a particular maximum number of threads like above is useful when a certain tool has a natural maximum beyond it parallelization won't help to further speed it up. This is often the case, and should be evaluated carefully for production workflows. If it is certain that no such maximum exists for a tool, one can instead define threads as a function of the number of cores given to Snakemake: .. code-block:: python rule NAME: input: "path/to/inputfile", "path/to/other/inputfile" output: "path/to/outputfile", "path/to/another/outputfile" threads: workflow.cores * 0.75 shell: "somecommand --threads {threads} {input} {output}" The number of given cores is globally available in the Snakefile as an attribute of the workflow object: ``workflow.cores``. Any arithmetic operation can be performed to derive a number of threads from this. E.g., in the above example, we reserve 75% of the given cores for the rule. Snakemake will always round the calculated value down (while enforcing a minimum of 1 thread). Starting from version 3.7, threads can also be a callable that returns an ``int`` value. The signature of the callable should be ``callable(wildcards[, input])`` (input is an optional parameter). It is also possible to refer to a predefined variable (e.g, ``threads: threads_max``) so that the number of cores for a set of rules can be changed with one change only by altering the value of the variable ``threads_max``. .. _snakefiles-resources: Resources --------- In addition to threads, a rule can use arbitrary user-defined resources by specifying them with the resources-keyword: .. code-block:: python rule: input: ... output: ... resources: mem_mb=100 shell: "..." If limits for the resources are given via the command line, e.g. .. code-block:: console $ snakemake --resources mem_mb=100 the scheduler will ensure that the given resources are not exceeded by running jobs. If no limits are given, the resources are ignored in local execution. In cluster or cloud execution, resources are always passed to the backend, even if ``--resources`` is not specified. Apart from making Snakemake aware of hybrid-computing architectures (e.g. with a limited number of additional devices like GPUs) this allows to control scheduling in various ways, e.g. to limit IO-heavy jobs by assigning an artificial IO-resource to them and limiting it via the ``--resources`` flag. Resources must be ``int`` values. Note that you are free to choose any names for the given resources. There are two **standard resources** for memory and disk usage though: ``mem_mb`` and ``disk_mb``. When defining memory constraints, it is advised to use ``mem_mb``, because there are Some execution modes make direct use of this information (e.g., when using :ref:`Kubernetes `). Since it would be cumbersome to define them for every rule, you can set default values at the terminal or in a :ref:`profile `. This works via the command line flag ``--default-resources``, see ``snakemake --help`` for more information. If those resource definitions are mandatory for a certain execution mode, Snakemake will fail with a hint if they are missing. Any resource definitions inside a rule override what has been defined with ``--default-resources``. Resources can also be callables that return ``int`` values. The signature of the callable has to be ``callable(wildcards [, input] [, threads] [, attempt])`` (``input``, ``threads``, and ``attempt`` are optional parameters). The parameter ``attempt`` allows to adjust resources based on how often the job has been restarted (see :ref:`all_options`, option ``--restart-times``). This is handy when executing a Snakemake workflow in a cluster environment, where jobs can e.g. fail because of too limited resources. When Snakemake is executed with ``--restart-times 3``, it will try to restart a failed job 3 times before it gives up. Thereby, the parameter ``attempt`` will contain the current attempt number (starting from ``1``). This can be used to adjust the required memory as follows .. code-block:: python rule: input: ... output: ... resources: mem_mb=lambda wildcards, attempt: attempt * 100 shell: "..." Here, the first attempt will require 100 MB memory, the second attempt will require 200 MB memory and so on. When passing memory requirements to the cluster engine, you can by this automatically try out larger nodes if it turns out to be necessary. Messages -------- When executing snakemake, a short summary for each running rule is given to the console. This can be overridden by specifying a message for a rule: .. code-block:: python rule NAME: input: "path/to/inputfile", "path/to/other/inputfile" output: "path/to/outputfile", "path/to/another/outputfile" threads: 8 message: "Executing somecommand with {threads} threads on the following files {input}." shell: "somecommand --threads {threads} {input} {output}" Note that access to wildcards is also possible via the variable ``wildcards`` (e.g, ``{wildcards.sample}``), which is the same as with shell commands. It is important to have a namespace around wildcards in order to avoid clashes with other variable names. Priorities ---------- Snakemake allows rules to specify numeric priorities: .. code-block:: python rule: input: ... output: ... priority: 50 shell: ... Per default, each rule has a priority of 0. Any rule that specifies a higher priority, will be preferred by the scheduler over all rules that are ready to execute at the same time without having at least the same priority. Furthermore, the ``--prioritize`` or ``-P`` command line flag allows to specify files (or rules) that shall be created with highest priority during the workflow execution. This means that the scheduler will assign the specified target and all its dependencies highest priority, such that the target is finished as soon as possible. The ``--dry-run`` (equivalently ``--dryrun``) or ``-n`` option allows you to see the scheduling plan including the assigned priorities. Log-Files --------- Each rule can specify a log file where information about the execution is written to: .. code-block:: python rule abc: input: "input.txt" output: "output.txt" log: "logs/abc.log" shell: "somecommand --log {log} {input} {output}" Log files can be used as input for other rules, just like any other output file. However, unlike output files, log files are not deleted upon error. This is obviously necessary in order to discover causes of errors which might become visible in the log file. The variable ``log`` can be used inside a shell command to tell the used tool to which file to write the logging information. The log file has to use the same wildcards as output files, e.g. .. code-block:: python log: "logs/abc.{dataset}.log" For programs that do not have an explicit ``log`` parameter, you may always use ``2> {log}`` to redirect standard output to a file (here, the ``log`` file) in Linux-based systems. Note that it is also supported to have multiple (named) log files being specified: .. code-block:: python rule abc: input: "input.txt" output: "output.txt" log: log1="logs/abc.log", log2="logs/xyz.log" shell: "somecommand --log {log.log1} METRICS_FILE={log.log2} {input} {output}" Non-file parameters for rules ----------------------------- Sometimes you may want to define certain parameters separately from the rule body. Snakemake provides the ``params`` keyword for this purpose: .. code-block:: python rule: input: ... params: prefix="somedir/{sample}" output: "somedir/{sample}.csv" shell: "somecommand -o {params.prefix}" The ``params`` keyword allows you to specify additional parameters depending on the wildcards values. This allows you to circumvent the need to use ``run:`` and python code for non-standard commands like in the above case. Here, the command ``somecommand`` expects the prefix of the output file instead of the actual one. The ``params`` keyword helps here since you cannot simply add the prefix as an output file (as the file won't be created, Snakemake would throw an error after execution of the rule). Furthermore, for enhanced readability and clarity, the ``params`` section is also an excellent place to name and assign parameters and variables for your subsequent command. Similar to ``input``, ``params`` can take functions as well (see :ref:`snakefiles-input_functions`), e.g. you can write .. code-block:: python rule: input: ... params: prefix=lambda wildcards, output: output[0][:-4] output: "somedir/{sample}.csv" shell: "somecommand -o {params.prefix}" to get the same effect as above. Note that in contrast to the ``input`` directive, the ``params`` directive can optionally take more arguments than only ``wildcards``, namely ``input``, ``output``, ``threads``, and ``resources``. From the Python perspective, they can be seen as optional keyword arguments without a default value. Their order does not matter, apart from the fact that ``wildcards`` has to be the first argument. In the example above, this allows you to derive the prefix name from the output file. .. _snakefiles-external_scripts: External scripts ---------------- A rule can also point to an external script instead of a shell command or inline Python code, e.g. .. code-block:: python rule NAME: input: "path/to/inputfile", "path/to/other/inputfile" output: "path/to/outputfile", "path/to/another/outputfile" script: "scripts/script.py" The script path is always relative to the Snakefile (in contrast to the input and output file paths, which are relative to the working directory). It is recommended to put all scripts into a subfolder ``scripts`` as above. Inside the script, you have access to an object ``snakemake`` that provides access to the same objects that are available in the ``run`` and ``shell`` directives (input, output, params, wildcards, log, threads, resources, config), e.g. you can use ``snakemake.input[0]`` to access the first input file of above rule. Apart from Python scripts, this mechanism also allows you to integrate R_ and R Markdown_ scripts with Snakemake, e.g. .. _R: https://www.r-project.org .. _Markdown: http://rmarkdown.rstudio.com .. code-block:: python rule NAME: input: "path/to/inputfile", "path/to/other/inputfile" output: "path/to/outputfile", "path/to/another/outputfile" script: "scripts/script.R" In the R script, an S4 object named ``snakemake`` analog to the Python case above is available and allows access to input and output files and other parameters. Here the syntax follows that of S4 classes with attributes that are R lists, e.g. we can access the first input file with ``snakemake@input[[1]]`` (note that the first file does not have index ``0`` here, because R starts counting from ``1``). Named input and output files can be accessed in the same way, by just providing the name instead of an index, e.g. ``snakemake@input[["myfile"]]``. Alternatively, it is possible to integrate Julia_ scripts, e.g. .. _Julia: https://julialang.org .. code-block:: python rule NAME: input: "path/to/inputfile", "path/to/other/inputfile" output: "path/to/outputfile", "path/to/another/outputfile" script: "path/to/script.jl" In the Julia_ script, a ``snakemake`` object is available, which can be accessed similar to the Python case (see above), with the only difference that you have to index from 1 instead of 0. For technical reasons, scripts are executed in ``.snakemake/scripts``. The original script directory is available as ``scriptdir`` in the ``snakemake`` object. A convenience method, ``snakemake@source()``, acts as a wrapper for the normal R ``source()`` function, and can be used to source files relative to the original script directory. An example external Python script could look like this: .. code-block:: python def do_something(data_path, out_path, threads, myparam): # python code do_something(snakemake.input[0], snakemake.output[0], snakemake.threads, snakemake.config["myparam"]) You can use the Python debugger from within the script if you invoke Snakemake with ``--debug``. An equivalent script written in R would look like this: .. code-block:: r do_something <- function(data_path, out_path, threads, myparam) { # R code } do_something(snakemake@input[[1]], snakemake@output[[1]], snakemake@threads, snakemake@config[["myparam"]]) To debug R scripts, you can save the workspace with ``save.image()``, and invoke R after Snakemake has terminated. Then you can use the usual R debugging facilities while having access to the ``snakemake`` variable. It is best practice to wrap the actual code into a separate function. This increases the portability if the code shall be invoked outside of Snakemake or from a different rule. An R Markdown file can be integrated in the same way as R and Python scripts, but only a single output (html) file can be used: .. code-block:: python rule NAME: input: "path/to/inputfile", "path/to/other/inputfile" output: "path/to/report.html", script: "path/to/report.Rmd" In the R Markdown file you can insert output from a R command, and access variables stored in the S4 object named ``snakemake`` .. code-block:: R --- title: "Test Report" author: - "Your Name" date: "`r format(Sys.time(), '%d %B, %Y')`" params: rmd: "report.Rmd" output: html_document: highlight: tango number_sections: no theme: default toc: yes toc_depth: 3 toc_float: collapsed: no smooth_scroll: yes --- ## R Markdown This is an R Markdown document. Test include from snakemake `r snakemake@input`. ## Source R Markdown source file (to produce this document) A link to the R Markdown document with the snakemake object can be inserted. Therefore a variable called ``rmd`` needs to be added to the ``params`` section in the header of the ``report.Rmd`` file. The generated R Markdown file with snakemake object will be saved in the file specified in this ``rmd`` variable. This file can be embedded into the HTML document using base64 encoding and a link can be inserted as shown in the example above. Also other input and output files can be embedded in this way to make a portable report. Note that the above method with a data URI only works for small files. An experimental technology to embed larger files is using Javascript Blob `object `_. .. _snakefiles_notebook-integration: Jupyter notebook integration ---------------------------- Instead of plain scripts (see above), one can integrate Jupyter_ Notebooks. This enables the interactive development of data analysis components (e.g. for plotting). Integration works as follows (note the use of `notebook:` instead of `script:`): .. _Jupyter: https://jupyter.org/ .. code-block:: python rule NAME: input: "path/to/inputfile", "path/to/other/inputfile" output: "path/to/outputfile", "path/to/another/outputfile" log: # optional path to the processed notebook notebook = "logs/notebooks/processed_notebook.ipynb" notebook: "notebooks/notebook.ipynb" .. note: Consider Jupyter notebook integration as a way to get the best of both worlds. A modular, readable workflow definition with Snakemake, and the ability to quickly explore and plot data with Jupyter. The benefit will be maximal when integrating many small notebooks that each do a particular job, hence allowing to get away from large monolithic, and therefore unreadable notebooks. In the notebook, a snakemake object is available, which can be accessed in the same way as the with :ref:`script integration `. In other words, you have access to input files via ``snakemake.input`` (in the Python case) and ``snakemake@input`` (in the R case) etc.. Hence, integrating a new notebook works by first writing it from scratch in the usual interactive way. Then, you replace all hardcoded variables with references to properties of the rule where it shall be integrated, e.g. replacing the path to an input file with ``snakemake.input[0]``. Once having moved the notebook to the right place in the pipeline (ideally a subfolder ``notebooks``) and referring to it from the rule, Snakemake will be able to re-execute it while inserting the desired variable values from the rule properties. Optionally it is possible to automatically store the processed notebook. This can be achieved by adding a named logfile ``notebook=...`` to the ``log`` directive. Protected and Temporary Files ----------------------------- A particular output file may require a huge amount of computation time. Hence one might want to protect it against accidental deletion or overwriting. Snakemake allows this by marking such a file as ``protected``: .. code-block:: python rule NAME: input: "path/to/inputfile" output: protected("path/to/outputfile") shell: "somecommand {input} {output}" A protected file will be write-protected after the rule that produces it is completed. Further, an output file marked as ``temp`` is deleted after all rules that use it as an input are completed: .. code-block:: python rule NAME: input: "path/to/inputfile" output: temp("path/to/outputfile") shell: "somecommand {input} {output}" Directories as outputs ---------------------- Sometimes it can be convenient to have directories, rather than files, as outputs of a rule. As of version 5.2.0, directories as outputs have to be explicitly marked with ``directory``. This is primarily for safety reasons; since all outputs are deleted before a job is executed, we don't want to risk deleting important directories if the user makes some mistake. Marking the output as ``directory`` makes the intent clear, and the output can be safely removed. Another reason comes down to how modification time for directories work. The modification time on a directory changes when a file or a subdirectory is added, removed or renamed. This can easily happen in not-quite-intended ways, such as when Apple macOS or MS Windows add ``.DS_Store`` or ``thumbs.db`` files to store parameters for how the directory contents should be displayed. When the ``directory`` flag is used a hidden file called ``.snakemake_timestamp`` is created in the output directory, and the modification time of that file is used when determining whether the rule output is up to date or if it needs to be rerun. Always consider if you can't formulate your workflow using normal files before resorting to using ``directory()``. .. code-block:: python rule NAME: input: "path/to/inputfile" output: directory("path/to/outputdir") shell: "somecommand {input} {output}" Ignoring timestamps ------------------- For determining whether output files have to be re-created, Snakemake checks whether the file modification date (i.e. the timestamp) of any input file of the same job is newer than the timestamp of the output file. This behavior can be overridden by marking an input file as ``ancient``. The timestamp of such files is ignored and always assumed to be older than any of the output files: .. code-block:: python rule NAME: input: ancient("path/to/inputfile") output: "path/to/outputfile" shell: "somecommand {input} {output}" Here, this means that the file ``path/to/outputfile`` will not be triggered for re-creation after it has been generated once, even when the input file is modified in the future. Note that any flag that forces re-creation of files still also applies to files marked as ``ancient``. Shadow rules ------------ Shadow rules result in each execution of the rule to be run in isolated temporary directories. This "shadow" directory contains symlinks to files and directories in the current workdir. This is useful for running programs that generate lots of unused files which you don't want to manually cleanup in your snakemake workflow. It can also be useful if you want to keep your workdir clean while the program executes, or simplify your workflow by not having to worry about unique filenames for all outputs of all rules. By setting ``shadow: "shallow"``, the top level files and directories are symlinked, so that any relative paths in a subdirectory will be real paths in the filesystem. The setting ``shadow: "full"`` fully shadows the entire subdirectory structure of the current workdir. The setting ``shadow: "minimal"`` only symlinks the inputs to the rule. Once the rule successfully executes, the output file will be moved if necessary to the real path as indicated by ``output``. Typically, you will not need to modify your rule for compatibility with ``shadow``, unless you reference parent directories relative to your workdir in a rule. .. code-block:: python rule NAME: input: "path/to/inputfile" output: "path/to/outputfile" shadow: "shallow" shell: "somecommand --other_outputs other.txt {input} {output}" Shadow directories are stored one per rule execution in ``.snakemake/shadow/``, and are cleared on successful execution. Consider running with the ``--cleanup-shadow`` argument every now and then to remove any remaining shadow directories from aborted jobs. The base shadow directory can be changed with the ``--shadow-prefix`` command line argument. Flag files ---------- Sometimes it is necessary to enforce some rule execution order without real file dependencies. This can be achieved by "touching" empty files that denote that a certain task was completed. Snakemake supports this via the `touch` flag: .. code-block:: python rule all: input: "mytask.done" rule mytask: output: touch("mytask.done") shell: "mycommand ..." With the ``touch`` flag, Snakemake touches (i.e. creates or updates) the file ``mytask.done`` after ``mycommand`` has finished successfully. .. _snakefiles-job_properties: Job Properties -------------- When executing a workflow on a cluster using the ``--cluster`` parameter (see below), Snakemake creates a job script for each job to execute. This script is then invoked using the provided cluster submission command (e.g. ``qsub``). Sometimes you want to provide a custom wrapper for the cluster submission command that decides about additional parameters. As this might be based on properties of the job, Snakemake stores the job properties (e.g. rule name, threads, input files, params etc.) as JSON inside the job script. For convenience, there exists a parser function ``snakemake.utils.read_job_properties`` that can be used to access the properties. The following shows an example job submission wrapper: .. code-block:: python #!/usr/bin/env python3 import os import sys from snakemake.utils import read_job_properties jobscript = sys.argv[1] job_properties = read_job_properties(jobscript) # do something useful with the threads threads = job_properties[threads] # access property defined in the cluster configuration file (Snakemake >=3.6.0) job_properties["cluster"]["time"] os.system("qsub -t {threads} {script}".format(threads=threads, script=jobscript)) .. _snakefiles-dynamic_files: Dynamic Files ------------- Snakemake provides experimental support for dynamic files. Dynamic files can be used whenever one has a rule, for which the number of output files is unknown before the rule was executed. This is useful for example with certain clustering algorithms: .. code-block:: python rule cluster: input: "afile.csv" output: dynamic("{clusterid}.cluster.csv") run: ... Now the results of the rule can be used in Snakemake although it does not know how many files will be present before executing the rule `cluster`, e.g. by: .. code-block:: python rule all: input: dynamic("{clusterid}.cluster.plot.pdf") rule plot: input: "{clusterid}.cluster.csv" output: "{clusterid}.cluster.plot.pdf" run: ... Here, Snakemake determines the input files for the rule `all` after the rule `cluster` was executed, and then dynamically inserts jobs of the rule `plot` into the DAG to create the desired plots. .. note: Note that dynamic file support is still experimental. Especially, using more than one wildcard within dynamic files can introduce various problems. Before using dynamic files, think about alternative, static solutions, where you know beforehand how many output files your rule will produce. In four years and hundreds of workflows, I needed dynamic files only once. .. _snakefiles-input_functions: Functions as Input Files ------------------------ Instead of specifying strings or lists of strings as input files, snakemake can also make use of functions that return single **or** lists of input files: .. code-block:: python def myfunc(wildcards): return [... a list of input files depending on given wildcards ...] rule: input: myfunc output: "someoutput.{somewildcard}.txt" shell: "..." The function has to accept a single argument that will be the wildcards object generated from the application of the rule to create some requested output files. Note that you can also use `lambda expressions `_ instead of full function definitions. By this, rules can have entirely different input files (both in form and number) depending on the inferred wildcards. E.g. you can assign input files that appear in entirely different parts of your filesystem based on some wildcard value and a dictionary that maps the wildcard value to file paths. Note that the function will be executed when the rule is evaluated and before the workflow actually starts to execute. Further note that using a function as input overrides the default mechanism of replacing wildcards with their values inferred from the output files. You have to take care of that yourself with the given wildcards object. Finally, when implementing the input function, it is best practice to make sure that it can properly handle all possible wildcard values your rule can have. In particular, input files should not be combined with very general rules that can be applied to create almost any file: Snakemake will try to apply the rule, and will report the exceptions of your input function as errors. For a practical example, see the :ref:`tutorial` (:ref:`tutorial-input_functions`). .. _snakefiles-unpack: Input Functions and ``unpack()`` -------------------------------- In some cases, you might want to have your input functions return named input files. This can be done by having them return ``dict()`` objects with the names as the dict keys and the file names as the dict values and using the ``unpack()`` keyword. .. code-block:: python def myfunc(wildcards): return { 'foo': '{wildcards.token}.txt'.format(wildcards=wildcards) rule: input: unpack(myfunc) output: "someoutput.{token}.txt" shell: "..." Note that ``unpack()`` only necessary for input functions returning ``dict``. While it also works for ``list``, remember that lists (and nested lists) of strings are automatically flattened. Also note that if you do not pass in a *function* into the input list but you directly *call a function* then you don't use ``unpack()`` either. Here, you can simply use Python's double-star (``**``) operator for unpacking the parameters. Note that as Snakefiles are translated into Python for execution, the same rules as for using the `star and double-star unpacking Python operators `_ apply. These restrictions do not apply when using ``unpack()``. .. code-block:: python def myfunc1(): return ['foo.txt'] def myfunc2(): return {'foo': 'nowildcards.txt'} rule: input: *myfunc1(), **myfunc2(), output: "..." shell: "..." .. _snakefiles-version_tracking: Version Tracking ---------------- Rules can specify a version that is tracked by Snakemake together with the output files. When the version changes snakemake informs you when using the flag ``--summary`` or ``--list-version-changes``. The version can be specified by the version directive, which takes a string: .. code-block:: python rule: input: ... output: ... version: "1.0" shell: ... The version can of course also be filled with the output of a shell command, e.g.: .. code-block:: python SOMECOMMAND_VERSION = subprocess.check_output("somecommand --version", shell=True) rule: version: SOMECOMMAND_VERSION Alternatively, you might want to use file modification times in case of local scripts: .. code-block:: python SOMECOMMAND_VERSION = str(os.path.getmtime("path/to/somescript")) rule: version: SOMECOMMAND_VERSION A re-run can be automated by invoking Snakemake as follows: .. code-block:: console $ snakemake -R `snakemake --list-version-changes` With the availability of the ``conda`` directive (see :ref:`integrated_package_management`) the ``version`` directive has become **obsolete** in favor of defining isolated software environments that can be automatically deployed via the conda package manager. .. _snakefiles-code_tracking: Code Tracking ------------- Snakemake tracks the code that was used to create your files. In combination with ``--summary`` or ``--list-code-changes`` this can be used to see what files may need a re-run because the implementation changed. Re-run can be automated by invoking Snakemake as follows: .. code-block:: console $ snakemake -R `snakemake --list-code-changes` .. _snakefiles-job_lifetime_handlers: Onstart, onsuccess and onerror handlers --------------------------------------- Sometimes, it is necessary to specify code that shall be executed when the workflow execution is finished (e.g. cleanup, or notification of the user). With Snakemake 3.2.1, this is possible via the ``onsuccess`` and ``onerror`` keywords: .. code-block:: python onsuccess: print("Workflow finished, no error") onerror: print("An error occurred") shell("mail -s "an error occurred" youremail@provider.com < {log}") The ``onsuccess`` handler is executed if the workflow finished without error. Else, the ``onerror`` handler is executed. In both handlers, you have access to the variable ``log``, which contains the path to a logfile with the complete Snakemake output. Snakemake 3.6.0 adds an ````onstart```` handler, that will be executed before the workflow starts. Note that dry-runs do not trigger any of the handlers. Rule dependencies ----------------- From version 2.4.8 on, rules can also refer to the output of other rules in the Snakefile, e.g.: .. code-block:: python rule a: input: "path/to/input" output: "path/to/output" shell: ... rule b: input: rules.a.output output: "path/to/output/of/b" shell: ... Importantly, be aware that referring to rule a here requires that rule a was defined above rule b in the file, since the object has to be known already. This feature also allows to resolve dependencies that are ambiguous when using filenames. Note that when the rule you refer to defines multiple output files but you want to require only a subset of those as input for another rule, you should name the output files and refer to them specifically: .. code-block:: python rule a: input: "path/to/input" output: a = "path/to/output", b = "path/to/output2" shell: ... rule b: input: rules.a.output.a output: "path/to/output/of/b" shell: ... .. _snakefiles-ambiguous-rules: Handling Ambiguous Rules ------------------------ When two rules can produce the same output file, snakemake cannot decide per default which one to use. Hence an ``AmbiguousRuleException`` is thrown. Note: ruleorder is not intended to bring rules in the correct execution order (this is solely guided by the names of input and output files you use), it only helps snakemake to decide which rule to use when multiple ones can create the same output file! The proposed strategy to deal with such ambiguity is to provide a ``ruleorder`` for the conflicting rules, e.g. .. code-block:: python ruleorder: rule1 > rule2 > rule3 Here, ``rule1`` is preferred over ``rule2`` and ``rule3``, and ``rule2`` is preferred over ``rule3``. Only if rule1 and rule2 cannot be applied (e.g. due to missing input files), rule3 is used to produce the desired output file. Alternatively, rule dependencies (see above) can also resolve ambiguities. Another (quick and dirty) possiblity is to tell snakemake to allow ambiguity via a command line option .. code-block:: console $ snakemake --allow-ambiguity such that similar to GNU Make always the first matching rule is used. Here, a warning that summarizes the decision of snakemake is provided at the terminal. Local Rules ----------- When working in a cluster environment, not all rules need to become a job that has to be submitted (e.g. downloading some file, or a target-rule like `all`, see :ref:`snakefiles-targets`). The keyword `localrules` allows to mark a rule as local, so that it is not submitted to the cluster and instead executed on the host node: .. code-block:: python localrules: all, foo rule all: input: ... rule foo: ... rule bar: ... Here, only jobs from the rule ``bar`` will be submitted to the cluster, whereas all and foo will be run locally. Note that you can use the localrules directive **multiple times**. The result will be the union of all declarations. Benchmark Rules --------------- Since version 3.1, Snakemake provides support for benchmarking the run times of rules. This can be used to create complex performance analysis pipelines. With the `benchmark` keyword, a rule can be declared to store a benchmark of its code into the specified location. E.g. the rule .. code-block:: python rule benchmark_command: input: "path/to/input.{sample}.txt" output: "path/to/output.{sample}.txt" benchmark: "benchmarks/somecommand/{sample}.tsv" shell: "somecommand {input} {output}" benchmarks the CPU and wall clock time of the command ``somecommand`` for the given output and input files. For this, the shell or run body of the rule is executed on that data, and all run times are stored into the given benchmark tsv file (which will contain a tab-separated table of run times and memory usage in MiB). Per default, Snakemake executes the job once, generating one run time. However, the benchmark file can be annotated with the desired number of repeats, e.g., .. code-block:: python rule benchmark_command: input: "path/to/input.{sample}.txt" output: "path/to/output.{sample}.txt" benchmark: repeat("benchmarks/somecommand/{sample}.tsv", 3) shell: "somecommand {input} {output}" will instruct Snakemake to run each job of this rule three times and store all measurements in the benchmark file. The resulting tsv file can be used as input for other rules, just like any other output file. .. note:: Note that benchmarking is only possible in a reliable fashion for subprocesses (thus for tasks run through the ``shell``, ``script``, and ``wrapper`` directive). In the ``run`` block, the variable ``bench_record`` is available that you can pass to ``shell()`` as ``bench_record=bench_record``. When using ``shell(..., bench_record=bench_record)``, the maximum of all measurements of all ``shell()`` calls will be used but the running time of the rule execution including any Python code. .. _snakefiles-grouping: Defining groups for execution ----------------------------- From Snakemake 5.0 on, it is possible to assign rules to groups. Such groups will be executed together in **cluster** or **cloud mode**, as a so-called **group job**, i.e., all jobs of a particular group will be submitted at once, to the same computing node. By this, queueing and execution time can be saved, in particular if one or several short-running rules are involved. When executing locally, group definitions are ignored. Groups can be defined via the ``group`` keyword, e.g., .. code-block:: python samples = [1,2,3,4,5] rule all: input: "test.out" rule a: output: "a/{sample}.out" group: "mygroup" shell: "touch {output}" rule b: input: "a/{sample}.out" output: "b/{sample}.out" group: "mygroup" shell: "touch {output}" rule c: input: expand("b/{sample}.out", sample=samples) output: "test.out" shell: "touch {output}" Here, jobs from rule ``a`` and ``b`` end up in one group ``mygroup``, whereas jobs from rule ``c`` are executed separately. Note that Snakemake always determines a **connected subgraph** with the same group id to be a **group job**. Here, this means that, e.g., the jobs creating ``a/1.out`` and ``b/1.out`` will be in one group, and the jobs creating ``a/2.out`` and ``b/2.out`` will be in a separate group. However, if we would add ``group: "mygroup"`` to rule ``c``, all jobs would end up in a single group, including the one spawned from rule ``c``, because ``c`` connects all the other jobs. Piped output ------------ From Snakemake 5.0 on, it is possible to mark output files as pipes, via the ``pipe`` flag, e.g.: .. code-block:: python rule all: input: expand("test.{i}.out", i=range(2)) rule a: output: pipe("test.{i}.txt") shell: "for i in {{0..2}}; do echo {wildcards.i} >> {output}; done" rule b: input: "test.{i}.txt" output: "test.{i}.out" shell: "grep {wildcards.i} < {input} > {output}" If an output file is marked to be a pipe, then Snakemake will first create a `named pipe `_ with the given name and then execute the creating job simultaneously with the consuming job, inside a **group job** (see above). This works in all execution modes, local, cluster, and cloud. Naturally, a pipe output may only have a single consumer. It is possible to combine explicit group definition as above with pipe outputs. Thereby, pipe jobs can live within, or (automatically) extend existing groups. However, the two jobs connected by a pipe may not exist in conflicting groups. .. _snakefiles-checkpoints: Data-dependent conditional execution ------------------------------------ From Snakemake 5.4 on, conditional reevaluation of the DAG of jobs based on the content outputs is possible. The key idea is that rules can be declared as checkpoints, e.g., .. code-block:: python checkpoint somestep: input: "samples/{sample}.txt" output: "somestep/{sample}.txt" shell: "somecommand {input} > {output}" Snakemake allows to re-evaluate the DAG after the successful execution of every job spawned from a checkpoint. For this, every checkpoint is registered by its name in a globally available ``checkpoints`` object. The ``checkpoints`` object can be accessed by :ref:`input functions `. Assuming that the checkpoint is named ``somestep`` as above, the output files for a particular job can be retrieved with .. code-block:: python checkpoints.somestep.get(sample="a").output Thereby, the ``get`` method throws ``snakemake.exceptions.IncompleteCheckpointException`` if the checkpoint has not yet been executed for these particular wildcard value(s). Inside an input function, the exception will be automatically handled by Snakemake, and leads to a re-evaluation after the checkpoint has been successfully passed. To illustrate the possibilities of this mechanism, consider the following complete example: .. code-block:: python # a target rule to define the desired final output rule all: input: "aggregated/a.txt", "aggregated/b.txt" # the checkpoint that shall trigger re-evaluation of the DAG checkpoint somestep: input: "samples/{sample}.txt" output: "somestep/{sample}.txt" shell: # simulate some output value "echo {wildcards.sample} > somestep/{wildcards.sample}.txt" # intermediate rule rule intermediate: input: "somestep/{sample}.txt" output: "post/{sample}.txt" shell: "touch {output}" # alternative intermediate rule rule alt_intermediate: input: "somestep/{sample}.txt" output: "alt/{sample}.txt" shell: "touch {output}" # input function for the rule aggregate def aggregate_input(wildcards): # decision based on content of output file # Important: use the method open() of the returned file! # This way, Snakemake is able to automatically download the file if it is generated in # a cloud environment without a shared filesystem. with checkpoints.somestep.get(sample=wildcards.sample).output[0].open() as f: if f.read().strip() == "a": return "post/{sample}.txt" else: return "alt/{sample}.txt" rule aggregate: input: aggregate_input output: "aggregated/{sample}.txt" shell: "touch {output}" As can be seen, the rule aggregate uses an input function. Inside the function, we first retrieve the output files of the checkpoint ``somestep`` with the wildcards, passing through the value of the wildcard sample. Upon execution, if the checkpoint is not yet complete, Snakemake will record ``somestep`` as a direct dependency of the rule ``aggregate``. Once ``somestep`` has finished for a given sample, the input function will automatically be re-evaluated and the method ``get`` will no longer return an exception. Instead, the output file will be opened, and depending on its contents either ``"post/{sample}.txt"`` or ``"alt/{sample}.txt"`` will be returned by the input function. This way, the DAG becomes conditional on some produced data. It is also possible to use checkpoints for cases where the output files are unknown before execution. A typical example is a clustering process with an unknown number of clusters, where each cluster shall be saved into a separate file. Consider the following example: .. code-block:: python # a target rule to define the desired final output rule all: input: "aggregated/a.txt", "aggregated/b.txt" # the checkpoint that shall trigger re-evaluation of the DAG checkpoint clustering: input: "samples/{sample}.txt" output: clusters=directory("clustering/{sample}") shell: "mkdir clustering/{wildcards.sample}; " "for i in 1 2 3; do echo $i > clustering/{wildcards.sample}/$i.txt; done" # an intermediate rule rule intermediate: input: "clustering/{sample}/{i}.txt" output: "post/{sample}/{i}.txt" shell: "cp {input} {output}" def aggregate_input(wildcards): checkpoint_output = checkpoints.clustering.get(**wildcards).output[0] return expand("post/{sample}/{i}.txt", sample=wildcards.sample, i=glob_wildcards(os.path.join(checkpoint_output, "{i}.txt")).i) # an aggregation over all produced clusters rule aggregate: input: aggregate_input output: "aggregated/{sample}.txt" shell: "cat {input} > {output}" Here, our checkpoint simulates a clustering. We pretend that the number of clusters is unknown beforehand. Hence, the checkpoint only defines an output ``directory``. The rule ``aggregate`` again uses the ``checkpoints`` object to retrieve the output of the checkpoint. This time, instead of explicitly writing .. code-block:: python checkpoints.clustering.get(sample=wildcards.sample).output[0] we use the shorthand .. code-block:: python checkpoints.clustering.get(**wildcards).output[0] which automatically unpacks the wildcards as keyword arguments (this is standard python argument unpacking). If the checkpoint has not yet been executed, accessing ``checkpoints.clustering.get(**wildcards)`` ensure that Snakemake records the checkpoint as a direct dependency of the rule ``aggregate``. Upon completion of the checkpoint, the input function is re-evaluated, and the code beyond its first line is executed. Here, we retrieve the values of the wildcard ``i`` based on all files named ``{i}.txt`` in the output directory of the checkpoint. These values are then used to expand the pattern ``"post/{sample}/{i}.txt"``, such that the rule ``intermediate`` is executed for each of the determined clusters. This mechanism can be used to replace the use of the :ref:`dynamic-flag ` which will be deprecated in Snakemake 6.0. snakemake-5.10.0/docs/snakefiles/utils.rst000066400000000000000000000003061361131222100204710ustar00rootroot00000000000000.. _snakefiles-utils: ===== Utils ===== The module ``snakemake.utils`` provides a collection of helper functions for common tasks in Snakemake workflows. Details can be found in :ref:`utils-api`. snakemake-5.10.0/docs/snakefiles/writing_snakefiles.rst000066400000000000000000000037111361131222100232230ustar00rootroot00000000000000.. _user_manual-writing_snakefiles: ================= Writing Workflows ================= In Snakemake, workflows are specified as Snakefiles. Inspired by GNU Make, a Snakefile contains rules that denote how to create output files from input files. Dependencies between rules are handled implicitly, by matching filenames of input files against output files. Thereby wildcards can be used to write general rules. .. _snakefiles-grammar: ------- Grammar ------- The Snakefile syntax obeys the following grammar, given in extended Backus-Naur form (EBNF) .. code-block:: text snakemake = statement | rule | include | workdir rule = "rule" (identifier | "") ":" ruleparams include = "include:" stringliteral workdir = "workdir:" stringliteral ni = NEWLINE INDENT ruleparams = [ni input] [ni output] [ni params] [ni message] [ni threads] [ni (run | shell)] NEWLINE snakemake input = "input" ":" parameter_list output = "output" ":" parameter_list params = "params" ":" parameter_list log = "log" ":" parameter_list benchmark = "benchmark" ":" statement message = "message" ":" stringliteral threads = "threads" ":" integer resources = "resources" ":" parameter_list version = "version" ":" statement run = "run" ":" ni statement shell = "shell" ":" stringliteral while all not defined non-terminals map to their Python equivalents. .. _snakefiles-depend_version: Depend on a Minimum Snakemake Version ------------------------------------- From Snakemake 3.2 on, if your workflow depends on a minimum Snakemake version, you can easily ensure that at least this version is installed via .. code-block:: python from snakemake.utils import min_version min_version("3.2") given that your minimum required version of Snakemake is 3.2. The statement will raise a WorkflowError (and therefore abort the workflow execution) if the version is not met. snakemake-5.10.0/docs/tutorial/000077500000000000000000000000001361131222100163175ustar00rootroot00000000000000snakemake-5.10.0/docs/tutorial/additional_features.rst000066400000000000000000000303651361131222100230660ustar00rootroot00000000000000.. tutorial-additional_features: Additional features ------------------- .. _Snakemake: https://snakemake.readthedocs.io .. _Snakemake homepage: https://snakemake.readthedocs.io .. _GNU Make: https://www.gnu.org/software/make .. _Python: http://www.python.org .. _BWA: http://bio-bwa.sourceforge.net .. _SAMtools: http://www.htslib.org .. _BCFtools: http://www.htslib.org .. _Pandas: http://pandas.pydata.org .. _Miniconda: http://conda.pydata.org/miniconda.html .. _Conda: http://conda.pydata.org .. _Bash: http://www.tldp.org/LDP/Bash-Beginners-Guide/html .. _Atom: https://atom.io .. _Anaconda: https://anaconda.org .. _Graphviz: http://www.graphviz.org .. _RestructuredText: http://docutils.sourceforge.net/rst.html .. _data URI: https://developer.mozilla.org/en-US/docs/Web/HTTP/data_URIs .. _JSON: http://json.org .. _YAML: http://yaml.org .. _DRMAA: http://www.drmaa.org .. _rpy2: http://rpy.sourceforge.net .. _R: https://www.r-project.org .. _Rscript: https://stat.ethz.ch/R-manual/R-devel/library/utils/html/Rscript.html .. _PyYAML: http://pyyaml.org .. _Docutils: http://docutils.sourceforge.net .. _Bioconda: https://bioconda.github.io .. _Vagrant: https://www.vagrantup.com .. _Vagrant Documentation: https://docs.vagrantup.com .. _Blogpost: http://blog.osteel.me/posts/2015/01/25/how-to-use-vagrant-on-windows.html .. _slides: http://slides.com/johanneskoester/deck-1 In the following, we introduce some features that are beyond the scope of above example workflow. For details and even more features, see :ref:`user_manual-writing_snakefiles`, :ref:`project_info-faq` and the command line help (``snakemake --help``). Benchmarking :::::::::::: With the ``benchmark`` directive, Snakemake can be instructed to **measure the wall clock time of a job**. We activate benchmarking for the rule ``bwa_map``: .. code:: python rule bwa_map: input: "data/genome.fa", lambda wildcards: config["samples"][wildcards.sample] output: temp("mapped_reads/{sample}.bam") params: rg="@RG\tID:{sample}\tSM:{sample}" log: "logs/bwa_mem/{sample}.log" benchmark: "benchmarks/{sample}.bwa.benchmark.txt" threads: 8 shell: "(bwa mem -R '{params.rg}' -t {threads} {input} | " "samtools view -Sb - > {output}) 2> {log}" The ``benchmark`` directive takes a string that points to the file where benchmarking results shall be stored. Similar to output files, the path can contain wildcards (it must be the same wildcards as in the output files). When a job derived from the rule is executed, Snakemake will measure the wall clock time and memory usage (in MiB) and store it in the file in tab-delimited format. It is possible to repeat a benchmark multiple times in order to get a sense for the variability of the measurements. This can be done by annotating the benchmark file, e.g., with ``repeat("benchmarks/{sample}.bwa.benchmark.txt", 3)`` Snakemake can be told to run the job three times. The repeated measurements occur as subsequent lines in the tab-delimited benchmark file. Modularization :::::::::::::: In order to re-use building blocks or simply to structure large workflows, it is sometimes reasonable to **split a workflow into modules**. For this, Snakemake provides the ``include`` directive to include another Snakefile into the current one, e.g.: .. code:: python include: "path/to/other.snakefile" Alternatively, Snakemake allows to **define sub-workflows**. A sub-workflow refers to a working directory with a complete Snakemake workflow. Output files of that sub-workflow can be used in the current Snakefile. When executing, Snakemake ensures that the output files of the sub-workflow are up-to-date before executing the current workflow. This mechanism is particularly useful when you want to extend a previous analysis without modifying it. For details about sub-workflows, see the :ref:`documentation `. Exercise ........ * Put the read mapping related rules into a separate Snakefile and use the ``include`` directive to make them available in our example workflow again. .. _tutorial-conda: Automatic deployment of software dependencies ::::::::::::::::::::::::::::::::::::::::::::: In order to get a fully reproducible data analysis, it is not sufficient to be able to execute each step and document all used parameters. The used software tools and libraries have to be documented as well. In this tutorial, you have already seen how Conda_ can be used to specify an isolated software environment for a whole workflow. With Snakemake, you can go one step further and specify Conda environments per rule. This way, you can even make use of conflicting software versions (e.g. combine Python 2 with Python 3). In our example, instead of using an external environment we can specify environments per rule, e.g.: .. code:: python rule samtools_index: input: "sorted_reads/{sample}.bam" output: "sorted_reads/{sample}.bam.bai" conda: "envs/samtools.yaml" shell: "samtools index {input}" with ``envs/samtools.yaml`` defined as .. code:: yaml channels: - bioconda dependencies: - samtools =1.9 .. sidebar:: Note The conda directive does not work in combination with ``run`` blocks, because they have to share their Python environment with the surrounding snakefile. When Snakemake is executed with .. code:: console snakemake --use-conda it will automatically create required environments and activate them before a job is executed. It is best practice to specify at least the `major and minor version `_ of any packages in the environment definition. Specifying environments per rule in this way has two advantages. First, the workflow definition also documents all used software versions. Second, a workflow can be re-executed (without admin rights) on a vanilla system, without installing any prerequisites apart from Snakemake and Miniconda_. Tool wrappers ::::::::::::: In order to simplify the utilization of popular tools, Snakemake provides a repository of so-called wrappers (the `Snakemake wrapper repository `_). A wrapper is a short script that wraps (typically) a command line application and makes it directly addressable from within Snakemake. For this, Snakemake provides the ``wrapper`` directive that can be used instead of ``shell``, ``script``, or ``run``. For example, the rule ``bwa_map`` could alternatively look like this: .. code:: python rule bwa_mem: input: ref="data/genome.fa", sample=lambda wildcards: config["samples"][wildcards.sample] output: temp("mapped_reads/{sample}.bam") log: "logs/bwa_mem/{sample}.log" params: "-R '@RG\tID:{sample}\tSM:{sample}'" threads: 8 wrapper: "0.15.3/bio/bwa/mem" .. sidebar:: Note Updates to the Snakemake wrapper repository are automatically tested via `continuous integration `_. The wrapper directive expects a (partial) URL that points to a wrapper in the repository. These can be looked up in the corresponding `database `_. The first part of the URL is a Git version tag. Upon invocation, Snakemake will automatically download the requested version of the wrapper. Furthermore, in combination with ``--use-conda`` (see :ref:`tutorial-conda`), the required software will be automatically deployed before execution. Cluster execution ::::::::::::::::: By default, Snakemake executes jobs on the local machine it is invoked on. Alternatively, it can execute jobs in **distributed environments, e.g., compute clusters or batch systems**. If the nodes share a common file system, Snakemake supports three alternative execution modes. In cluster environments, compute jobs are usually submitted as shell scripts via commands like ``qsub``. Snakemake provides a **generic mode** to execute on such clusters. By invoking Snakemake with .. code:: console $ snakemake --cluster qsub --jobs 100 each job will be compiled into a shell script that is submitted with the given command (here ``qsub``). The ``--jobs`` flag limits the number of concurrently submitted jobs to 100. This basic mode assumes that the submission command returns immediately after submitting the job. Some clusters allow to run the submission command in **synchronous mode**, such that it waits until the job has been executed. In such cases, we can invoke e.g. .. code:: console $ snakemake --cluster-sync "qsub -sync yes" --jobs 100 The specified submission command can also be **decorated with additional parameters taken from the submitted job**. For example, the number of used threads can be accessed in braces similarly to the formatting of shell commands, e.g. .. code:: console $ snakemake --cluster "qsub -pe threaded {threads}" --jobs 100 Alternatively, Snakemake can use the Distributed Resource Management Application API (DRMAA_). This API provides a common interface to control various resource management systems. The **DRMAA support** can be activated by invoking Snakemake as follows: .. code:: console $ snakemake --drmaa --jobs 100 If available, **DRMAA is preferable over the generic cluster modes** because it provides better control and error handling. To support additional cluster specific parametrization, a Snakefile can be complemented by a :ref:`snakefiles-cluster_configuration` file. Using --cluster-status :::::::::::::::::::::: Sometimes you need specific detection to determine if a cluster job completed successfully, failed or is still running. Error detection with ``--cluster`` can be improved for edge cases such as timeouts and jobs exceeding memory that are silently terminated by the queueing system. This can be achieved with the ``--cluster-status`` option. This takes as input a script and passes a job id as first argument. The following (simplified) script detects the job status on a given SLURM cluster (>= 14.03.0rc1 is required for ``--parsable``). .. code:: python #!/usr/bin/env python import subprocess import sys jobid = sys.argv[1] output = str(subprocess.check_output("sacct -j %s --format State --noheader | head -1 | awk '{print $1}'" % jobid, shell=True).strip()) running_status=["PENDING", "CONFIGURING", "COMPLETING", "RUNNING", "SUSPENDED"] if "COMPLETED" in output: print("success") elif any(r in output for r in running_status): print("running") else: print("failed") To use this script call snakemake similar to below, where ``status.py`` is the script above. .. code:: console $ snakemake all --cluster "sbatch --cpus-per-task=1 --parsable" --cluster-status ./status.py Constraining wildcards :::::::::::::::::::::: Snakemake uses regular expressions to match output files to input files and determine dependencies between the jobs. Sometimes it is useful to constrain the values a wildcard can have. This can be achieved by adding a regular expression that describes the set of allowed wildcard values. For example, the wildcard ``sample`` in the output file ``"sorted_reads/{sample}.bam"`` can be constrained to only allow alphanumeric sample names as ``"sorted_reads/{sample,[A-Za-z0-9]+}.bam"``. Constraints may be defined per rule or globally using the ``wildcard_constraints`` keyword, as demonstrated in :ref:`snakefiles-wildcards`. This mechanism helps to solve two kinds of ambiguity. * It can help to avoid ambiguous rules, i.e. two or more rules that can be applied to generate the same output file. Other ways of handling ambiguous rules are described in the Section :ref:`snakefiles-ambiguous-rules`. * It can help to guide the regular expression based matching so that wildcards are assigned to the right parts of a file name. Consider the output file ``{sample}.{group}.txt`` and assume that the target file is ``A.1.normal.txt``. It is not clear whether ``dataset="A.1"`` and ``group="normal"`` or ``dataset="A"`` and ``group="1.normal"`` is the right assignment. Here, constraining the dataset wildcard by ``{sample,[A-Z]+}.{group}`` solves the problem. When dealing with ambiguous rules, it is best practice to first try to solve the ambiguity by using a proper file structure, for example, by separating the output files of different steps in different directories. snakemake-5.10.0/docs/tutorial/advanced.rst000066400000000000000000000373521361131222100206300ustar00rootroot00000000000000.. tutorial-advanced: Advanced: Decorating the example workflow ----------------------------------------- .. _Snakemake: https://snakemake.readthedocs.io .. _Snakemake homepage: https://snakemake.readthedocs.io .. _GNU Make: https://www.gnu.org/software/make .. _Python: http://www.python.org .. _BWA: http://bio-bwa.sourceforge.net .. _SAMtools: http://www.htslib.org .. _BCFtools: http://www.htslib.org .. _Pandas: http://pandas.pydata.org .. _Miniconda: http://conda.pydata.org/miniconda.html .. _Conda: http://conda.pydata.org .. _Bash: http://www.tldp.org/LDP/Bash-Beginners-Guide/html .. _Atom: https://atom.io .. _Anaconda: https://anaconda.org .. _Graphviz: http://www.graphviz.org .. _RestructuredText: http://docutils.sourceforge.net/rst.html .. _data URI: https://developer.mozilla.org/en-US/docs/Web/HTTP/data_URIs .. _JSON: http://json.org .. _YAML: http://yaml.org .. _DRMAA: http://www.drmaa.org .. _rpy2: http://rpy.sourceforge.net .. _R: https://www.r-project.org .. _Rscript: https://stat.ethz.ch/R-manual/R-devel/library/utils/html/Rscript.html .. _PyYAML: http://pyyaml.org .. _Docutils: http://docutils.sourceforge.net .. _Bioconda: https://bioconda.github.io .. _Vagrant: https://www.vagrantup.com .. _Vagrant Documentation: https://docs.vagrantup.com .. _Blogpost: http://blog.osteel.me/posts/2015/01/25/how-to-use-vagrant-on-windows.html .. _slides: http://slides.com/johanneskoester/deck-1 Now that the basic concepts of Snakemake have been illustrated, we can introduce advanced topics. Step 1: Specifying the number of used threads ::::::::::::::::::::::::::::::::::::::::::::: For some tools, it is advisable to use more than one thread in order to speed up the computation. **Snakemake can be made aware of the threads a rule needs** with the ``threads`` directive. In our example workflow, it makes sense to use multiple threads for the rule ``bwa_map``: .. code:: python rule bwa_map: input: "data/genome.fa", "data/samples/{sample}.fastq" output: "mapped_reads/{sample}.bam" threads: 8 shell: "bwa mem -t {threads} {input} | samtools view -Sb - > {output}" The number of threads can be propagated to the shell command with the familiar braces notation (i.e. ``{threads}``). If no ``threads`` directive is given, a rule is assumed to need 1 thread. When a workflow is executed, **the number of threads the jobs need is considered by the Snakemake scheduler**. In particular, the scheduler ensures that the sum of the threads of all running jobs does not exceed a given number of available CPU cores. This number can be given with the ``--cores`` command line argument (per default, Snakemake uses only 1 CPU core). For example .. code:: console $ snakemake --cores 10 .. sidebar:: Note Apart from the very common thread resource, Snakemake provides a ``resources`` directive that can be used to **specify arbitrary resources**, e.g., memory usage or auxiliary computing devices like GPUs. Similar to threads, these can be considered by the scheduler when an available amount of that resource is given with the command line argument ``--resources`` (see :ref:`snakefiles-resources`). would execute the workflow with 10 cores. Since the rule ``bwa_map`` needs 8 threads, only one job of the rule can run at a time, and the Snakemake scheduler will try to saturate the remaining cores with other jobs like, e.g., ``samtools_sort``. The threads directive in a rule is interpreted as a maximum: when **less cores than threads** are provided, the number of threads a rule uses will be **reduced to the number of given cores**. Exercise ........ * With the flag ``--forceall`` you can enforce a complete re-execution of the workflow. Combine this flag with different values for ``--cores`` and examine how the scheduler selects jobs to run in parallel. Step 2: Config files :::::::::::::::::::: So far, we specified the samples to consider in a Python list within the Snakefile. However, often you want your workflow to be customizable, so that it can be easily adapted to new data. For this purpose, Snakemake provides a config file mechanism. Config files can be written in JSON_ or YAML_, and loaded with the ``configfile`` directive. In our example workflow, we add the line .. code:: python configfile: "config.yaml" to the top of the Snakefile. Snakemake will load the config file and store its contents into a globally available dictionary named ``config``. In our case, it makes sense to specify the samples in ``config.yaml`` as .. code:: yaml samples: A: data/samples/A.fastq B: data/samples/B.fastq Now, we can remove the statement defining ``SAMPLES`` from the Snakefile and change the rule ``bcftools_call`` to .. code:: python rule bcftools_call: input: fa="data/genome.fa", bam=expand("sorted_reads/{sample}.bam", sample=config["samples"]), bai=expand("sorted_reads/{sample}.bam.bai", sample=config["samples"]) output: "calls/all.vcf" shell: "samtools mpileup -g -f {input.fa} {input.bam} | " "bcftools call -mv - > {output}" .. _tutorial-input_functions: Step 3: Input functions ::::::::::::::::::::::: Since we have stored the path to the FASTQ files in the config file, we can also generalize the rule ``bwa_map`` to use these paths. This case is different to the rule ``bcftools_call`` we modified above. To understand this, it is important to know that Snakemake workflows are executed in three phases. * In the **initialization** phase, the workflow is parsed and all rules are instantiated. * In the **DAG** phase, the DAG of jobs is built by filling wildcards and matching input files to output files. * In the **scheduling** phase, the DAG of jobs is executed. The expand functions in the list of input files of the rule ``bcftools_call`` are executed during the initialization phase. In this phase, we don't know about jobs, wildcard values and rule dependencies. Hence, we cannot determine the FASTQ paths for rule ``bwa_map`` from the config file in this phase, because we don't even know which jobs will be generated from that rule. Instead, we need to defer the determination of input files to the DAG phase. This can be achieved by specifying an **input function** instead of a string as inside of the input directive. For the rule ``bwa_map`` this works as follows: .. code:: python rule bwa_map: input: "data/genome.fa", lambda wildcards: config["samples"][wildcards.sample] output: "mapped_reads/{sample}.bam" threads: 8 shell: "bwa mem -t {threads} {input} | samtools view -Sb - > {output}" .. sidebar:: Note Snakemake does not automatically rerun jobs when new input files are added as in the excercise below. However, you can get a list of output files that are affected by such changes with ``snakemake --list-input-changes``. To trigger a rerun, some bash magic helps: .. code:: console snakemake -n --forcerun $(snakemake --list-input-changes) Here, we use an anonymous function, also called `lambda expression `_. Any normal function would work as well. Input functions take as **single argument** a ``wildcards`` object, that allows to access the wildcards values via attributes (here ``wildcards.sample``). They have to **return a string or a list of strings**, that are interpreted as paths to input files (here, we return the path that is stored for the sample in the config file). Input functions are evaluated once the wildcard values of a job are determined. Exercise ........ * In the ``data/samples`` folder, there is an additional sample ``C.fastq``. Add that sample to the config file and see how Snakemake wants to recompute the part of the workflow belonging to the new sample, when invoking with ``snakemake -n --reason --forcerun bcftools_call``. Step 4: Rule parameters ::::::::::::::::::::::: Sometimes, shell commands are not only composed of input and output files and some static flags. In particular, it can happen that additional parameters need to be set depending on the wildcard values of the job. For this, Snakemake allows to **define arbitrary parameters** for rules with the ``params`` directive. In our workflow, it is reasonable to annotate aligned reads with so-called read groups, that contain metadata like the sample name. We modify the rule ``bwa_map`` accordingly: .. code:: python rule bwa_map: input: "data/genome.fa", lambda wildcards: config["samples"][wildcards.sample] output: "mapped_reads/{sample}.bam" params: rg=r"@RG\tID:{sample}\tSM:{sample}" threads: 8 shell: "bwa mem -R '{params.rg}' -t {threads} {input} | samtools view -Sb - > {output}" .. sidebar:: Note The ``params`` directive can also take functions like in Step 3 to defer initialization to the DAG phase. In contrast to input functions, these can optionally take additional arguments ``input``, ``output``, ``threads``, and ``resources``. Similar to input and output files, ``params`` can be accessed from the shell command the Python based ``run`` block, or the script directive (see :ref:`tutorial-script`). Exercise ........ * Variant calling can consider a lot of parameters. A particularly important one is the prior mutation rate (1e-3 per default). It is set via the flag ``-P`` of the ``bcftools call`` command. Consider making this flag configurable via adding a new key to the config file and using the ``params`` directive in the rule ``bcftools_call`` to propagate it to the shell command. Step 5: Logging ::::::::::::::: When executing a large workflow, it is usually desirable to store the output of each job persistently in files instead of just printing it to the terminal. For this purpose, Snakemake allows to **specify log files** for rules. Log files are defined via the ``log`` directive and handled similarly to output files, but they are not subject of rule matching and are not cleaned up when a job fails. We modify our rule ``bwa_map`` as follows: .. code:: python rule bwa_map: input: "data/genome.fa", lambda wildcards: config["samples"][wildcards.sample] output: "mapped_reads/{sample}.bam" params: rg=r"@RG\tID:{sample}\tSM:{sample}" log: "logs/bwa_mem/{sample}.log" threads: 8 shell: "(bwa mem -R '{params.rg}' -t {threads} {input} | " "samtools view -Sb - > {output}) 2> {log}" .. sidebar:: Note It is best practice to store all log files in a subdirectory ``logs/``, prefixed by the rule or tool name. The shell command is modified to collect STDERR output of both ``bwa`` and ``samtools`` and pipe it into the file referred by ``{log}``. Log files must contain exactly the same wildcards as the output files to avoid clashes. Exercise ........ * Add a log directive to the ``bcftools_call`` rule as well. * Time to re-run the whole workflow (remember the command line flags to force re-execution). See how log files are created for variant calling and read mapping. * The ability to track the provenance of each generated result is an important step towards reproducible analyses. Apart from the ``report`` functionality discussed before, Snakemake can summarize various provenance information for all output files of the workflow. The flag ``--summary`` prints a table associating each output file with the rule used to generate it, the creation date and optionally the version of the tool used for creation is provided. Further, the table informs about updated input files and changes to the source code of the rule after creation of the output file. Invoke Snakemake with ``--summary`` to examine the information for our example. .. _tutorial_temp-and-protected-files: Step 6: Temporary and protected files ::::::::::::::::::::::::::::::::::::: In our workflow, we create two BAM files for each sample, namely the output of the rules ``bwa_map`` and ``samtools_sort``. When not dealing with examples, the underlying data is usually huge. Hence, the resulting BAM files need a lot of disk space and their creation takes some time. Snakemake allows to **mark output files as temporary**, such that they are deleted once every consuming job has been executed, in order to save disk space. We use this mechanism for the output file of the rule ``bwa_map``: .. code:: python rule bwa_map: input: "data/genome.fa", lambda wildcards: config["samples"][wildcards.sample] output: temp("mapped_reads/{sample}.bam") params: rg=r"@RG\tID:{sample}\tSM:{sample}" log: "logs/bwa_mem/{sample}.log" threads: 8 shell: "(bwa mem -R '{params.rg}' -t {threads} {input} | " "samtools view -Sb - > {output}) 2> {log}" This results in the deletion of the BAM file once the corresponding ``samtools_sort`` job has been executed. Since the creation of BAM files via read mapping and sorting is computationally expensive, it is reasonable to **protect** the final BAM file **from accidental deletion or modification**. We modify the rule ``samtools_sort`` by marking its output file as ``protected``: .. code:: python rule samtools_sort: input: "mapped_reads/{sample}.bam" output: protected("sorted_reads/{sample}.bam") shell: "samtools sort -T sorted_reads/{wildcards.sample} " "-O bam {input} > {output}" After execution of the job, Snakemake will write-protect the output file in the filesystem, so that it can't be overwritten or deleted accidentally. Exercise ........ * Re-execute the whole workflow and observe how Snakemake handles the temporary and protected files. * Run Snakemake with the target ``mapped_reads/A.bam``. Although the file is marked as temporary, you will see that Snakemake does not delete it because it is specified as a target file. * Try to re-execute the whole workflow again with the dry-run option. You will see that it fails (as intended) because Snakemake cannot overwrite the protected output files. Summary ::::::: The final version of our workflow looks like this: .. code:: python configfile: "config.yaml" rule all: input: "plots/quals.svg" rule bwa_map: input: "data/genome.fa", lambda wildcards: config["samples"][wildcards.sample] output: temp("mapped_reads/{sample}.bam") params: rg=r"@RG\tID:{sample}\tSM:{sample}" log: "logs/bwa_mem/{sample}.log" threads: 8 shell: "(bwa mem -R '{params.rg}' -t {threads} {input} | " "samtools view -Sb - > {output}) 2> {log}" rule samtools_sort: input: "mapped_reads/{sample}.bam" output: protected("sorted_reads/{sample}.bam") shell: "samtools sort -T sorted_reads/{wildcards.sample} " "-O bam {input} > {output}" rule samtools_index: input: "sorted_reads/{sample}.bam" output: "sorted_reads/{sample}.bam.bai" shell: "samtools index {input}" rule bcftools_call: input: fa="data/genome.fa", bam=expand("sorted_reads/{sample}.bam", sample=config["samples"]), bai=expand("sorted_reads/{sample}.bam.bai", sample=config["samples"]) output: "calls/all.vcf" shell: "samtools mpileup -g -f {input.fa} {input.bam} | " "bcftools call -mv - > {output}" rule plot_quals: input: "calls/all.vcf" output: "plots/quals.svg" script: "scripts/plot-quals.py" snakemake-5.10.0/docs/tutorial/basics.rst000066400000000000000000000555631361131222100203330ustar00rootroot00000000000000.. _tutorial-basics: Basics: An example workflow --------------------------- .. _Snakemake: https://snakemake.readthedocs.io .. _Snakemake homepage: https://snakemake.readthedocs.io .. _GNU Make: https://www.gnu.org/software/make .. _Python: http://www.python.org .. _BWA: http://bio-bwa.sourceforge.net .. _SAMtools: http://www.htslib.org .. _BCFtools: http://www.htslib.org .. _Pandas: http://pandas.pydata.org .. _Miniconda: http://conda.pydata.org/miniconda.html .. _Conda: http://conda.pydata.org .. _Bash: http://www.tldp.org/LDP/Bash-Beginners-Guide/html .. _Atom: https://atom.io .. _Anaconda: https://anaconda.org .. _Graphviz: http://www.graphviz.org .. _RestructuredText: http://docutils.sourceforge.net/rst.html .. _data URI: https://developer.mozilla.org/en-US/docs/Web/HTTP/data_URIs .. _JSON: http://json.org .. _YAML: http://yaml.org .. _DRMAA: http://www.drmaa.org .. _rpy2: http://rpy.sourceforge.net .. _R: https://www.r-project.org .. _Rscript: https://stat.ethz.ch/R-manual/R-devel/library/utils/html/Rscript.html .. _PyYAML: http://pyyaml.org .. _Docutils: http://docutils.sourceforge.net .. _Bioconda: https://bioconda.github.io .. _Vagrant: https://www.vagrantup.com .. _Vagrant Documentation: https://docs.vagrantup.com .. _Blogpost: http://blog.osteel.me/posts/2015/01/25/how-to-use-vagrant-on-windows.html .. _slides: http://slides.com/johanneskoester/deck-1 Please make sure that you have **activated** the environment we created before, and that you have an open terminal in the working directory you have created. **A Snakemake workflow is defined by specifying rules in a Snakefile**. **Rules decompose the workflow into small steps** (e.g., the application of a single tool) by specifying how to create sets of **output files** from sets of **input files**. Snakemake automatically **determines the dependencies** between the rules by matching file names. The Snakemake language extends the Python language, adding syntactic structures for rule definition and additional controls. All added syntactic structures begin with a keyword followed by a code block that is either in the same line or indented and consisting of multiple lines. The resulting syntax resembles that of original Python constructs. In the following, we will introduce the Snakemake syntax by creating an example workflow. The workflow comes from the domain of genome analysis. It maps sequencing reads to a reference genome and call variants on the mapped reads. The tutorial does not require you to know what this is about. Nevertheless, we provide some background in the following paragraph. .. _tutorial-background: Background :::::::::: The genome of a living organism encodes its hereditary information. It serves as a blueprint for proteins, which form living cells, carry information and drive chemical reactions. Differences between populations, species, cancer cells and healthy tissue, as well as syndromes or diseases can be reflected and sometimes caused by changes in the genome. This makes the genome a major target of biological and medical research. Today, it is often analyzed with DNA sequencing, producing gigabytes of data from a single biological sample (e.g. a biopsy of some tissue). For technical reasons, DNA sequencing cuts the DNA of a sample into millions of small pieces, called **reads**. In order to recover the genome of the sample, one has to map these reads against a known **reference genome** (e.g., the human one obtained during the famous `human genome project `_). This task is called **read mapping**. Often, it is of interest where an individual genome is different from the species-wide consensus represented with the reference genome. Such differences are called **variants**. They are responsible for harmless individual differences (like eye color), but can also cause diseases like cancer. By investigating the differences between the all mapped reads and the reference sequence at one position, variants can be detected. This is a statistical challenge, because they have to be distinguished from artifacts generated by the sequencing process. Step 1: Mapping reads ::::::::::::::::::::: Our first Snakemake rule maps reads of a given sample to a given reference genome (see :ref:`tutorial-background`). For this, we will use the tool bwa_, specifically the subcommand ``bwa mem``. In the working directory, **create a new file** called ``Snakefile`` with an editor of your choice. We propose to use the Atom_ editor, since it provides out-of-the-box syntax highlighting for Snakemake. In the Snakefile, define the following rule: .. code:: python rule bwa_map: input: "data/genome.fa", "data/samples/A.fastq" output: "mapped_reads/A.bam" shell: "bwa mem {input} | samtools view -Sb - > {output}" .. sidebar:: Note A common error is to forget the comma between the input or output items. Since Python concatenates subsequent strings, this can lead to unexpected behavior. A Snakemake rule has a name (here ``bwa_map``) and a number of directives, here ``input``, ``output`` and ``shell``. The ``input`` and ``output`` directives are followed by lists of files that are expected to be used or created by the rule. In the simplest case, these are just explicit Python strings. The ``shell`` directive is followed by a Python string containing the shell command to execute. In the shell command string, we can refer to elements of the rule via braces notation (similar to the Python format function). Here, we refer to the output file by specifying ``{output}`` and to the input files by specifying ``{input}``. Since the rule has multiple input files, Snakemake will concatenate them separated by a whitespace. In other words, Snakemake will replace ``{input}`` with ``data/genome.fa data/samples/A.fastq`` before executing the command. The shell command invokes ``bwa mem`` with reference genome and reads, and pipes the output into ``samtools`` which creates a compressed `BAM `_ file containing the alignments. The output of ``samtools`` is piped into the output file defined by the rule. When a workflow is executed, Snakemake tries to generate given **target** files. Target files can be specified via the command line. By executing .. code:: console $ snakemake -np mapped_reads/A.bam in the working directory containing the Snakefile, we tell Snakemake to generate the target file ``mapped_reads/A.bam``. Since we used the ``-n`` (or ``--dry-run``) flag, Snakemake will only show the execution plan instead of actually perform the steps. The ``-p`` flag instructs Snakemake to also print the resulting shell command for illustration. To generate the target files, **Snakemake applies the rules given in the Snakefile in a top-down way**. The application of a rule to generate a set of output files is called **job**. For each input file of a job, Snakemake again (i.e. recursively) determines rules that can be applied to generate it. This yields a `directed acyclic graph (DAG) `_ of jobs where the edges represent dependencies. So far, we only have a single rule, and the DAG of jobs consists of a single node. Nevertheless, we can **execute our workflow** with .. code:: console $ snakemake mapped_reads/A.bam Note that, after completion of above command, Snakemake will not try to create ``mapped_reads/A.bam`` again, because it is already present in the file system. Snakemake **only re-runs jobs if one of the input files is newer than one of the output files or one of the input files will be updated by another job**. Step 2: Generalizing the read mapping rule :::::::::::::::::::::::::::::::::::::::::: Obviously, the rule will only work for a single sample with reads in the file ``data/samples/A.fastq``. However, Snakemake allows to **generalize rules by using named wildcards**. Simply replace the ``A`` in the second input file and in the output file with the wildcard ``{sample}``, leading to .. code:: python rule bwa_map: input: "data/genome.fa", "data/samples/{sample}.fastq" output: "mapped_reads/{sample}.bam" shell: "bwa mem {input} | samtools view -Sb - > {output}" .. sidebar:: Note Note that if a rule has multiple output files, Snakemake requires them to all have exactly the same wildcards. Otherwise, it could happen that two jobs from the same rule want to write the same file. When Snakemake determines that this rule can be applied to generate a target file by replacing the wildcard ``{sample}`` in the output file with an appropriate value, it will propagate that value to all occurrences of ``{sample}`` in the input files and thereby determine the necessary input for the resulting job. Note that you can have multiple wildcards in your file paths, however, to avoid conflicts with other jobs of the same rule, **all output files** of a rule have to **contain exactly the same wildcards**. When executing .. code:: console $ snakemake -np mapped_reads/B.bam Snakemake will determine that the rule ``bwa_map`` can be applied to generate the target file by replacing the wildcard ``{sample}`` with the value ``B``. In the output of the dry-run, you will see how the wildcard value is propagated to the input files and all filenames in the shell command. You can also **specify multiple targets**, e.g.: .. code:: console $ snakemake -np mapped_reads/A.bam mapped_reads/B.bam Some Bash_ magic can make this particularly handy. For example, you can alternatively compose our multiple targets in a single pass via .. code:: console $ snakemake -np mapped_reads/{A,B}.bam Note that this is not a special Snakemake syntax. Bash is just expanding the given path into two, one for each element of the set ``{A,B}``. In both cases, you will see that Snakemake only proposes to create the output file ``mapped_reads/B.bam``. This is because you already executed the workflow before (see the previous step) and no input file is newer than the output file ``mapped_reads/A.bam``. You can update the file modification date of the input file ``data/samples/A.fastq`` via .. code:: console $ touch data/samples/A.fastq and see how Snakemake wants to re-run the job to create the file ``mapped_reads/A.bam`` by executing .. code:: console $ snakemake -np mapped_reads/A.bam mapped_reads/B.bam Step 3: Sorting read alignments ::::::::::::::::::::::::::::::: For later steps, we need the read alignments in the BAM files to be sorted. This can be achieved with the samtools_ command. We add the following rule beneath the ``bwa_map`` rule: .. code:: python rule samtools_sort: input: "mapped_reads/{sample}.bam" output: "sorted_reads/{sample}.bam" shell: "samtools sort -T sorted_reads/{wildcards.sample} " "-O bam {input} > {output}" .. sidebar:: Note It is best practice to have subsequent steps of a workflow in separate, unique, output folders. This keeps the working directory structured. Further, such unique prefixes allow Snakemake to prune the search space for dependencies. This rule will take the input file from the ``mapped_reads`` directory and store a sorted version in the ``sorted_reads`` directory. Note that Snakemake **automatically creates missing directories** before jobs are executed. For sorting, ``samtools`` requires a prefix specified with the flag ``-T``. Here, we need the value of the wildcard ``sample``. Snakemake allows to access wildcards in the shell command via the ``wildcards`` object that has an attribute with the value for each wildcard. When issuing .. code:: console $ snakemake -np sorted_reads/B.bam you will see how Snakemake wants to run first the rule ``bwa_map`` and then the rule ``samtools_sort`` to create the desired target file: as mentioned before, the dependencies are resolved automatically by matching file names. Step 4: Indexing read alignments and visualizing the DAG of jobs :::::::::::::::::::::::::::::::::::::::::::::::::::::::::::::::: Next, we need to use samtools_ again to index the sorted read alignments for random access. This can be done with the following rule: .. code:: python rule samtools_index: input: "sorted_reads/{sample}.bam" output: "sorted_reads/{sample}.bam.bai" shell: "samtools index {input}" .. sidebar:: Note Snakemake uses the Python format mini language to format shell commands. Sometimes you have to use braces for something else in a shell command. In that case, you have to escape them by doubling, e.g., ``ls {{A,B}}.txt``. Having three steps already, it is a good time to take a closer look at the resulting DAG of jobs. By executing .. code:: console $ snakemake --dag sorted_reads/{A,B}.bam.bai | dot -Tsvg > dag.svg we create a **visualization of the DAG** using the ``dot`` command provided by Graphviz_. For the given target files, Snakemake specifies the DAG in the dot language and pipes it into the ``dot`` command, which renders the definition into SVG format. The rendered DAG is piped into the file ``dag.svg`` and will look similar to this: .. image:: workflow/dag_index.png :align: center The DAG contains a node for each job and edges representing the dependencies. Jobs that don't need to be run because their output is up-to-date are dashed. For rules with wildcards, the value of the wildcard for the particular job is displayed in the job node. Exercise ........ * Run parts of the workflow using different targets. Recreate the DAG and see how different rules become dashed because their output is present and up-to-date. Step 5: Calling genomic variants :::::::::::::::::::::::::::::::: The next step in our workflow will aggregate the mapped reads from all samples and jointly call genomic variants on them (see :ref:`tutorial-background`). For the variant calling, we will combine the two utilities samtools_ and bcftools_. Snakemake provides a **helper function for collecting input files** that helps us to describe the aggregation in this step. With .. code:: python expand("sorted_reads/{sample}.bam", sample=SAMPLES) we obtain a list of files where the given pattern ``"sorted_reads/{sample}.bam"`` was formatted with the values in a given list of samples ``SAMPLES``, i.e. .. code:: python ["sorted_reads/A.bam", "sorted_reads/B.bam"] The function is particularly useful when the pattern contains multiple wildcards. For example, .. code:: python expand("sorted_reads/{sample}.{replicate}.bam", sample=SAMPLES, replicate=[0, 1]) would create the product of all elements of ``SAMPLES`` and the list ``[0, 1]``, yielding .. code:: python ["sorted_reads/A.0.bam", "sorted_reads/A.1.bam", "sorted_reads/B.0.bam", "sorted_reads/B.1.bam"] Here, we use only the simple case of ``expand``. We first let Snakemake know which samples we want to consider. Remember that Snakemake works top-down, it does not automatically infer this from, e.g., the fastq files in the data folder. Also remember that Snakefiles are in principle Python code enhanced by some declarative statements to define workflows. Hence, we can define the list of samples ad-hoc in plain Python at the top of the Snakefile: .. code:: python SAMPLES = ["A", "B"] Later, we will learn about more sophisticated ways like **config files**. Now, we can add the following rule to our Snakefile: .. code:: python rule bcftools_call: input: fa="data/genome.fa", bam=expand("sorted_reads/{sample}.bam", sample=SAMPLES), bai=expand("sorted_reads/{sample}.bam.bai", sample=SAMPLES) output: "calls/all.vcf" shell: "samtools mpileup -g -f {input.fa} {input.bam} | " "bcftools call -mv - > {output}" .. sidebar:: Note If you name input or output files like above, their order won't be preserved when referring them as ``{input}``. Further, note that named and not named (i.e., positional) input and output files can be combined, but the positional ones must come first, equivalent to Python functions with keyword arguments. With multiple input or output files, it is sometimes handy to refer them separately in the shell command. This can be done by **specifying names for input or output files** (here, e.g., ``fa=...``). The files can then be referred in the shell command via, e.g., ``{input.fa}``. For **long shell commands** like this one, it is advisable to **split the string over multiple indented lines**. Python will automatically merge it into one. Further, you will notice that the **input or output file lists can contain arbitrary Python statements**, as long as it returns a string, or a list of strings. Here, we invoke our ``expand`` function to aggregate over the aligned reads of all samples. Exercise ........ * obtain the updated DAG of jobs for the target file ``calls/all.vcf``, it should look like this: .. image:: workflow/dag_call.png :align: center .. _tutorial-script: Step 6: Using custom scripts :::::::::::::::::::::::::::: Usually, a workflow not only consists of invoking various tools, but also contains custom code to e.g. calculate summary statistics or create plots. While Snakemake also allows you to directly :ref:`write Python code inside a rule <.. _snakefiles-rules>`_, it is usually reasonable to move such logic into separate scripts. For this purpose, Snakemake offers the ``script`` directive. Add the following rule to your Snakefile: .. code:: python rule plot_quals: input: "calls/all.vcf" output: "plots/quals.svg" script: "scripts/plot-quals.py" This rule shall generate a histogram of the quality scores that have been assigned to the variant calls in the file ``calls/all.vcf``. The actual Python code to generate the plot is hidden in the script ``scripts/plot-quals.py``. Script paths are always relative to the referring Snakefile. In the script, all properties of the rule like ``input``, ``output``, ``wildcards``, etc. are available as attributes of a global ``snakemake`` object. Create the file ``scripts/plot-quals.py``, with the following content: .. code:: python import matplotlib matplotlib.use("Agg") import matplotlib.pyplot as plt from pysam import VariantFile quals = [record.qual for record in VariantFile(snakemake.input[0])] plt.hist(quals) plt.savefig(snakemake.output[0]) .. sidebar:: Note It is best practice to use the script directive whenever an inline code block would have more than a few lines of code. Although there are other strategies to invoke separate scripts from your workflow (e.g., invoking them via shell commands), the benefit of this is obvious: the script logic is separated from the workflow logic (and can be even shared between workflows), but **boilerplate code like the parsing of command line arguments is unnecessary**. Apart from Python scripts, it is also possible to use R scripts. In R scripts, an S4 object named ``snakemake`` analog to the Python case above is available and allows access to input and output files and other parameters. Here the syntax follows that of S4 classes with attributes that are R lists, e.g. we can access the first input file with ``snakemake@input[[1]]`` (note that the first file does not have index 0 here, because R starts counting from 1). Named input and output files can be accessed in the same way, by just providing the name instead of an index, e.g. ``snakemake@input[["myfile"]]``. For details and examples, see the :ref:`snakefiles-external_scripts` section in the Documentation. Step 7: Adding a target rule :::::::::::::::::::::::::::: So far, we always executed the workflow by specifying a target file at the command line. Apart from filenames, Snakemake **also accepts rule names as targets** if the referred rule does not have wildcards. Hence, it is possible to write target rules collecting particular subsets of the desired results or all results. Moreover, if no target is given at the command line, Snakemake will define the **first rule** of the Snakefile as the target. Hence, it is best practice to have a rule ``all`` at the top of the workflow which has all typically desired target files as input files. Here, this means that we add a rule .. code:: python rule all: input: "plots/quals.svg" to the top of our workflow. When executing Snakemake with .. code:: console $ snakemake -n .. sidebar:: Note In case you have mutliple reasonable sets of target files, you can add multiple target rules at the top of the Snakefile. While Snakemake will execute the first per default, you can target any of them via the command line (e.g., ``snakemake -n mytarget``). the execution plan for creating the file ``plots/quals.svg`` which contains and summarizes all our results will be shown. Note that, apart from Snakemake considering the first rule of the workflow as default target, **the appearance of rules in the Snakefile is arbitrary and does not influence the DAG of jobs**. Exercise ........ * Create the DAG of jobs for the complete workflow. * Execute the complete workflow and have a look at the resulting ``plots/quals.svg``. * Snakemake provides handy flags for forcing re-execution of parts of the workflow. Have a look at the command line help with ``snakemake --help`` and search for the flag ``--forcerun``. Then, use this flag to re-execute the rule ``samtools_sort`` and see what happens. * With ``--reason`` it is possible to display the execution reason for each job. Try this flag together with a dry-run and the ``--forcerun`` flag to understand the decisions of Snakemake. Summary ::::::: In total, the resulting workflow looks like this: .. code:: console SAMPLES = ["A", "B"] rule all: input: "plots/quals.svg" rule bwa_map: input: "data/genome.fa", "data/samples/{sample}.fastq" output: "mapped_reads/{sample}.bam" shell: "bwa mem {input} | samtools view -Sb - > {output}" rule samtools_sort: input: "mapped_reads/{sample}.bam" output: "sorted_reads/{sample}.bam" shell: "samtools sort -T sorted_reads/{wildcards.sample} " "-O bam {input} > {output}" rule samtools_index: input: "sorted_reads/{sample}.bam" output: "sorted_reads/{sample}.bam.bai" shell: "samtools index {input}" rule bcftools_call: input: fa="data/genome.fa", bam=expand("sorted_reads/{sample}.bam", sample=SAMPLES), bai=expand("sorted_reads/{sample}.bam.bai", sample=SAMPLES) output: "calls/all.vcf" shell: "samtools mpileup -g -f {input.fa} {input.bam} | " "bcftools call -mv - > {output}" rule plot_quals: input: "calls/all.vcf" output: "plots/quals.svg" script: "scripts/plot-quals.py" snakemake-5.10.0/docs/tutorial/setup.rst000066400000000000000000000134141361131222100202140ustar00rootroot00000000000000 .. _tutorial-setup: Setup ----- .. _Snakemake: http://snakemake.readthedocs.io .. _Snakemake homepage: http://snakemake.readthedocs.io .. _GNU Make: https://www.gnu.org/software/make .. _Python: http://www.python.org .. _BWA: http://bio-bwa.sourceforge.net .. _SAMtools: http://www.htslib.org .. _BCFtools: http://www.htslib.org .. _Pandas: http://pandas.pydata.org .. _Miniconda: http://conda.pydata.org/miniconda.html .. _Conda: http://conda.pydata.org .. _Bash: http://www.tldp.org/LDP/Bash-Beginners-Guide/html .. _Atom: https://atom.io .. _Graphviz: http://www.graphviz.org .. _PyYAML: http://pyyaml.org .. _Docutils: http://docutils.sourceforge.net .. _Jinja2: http://jinja.pocoo.org .. _NetworkX: https://networkx.github.io .. _Matplotlib: https://matplotlib.org .. _Pysam: https://pysam.readthedocs.io .. _Bioconda: https://bioconda.github.io .. _Vagrant: https://www.vagrantup.com .. _Vagrant Documentation: https://docs.vagrantup.com .. _Blogpost: http://blog.osteel.me/posts/2015/01/25/how-to-use-vagrant-on-windows.html Requirements :::::::::::: To go through this tutorial, you need the following software installed: * Python_ ≥3.5 * Snakemake_ 5.2.3 * BWA_ 0.7.12 * SAMtools_ 1.3.1 * Pysam_ 0.15.0 * BCFtools_ 1.3.1 * Graphviz_ 2.38.0 * Jinja2_ 2.10 * NetworkX_ 2.1 * Matplotlib_ 2.2.3 The easiest way to setup these prerequisites is to use the Miniconda_ Python 3 distribution. The tutorial assumes that you are using either Linux or MacOS X. Both Snakemake and Miniconda work also under Windows, but the Windows shell is too different to be able to provide generic examples. Setup a Linux VM with Vagrant under Windows ::::::::::::::::::::::::::::::::::::::::::: If you already use Linux or MacOS X, go on with **Step 1**. If you use Windows, you can setup a Linux virtual machine (VM) with Vagrant_. First, install Vagrant following the installation instructions in the `Vagrant Documentation`_. Then, create a reasonable new directory you want to share with your Linux VM, e.g., create a folder ``vagrant-linux`` somewhere. Open a command line prompt, and change into that directory. Here, you create a 64-bit Ubuntu Linux environment with .. code:: console > vagrant init hashicorp/precise64 > vagrant up If you decide to use a 32-bit image, you will need to download the 32-bit version of Miniconda in the next step. The contents of the ``vagrant-linux`` folder will be shared with the virtual machine that is set up by vagrant. You can log into the virtual machine via .. code:: console > vagrant ssh If this command tells you to install an SSH client, you can follow the instructions in this Blogpost_. Now, you can follow the steps of our tutorial from within your Linux VM. Step 1: Installing Miniconda 3 :::::::::::::::::::::::::::::: First, please **open a terminal** or make sure you are logged into your Vagrant Linux VM. Assuming that you have a 64-bit system, on Linux, download and install Miniconda 3 with .. code:: console $ wget https://repo.continuum.io/miniconda/Miniconda3-latest-Linux-x86_64.sh $ bash Miniconda3-latest-Linux-x86_64.sh On MacOS X, download and install with .. code:: console $ curl https://repo.continuum.io/miniconda/Miniconda3-latest-MacOSX-x86_64.sh -o Miniconda3-latest-MacOSX-x86_64.sh $ bash Miniconda3-latest-MacOSX-x86_64.sh For a 32-bit system, URLs and file names are analogous but without the ``_64``. When you are asked the question .. code:: Do you wish the installer to prepend the Miniconda3 install location to PATH ...? [yes|no] answer with **yes**. Along with a minimal Python 3 environment, Miniconda contains the package manager Conda_. After opening a **new terminal**, you can use the new ``conda`` command to install software packages and create isolated environments to, e.g., use different versions of the same package. We will later use Conda_ to create an isolated environment with all required software for this tutorial. Step 2: Preparing a working directory ::::::::::::::::::::::::::::::::::::: First, **create a new directory** ``snakemake-tutorial`` at a **reasonable place** and change into that directory in your terminal: .. code:: console $ mkdir snakemake-tutorial $ cd snakemake-tutorial If you use a Vagrant Linux VM from Windows as described above, create that directory under ``/vagrant/``, so that the contents are shared with your host system (you can then edit all files from within Windows with an editor that supports Unix line breaks). Then, **change to the newly created directory**. In this directory, we will later create an example workflow that illustrates the Snakemake syntax and execution environment. First, we download some example data on which the workflow shall be executed: .. code:: console $ wget https://github.com/snakemake/snakemake-tutorial-data/archive/v5.4.5.tar.gz $ tar -xf v5.4.5.tar.gz --strip 1 This will create a folder ``data`` and a file ``environment.yaml`` in the working directory. Step 3: Creating an environment with the required software :::::::::::::::::::::::::::::::::::::::::::::::::::::::::: The ``environment.yaml`` file can be used to install all required software into an isolated Conda environment with the name ``snakemake-tutorial`` via .. code:: console $ conda env create --name snakemake-tutorial --file environment.yaml Step 4: Activating the environment :::::::::::::::::::::::::::::::::: To activate the ``snakemake-tutorial`` environment, execute .. code:: console $ conda activate snakemake-tutorial Now you can use the installed tools. Execute .. code:: console $ snakemake --help to test this and get information about the command-line interface of Snakemake. To exit the environment, you can execute .. code:: console $ conda deactivate but **don't do that now**, since we finally want to start working with Snakemake :-). snakemake-5.10.0/docs/tutorial/short.rst000066400000000000000000000317131361131222100202150ustar00rootroot00000000000000Short tutorial ============== Here we provide a short tutorial that guides you through the main features of Snakemake. Note that this is not suited to learn Snakemake from scratch, rather to give a first impression. To really learn Snakemake (starting from something simple, and extending towards advanced features), use the main :ref:`tutorial`. This document shows all steps performed in the official `Snakemake live demo `_, such that it becomes possible to follow them at your own pace. Solutions to each step can be found at the bottom of this document. The examples presented in this tutorial come from Bioinformatics. However, Snakemake is a general-purpose workflow management system for any discipline. For an explanation of the steps you will perform here, have a look at :ref:`tutorial-background`. More thorough explanations are provided in the full :ref:`tutorial`. Prerequisites ------------- First, install Snakemake via Conda, as outlined in :ref:`conda-install`. The minimal version of Snakemake is sufficient for this demo. Second, download and unpack the test data needed for this example from `here `_, e.g., via :: mkdir snakemake-demo cd snakemake-demo wget https://github.com/snakemake/snakemake-tutorial-data/archive/v5.4.5.tar.gz tar --wildcards -xf v5.4.5.tar.gz --strip 1 "*/data" Step 1 ------ First, create an empty workflow in the current directory with: :: touch Snakefile Once a Snakefile is present, you can perform a dry run of Snakemake with: :: snakemake -n Since the Snakefile is empty, it will report that nothing has to be done. In the next steps, we will gradually fill the Snakefile with an example analysis workflow. Step 2 ------ The data folder in your working directory looks as follows: :: data ├── genome.fa ├── genome.fa.amb ├── genome.fa.ann ├── genome.fa.bwt ├── genome.fa.fai ├── genome.fa.pac ├── genome.fa.sa └── samples ├── A.fastq ├── B.fastq └── C.fastq You will create a workflow that maps the sequencing samples in the ``data/samples`` folder to the reference genome ``data/genome.fa``. Then, you will call genomic variants over the mapped samples, and create an example plot. First, create a rule called ``bwa``, with input files - ``data/genome.fa`` - ``data/samples/A.fastq`` and output file - ``mapped/A.bam`` To generate output from input, use the shell command .. code:: python "bwa mem {input} | samtools view -Sb - > {output}" Providing a shell command is not enough to run your workflow on an unprepared system. For reproducibility, you also have to provide the required software stack and define the desired version. This can be done with the `Conda package manager `__, which is directly integrated with Snakemake: add a directive ``conda: "envs/mapping.yaml"`` that points to a `Conda environment definition `__, with the following content .. code:: yaml channels: - bioconda - conda-forge dependencies: - bwa =0.7.17 - samtools =1.9 Upon execution, Snakemake will automatically create that environment, and execute the shell command within. Now, test your workflow by simulating the creation of the file ``mapped/A.bam`` via :: snakemake --use-conda -n mapped/A.bam to perform a dry-run and :: snakemake --use-conda mapped/A.bam to perform the actual execution. Step 3 ------ Now, generalize the rule ``bwa`` by replacing the concrete sample name ``A`` with a wildcard ``{sample}`` in input and output file the rule ``bwa``. This way, Snakemake can apply the rule to map any of the three available samples to the reference genome. Test this by creating the file ``mapped/B.bam``. Step 4 ------ Next, create a rule ``sort`` that sorts the obtained ``.bam`` file by genomic coordinate. The rule should have the input file - ``mapped/{sample}.bam`` and the output file - ``mapped/{sample}.sorted.bam`` and uses the shell command :: samtools sort -o {output} {input} to perform the sorting. Moreover, use the same ``conda:`` directive as for the previous rule. Test your workflow with :: snakemake --use-conda -n mapped/A.sorted.bam and :: snakemake --use-conda mapped/A.sorted.bam Step 5 ------ Now, we aggregate over all samples to perform a joint calling of genomic variants. First, we define a variable .. code:: python samples = ["A", "B", "C"] at the top of the ``Snakefile``. This serves as a definition of the samples over which we would want to aggregate. In real life, you would want to use an external sample sheet or a `config file `__ for things like this. For aggregation over many files, Snakemake provides the helper function ``expand`` (see `the docs `__). Create a rule ``call`` with input files - ``fa="data/genome.fa"`` - ``bam=expand("mapped/{sample}.sorted.bam", sample=samples)`` output file - ``"calls/all.vcf"`` and shell command :: samtools mpileup -g -f {input.fa} {input.bam} | bcftools call -mv - > {output} Further, define a new conda environment file with the following content: .. code:: yaml channels: - bioconda - conda-forge dependencies: - bcftools =1.9 - samtools =1.9 Step 6 ------ Finally, we strive to calculate some exemplary statistics. This time, we don’t use a shell command, but rather employ Snakemake’s ability to integrate with scripting languages like R and Python. First, we create a rule ``stats`` with input file - ``"calls/all.vcf"`` and output file - ``"plots/quals.svg"``. Instead of a shell command, we write .. code:: python script: "scripts/plot-quals.py" and create the corresponding script and its containing folder in our working directory with :: mkdir scripts touch scripts/plot-quals.py We open the script in the editor and add the following content .. code:: python import matplotlib matplotlib.use("Agg") import matplotlib.pyplot as plt from pysam import VariantFile quals = [record.qual for record in VariantFile(snakemake.input[0])] plt.hist(quals) plt.savefig(snakemake.output[0]) As you can see, instead of writing a command line parser for passing parameters like input and output files, you have direct access to the properties of the rule via a magic ``snakemake`` object, that Snakemake automatically inserts into the script before executing the rule. Finally, we have to define a conda environment for the rule, say ``envs/stats.yaml``, that provides the required Python packages to execute the script: .. code:: yaml channels: - bioconda - conda-forge dependencies: - pysam =0.15 - matplotlib =3.1 - python =3.7 Make sure to test your workflow with :: snakemake --use-conda plots/quals.svg Step 7 ------ So far, we have always specified a target file at the command line when invoking Snakemake. When no target file is specified, Snakemake tries to execute the first rule in the ``Snakefile``. We can use this property to define default target files. At the top of your ``Snakefile`` define a rule ``all``, with input files - ``"calls/all.vcf"`` - ``"plots/quals.svg"`` and neither a shell command nor output files. This rule simply serves as an indicator of what shall be collected as results. Step 8 ------ As a last step, we strive to annotate our workflow with some additional information. Automatic reports ~~~~~~~~~~~~~~~~~ Snakemake can automatically create HTML reports with :: snakemake --report report.html Such a report contains runtime statistics, a visualization of the workflow topology, used software and data provenance information. In addition, you can mark any output file generated in your workflow for inclusion into the report. It will be encoded directly into the report, such that it can be, e.g., emailed as a self-contained document. The reader (e.g., a collaborator of yours) can at any time download the enclosed results from the report for further use, e.g., in a manuscript you write together. In this example, please mark the output file ``"plots/quals.svg"`` for inclusion by replacing it with ``report("plots/quals.svg", caption="report/calling.rst")`` and adding a file ``report/calling.rst``, containing some description of the output file. This description will be presented as caption in the resulting report. Threads ~~~~~~~ The first rule ``bwa`` can in theory use multiple threads. You can make Snakemake aware of this, such that the information can be used for scheduling. Add a directive ``threads: 8`` to the rule and alter the shell command to :: bwa mem -t {threads} {input} | samtools view -Sb - > {output} This passes the threads defined in the rule as a command line argument to the ``bwa`` process. Temporary files ~~~~~~~~~~~~~~~ The output of the ``bwa`` rule becomes superfluous once the sorted version of the ``.bam`` file is generated by the rule ``sort``. Snakemake can automatically delete the superfluous output once it is not needed anymore. For this, mark the output as temporary by replacing ``"mapped/{sample}.bam"`` in the rule ``bwa`` with ``temp("mapped/{sample}.bam")``. Solutions --------- Only read this if you have a problem with one of the steps. .. _step-2-1: Step 2 ~~~~~~ The rule should look like this: .. code:: python rule bwa: input: "data/genome.fa", "data/samples/A.fastq" output: "mapped/A.bam" conda: "envs/mapping.yaml" shell: "bwa mem {input} | samtools view -Sb - > {output}" .. _step-3-1: Step 3 ~~~~~~ The rule should look like this: .. code:: python rule bwa: input: "data/genome.fa", "data/samples/{sample}.fastq" output: "mapped/{sample}.bam" conda: "envs/mapping.yaml" shell: "bwa mem {input} | samtools view -Sb - > {output}" .. _step-4-1: Step 4 ~~~~~~ The rule should look like this: .. code:: python rule sort: input: "mapped/{sample}.bam" output: "mapped/{sample}.sorted.bam" conda: "envs/mapping.yaml" shell: "samtools sort -o {output} {input}" .. _step-5-1: Step 5 ~~~~~~ The rule should look like this: .. code:: python samples = ["A", "B", "C"] rule call: input: fa="data/genome.fa", bam=expand("mapped/{sample}.sorted.bam", sample=samples) output: "calls/all.vcf" conda: "envs/calling.yaml" shell: "samtools mpileup -g -f {input.fa} {input.bam} | " "bcftools call -mv - > {output}" .. _step-6-1: Step 6 ~~~~~~ The rule should look like this: .. code:: python rule stats: input: "calls/all.vcf" output: "plots/quals.svg" conda: "envs/stats.yaml" script: "scripts/plot-quals.py" .. _step-7-1: Step 7 ~~~~~~ The rule should look like this: .. code:: python rule all: input: "calls/all.vcf", "plots/quals.svg" It has to appear as first rule in the ``Snakefile``. .. _step-8-1: Step 8 ~~~~~~ The complete workflow should look like this: .. code:: python samples = ["A", "B"] rule all: input: "calls/all.vcf", "plots/quals.svg" rule bwa: input: "data/genome.fa", "data/samples/{sample}.fastq" output: temp("mapped/{sample}.bam") conda: "envs/mapping.yaml" threads: 8 shell: "bwa mem -t {threads} {input} | samtools view -Sb - > {output}" rule sort: input: "mapped/{sample}.bam" output: "mapped/{sample}.sorted.bam" conda: "envs/mapping.yaml" shell: "samtools sort -o {output} {input}" rule call: input: fa="data/genome.fa", bam=expand("mapped/{sample}.sorted.bam", sample=samples) output: "calls/all.vcf" conda: "envs/calling.yaml" shell: "samtools mpileup -g -f {input.fa} {input.bam} | " "bcftools call -mv - > {output}" rule stats: input: "calls/all.vcf" output: report("plots/quals.svg", caption="report/calling.rst") conda: "envs/stats.yaml" script: "scripts/plot-quals.py" snakemake-5.10.0/docs/tutorial/tutorial.rst000066400000000000000000000041541361131222100207200ustar00rootroot00000000000000.. _tutorial: ================== Snakemake Tutorial ================== .. _Snakemake: http://snakemake.readthedocs.io .. _GNU Make: https://www.gnu.org/software/make .. _Python: http://www.python.org .. _slides: http://slides.com/johanneskoester/snakemake-tutorial .. _Conda: https://conda.io .. _Singularity: https://www.sylabs.io This tutorial introduces the text-based workflow system Snakemake_. Snakemake follows the `GNU Make`_ paradigm: workflows are defined in terms of rules that define how to create output files from input files. Dependencies between the rules are determined automatically, creating a DAG (directed acyclic graph) of jobs that can be automatically parallelized. Snakemake sets itself apart from other text-based workflow systems in the following way. Hooking into the Python interpreter, Snakemake offers a definition language that is an extension of Python_ with syntax to define rules and workflow specific properties. This allows to combine the flexibility of a plain scripting language with a pythonic workflow definition. The Python language is known to be concise yet readable and can appear almost like pseudo-code. The syntactic extensions provided by Snakemake maintain this property for the definition of the workflow. Further, Snakemake's scheduling algorithm can be constrained by priorities, provided cores and customizable resources and it provides a generic support for distributed computing (e.g., cluster or batch systems). Hence, a Snakemake workflow scales without modification from single core workstations and multi-core servers to cluster or batch systems. Finally, Snakemake integrates with the package manager Conda_ and the container engine Singularity_ such that defining the software stack becomes part of the workflow itself. The examples presented in this tutorial come from Bioinformatics. However, Snakemake is a general-purpose workflow management system for any discipline. We ensured that no bioinformatics knowledge is needed to understand the tutorial. Also have a look at the corresponding slides_. .. toctree:: :maxdepth: 2 setup basics advanced additional_features snakemake-5.10.0/environment.yml000066400000000000000000000010711361131222100166120ustar00rootroot00000000000000channels: - conda-forge - bioconda dependencies: - python >=3.5 - boto3 - datrie - moto >=1.0.1 - httpretty - wrapt - pyyaml - ftputil - pysftp - requests - dropbox - appdirs - pytools - docutils - psutil - pandas - nomkl - google-cloud-storage - azure-storage - azure-storage-common - ratelimiter - configargparse - appdirs - python-irodsclient - jsonschema - networkx - pygraphviz # needed by graphviz - xorg-libxrender - xorg-libxpm - gitpython - pygments - imagemagick - nbformat - toposort snakemake-5.10.0/examples/000077500000000000000000000000001361131222100153425ustar00rootroot00000000000000snakemake-5.10.0/examples/c/000077500000000000000000000000001361131222100155645ustar00rootroot00000000000000snakemake-5.10.0/examples/c/README.txt000066400000000000000000000000751361131222100172640ustar00rootroot00000000000000http://www.cs.colby.edu/maxwell/courses/tutorials/maketutor/ snakemake-5.10.0/examples/c/include/000077500000000000000000000000001361131222100172075ustar00rootroot00000000000000snakemake-5.10.0/examples/c/include/hello.h000066400000000000000000000000351361131222100204610ustar00rootroot00000000000000void myPrintHelloMake(void); snakemake-5.10.0/examples/c/src/000077500000000000000000000000001361131222100163535ustar00rootroot00000000000000snakemake-5.10.0/examples/c/src/Makefile000066400000000000000000000007451361131222100200210ustar00rootroot00000000000000 IDIR=../include ODIR=obj LDIR=../lib LIBS=-lm CC=gcc CFLAGS=-I$(IDIR) _HEADERS = hello.h HEADERS = $(patsubst %,$(IDIR)/%,$(_HEADERS)) _OBJS = hello.o hellofunc.o OBJS = $(patsubst %,$(ODIR)/%,$(_OBJS)) # build the executable from the object files hello: $(OBJS) $(CC) -o $@ $^ $(CFLAGS) # compile a single .c file to an .o file $(ODIR)/%.o: %.c $(HEADERS) $(CC) -c -o $@ $< $(CFLAGS) # clean up temporary files .PHONY: clean clean: rm -f $(ODIR)/*.o *~ core $(IDIR)/*~ snakemake-5.10.0/examples/c/src/Snakefile000066400000000000000000000013621361131222100202010ustar00rootroot00000000000000from os.path import join IDIR = '../include' ODIR = 'obj' LDIR = '../lib' LIBS = '-lm' CC = 'gcc' CFLAGS = '-I' + IDIR _HEADERS = ['hello.h'] HEADERS = [join(IDIR, hfile) for hfile in _HEADERS] _OBJS = ['hello.o', 'hellofunc.o'] OBJS = [join(ODIR, ofile) for ofile in _OBJS] rule hello: """build the executable from the object files""" output: 'hello' input: OBJS shell: "{CC} -o {output} {input} {CFLAGS} {LIBS}" rule c_to_o: """compile a single .c file to an .o file""" output: temp('{ODIR}/{name}.o') input: '{name}.c' shell: "{CC} -c -o {output} {input} {CFLAGS}" rule clean: """clean up temporary files""" shell: "rm -f *~ core {IDIR}/*~" snakemake-5.10.0/examples/c/src/dag.png000066400000000000000000000177331361131222100176270ustar00rootroot00000000000000PNG  IHDREDFbKGDIDATxyt[Wd˫ɎE@v~d@)8!CJ8L !iPʤ9sSBӁ:!츶5,"[uʶ{%=s|tu>}}ޠDNk]UB4#ȟ㠜?H\w5~kS:_ֆY-҄**nqB3%OJv-tj3mn]f3y~ 4t,^ ^ir2d35%n Ξ8:;1R_kS߹Q"{2rbȟ9p ە+TWmKZnތ fCmhկ/_꒒/Dq1pl׮د^EO8[HRh/8y$?fix'6cxQSS3g̙33<si+ -[xG&s`!?oxT~ATE !lnٳV_B\=VZ+w^,\(//5\'x"VH>rC("oFD/h?x{7+VDB.kWDVee'(|?D]FT!lK?B87:KH?t"=Ab qN/\7BBbƍǛ!He˖Chp~cpNM6!c#vQ oъ֭Æ Ѐp X~-n7L&^}U`ҥhmm6Q__Rl߾=,7oS|"S7m۶zj}'{LcO>m388j߶e1*++YFF`j=pKOOg)))f6-É\ I'1<ȟ1O ǎ]w5nwߍcǎMh^ 666GSO!TM EIoъx7m7~iۿذaÔpB[x衇`e 777GDo@DSOa͚5HLL y>|m, %77k֬oxI]L#W__o۶- [!O> #Gرc(**;{JϟG^^^۱c~o ׯGii)/^B<BL Fp0rR]>KH(W\7(WD? o?ZYv-}Y DH}#&sM (NBVVz9'V߈I ţ>Pb! 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snakemake_dag 0 assembly sample: 103 2 compose_merge 0->2 1 all 5 merge_assemblies 2->5 3 assembly sample: 102 3->2 4 assembly sample: 101 4->2 6 compare_assemblies 5->6 8 diffexp 5->8 6->1 7 assembly sample: 104 7->2 8->1 snakemake-5.10.0/examples/cufflinks/hg19.fa000066400000000000000000000000001361131222100203740ustar00rootroot00000000000000snakemake-5.10.0/examples/cufflinks/hg19.gtf000066400000000000000000000000001361131222100205660ustar00rootroot00000000000000snakemake-5.10.0/examples/cufflinks/mapped/000077500000000000000000000000001361131222100205745ustar00rootroot00000000000000snakemake-5.10.0/examples/cufflinks/mapped/101.bam000066400000000000000000000000001361131222100215440ustar00rootroot00000000000000snakemake-5.10.0/examples/cufflinks/mapped/102.bam000066400000000000000000000000001361131222100215450ustar00rootroot00000000000000snakemake-5.10.0/examples/cufflinks/mapped/103.bam000066400000000000000000000000001361131222100215460ustar00rootroot00000000000000snakemake-5.10.0/examples/cufflinks/mapped/104.bam000066400000000000000000000000001361131222100215470ustar00rootroot00000000000000snakemake-5.10.0/examples/hello-world/000077500000000000000000000000001361131222100175725ustar00rootroot00000000000000snakemake-5.10.0/examples/hello-world/Snakefile000066400000000000000000000015621361131222100214220ustar00rootroot00000000000000configfile: "config.yaml" rule all: input: expand("plots/{country}.hist.pdf", country=config["countries"]) rule select_by_country: input: "data/worldcitiespop.csv" output: "by-country/{country}.csv" conda: "envs/xsv.yaml" shell: "xsv search -s Country '{wildcards.country}' {input} > {output}" rule plot_histogram: input: "by-country/{country}.csv" output: "plots/{country}.hist.svg" singularity: "docker://faizanbashir/python-datascience:3.6" script: "scripts/plot-hist.py" rule convert_to_pdf: input: "{prefix}.svg" output: "{prefix}.pdf" wrapper: "0.47.0/utils/cairosvg" rule download_data: output: "data/worldcitiespop.csv" shell: "curl -L https://burntsushi.net/stuff/worldcitiespop.csv > {output}" snakemake-5.10.0/examples/hello-world/config.yaml000066400000000000000000000000401361131222100217150ustar00rootroot00000000000000countries: - fr - at - sp snakemake-5.10.0/examples/hello-world/envs/000077500000000000000000000000001361131222100205455ustar00rootroot00000000000000snakemake-5.10.0/examples/hello-world/envs/matplotlib.yaml000066400000000000000000000001321361131222100235740ustar00rootroot00000000000000channels: - conda-forge dependencies: - python 3.7 - matplotlib 3.1 - pandas 0.25 snakemake-5.10.0/examples/hello-world/envs/xsv.yaml000066400000000000000000000000651361131222100222520ustar00rootroot00000000000000channels: - conda-forge dependencies: - xsv 0.13 snakemake-5.10.0/examples/hello-world/scripts/000077500000000000000000000000001361131222100212615ustar00rootroot00000000000000snakemake-5.10.0/examples/hello-world/scripts/plot-hist.py000066400000000000000000000002511361131222100235540ustar00rootroot00000000000000import matplotlib.pyplot as plt import pandas as pd cities = pd.read_csv(snakemake.input[0]) plt.hist(cities["Population"], bins=50) plt.savefig(snakemake.output[0]) 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I$U++҄bx}k>^z$I&$IB@Yx{Uqݕ4~/#i|0`h~sKYn:I$i-I$:Q(`h^w}vi+.p7t4ƺ$I'I$I }UAk)0=~{D#pǣ`  *s;$IV?I$#"Dk`? image/svg+xml Produce the files you want to have from some intermediateresult Tell Snakemake what filesyou want to be created rule: input: "A.txt", "B.txt", "C.txt" rule: input: "{sample}.inter" output: "{sample}.txt" shell: "somecommand {input} {output}" rule: input: "{sample}.in" output: "{sample}.inter" run: somepythoncode() Create a needed intermediate result Use wildcards to writegeneral rules for all samples Snakemake determinesthe dependenciesfor you snakemake-5.10.0/examples/latex/000077500000000000000000000000001361131222100164575ustar00rootroot00000000000000snakemake-5.10.0/examples/latex/Snakefile000066400000000000000000000006121361131222100203020ustar00rootroot00000000000000DOCUMENTS = ['document', 'response-to-editor'] TEXS = [doc+".tex" for doc in DOCUMENTS] PDFS = [doc+".pdf" for doc in DOCUMENTS] FIGURES = ['fig1.pdf'] include: 'tex.rules' rule all: input: PDFS rule zipit: output: 'upload.zip' input: TEXS, FIGURES, PDFS shell: 'zip -T {output} {input}' rule pdfclean: shell: "rm -f {PDFS}" snakemake-5.10.0/examples/latex/dag.png000066400000000000000000000224671361131222100177330ustar00rootroot00000000000000PNG  IHDRs{bKGD IDATxyt[ս/`YȲَؙ<$2)-ah1d( p)$+#ҮPhz&Ȣ-By-7*!yBI ! d۱!YdI5c˖%ٖu$Ykiw~:gc B™V$tBf9!DJ$3m@7h)݃hduls校H"qIDPHEȈBQJEf|СMvε0C7h`92 2Pt3jA؋A!Թka,V$%FP| ڰ'Z MBTx*$Lk[;dnཊnk7=.qP+H"^&DM' lF+L )`i2BoOls@]>w\X)Tr)ddm =CQϠ(1;"%d)O-ЏTt>A8,UrP3Յ0e9P9#zw_fbɸ`qߌ_B7C vFt ݠ ߴym xR\y2/ o‘f=XIJ ZFzo;])7.WC,𯳯Z xL#{ ,M5q}pJWK6|++iw2w0`׉6i3*K恣OYc?XùsPYY:{Q__J9s?}~|V͛7`pM/Яm~)= Nn 6l{P]]3g̙3?5X޶L^;\*BZћ}zzW2AP-)o̐+OaK}ul1&pBvE~GGq˶nrssYGGǶϝ;233ݖW]]߿p=_UUx=9p{cm߾%''7|1<8=Om`}r9?//oBcg6>c_mok/}u.M}zv::6l2O?vqzBL G^D 1r9'^m6ܹcGa/!GGGOx~:|c>]1ƲhО1O].kD{`_[nJ'N%xG08''g̈́q 4Vfc vo6>޽ n߻w/֭[w;& _1bcc}A.ofÁbt>2mWx# Ĥ2k9>{JNNf555nlʕfVYYd38x [ld1K/ m`z+jLղ[om۶7+W7YFF۳gcW^yeff;vxlӶ𴼱=3lʕL0FnfϯXeF5552o+o=0Bx3H2饗ؼy6ng{a .d2?1OS?ѭ]v~1&xgߏ/Nrk[yWJzۆޖ=m1YN\_DL1Eg>`YffFc2L>U_D},((`UUU'F~O1B(|cb{a---V՟Ҵ۲-}|LT(b?eHUJWO%X,3B5{{,#pٳgُcR؂ ءCڛj)ݩlq|;=Ӎi_S*ėܟګW͆ /J*ݙ51rH_R14D?˱~twwcxGﭼ틷e{㓭?1zjײRBx:1M>_mOHr!5c9~0LB+Wc͸͍7g?jkkaXPUUիWF]v-|I[lq{~͚5x'jjO`͚5=6oތ&'䟻ꪫsNL&477z1K19D3AK`m(鴹fjncO>uֹ[۲W=kپ>?LcvEo2{`_{`~LâYQQJ,;;ٳgʐzkW)Q_;- 233RdvUs6ZJ_ldcOv%~vp쏞ϊXtt4[l;|[{ʻ߾۲yꟾbײRBx:1MU={?=;UP+3>!sYɊ}pujQacIkabnx9pW9> ]ib ܒf;>NiFPIˌ¢$9#YY!BzoK&'J/SD/_k.;VRbzC?ֿduCu #3[$"(qB%bceqb]ebt'5b'/9'%ș7#!vߌ*qaL_]_~?nЊOw}8bWXd%D!E!8?́Ngی8f>}c$ńN ;cwU-TXP+AmC~؎.u=C8jDnN"p{/UMԒI~I ,MƵqB26>߅A/w b+~EՐgM5XƍpCv\f=ζaGnJaD܄*$BC9\rf2a`|,ݠ]ChdEAM8ejI%jyH Lհ́ ]- Z'^$6c)2P P`9]]]x"_C#++ yyyGEBYSS4 gE!9d&%CVcѢEg4Fi!.99"555p8h4X`Сr%p^mPTGEÀJ’%Kk(^HwKK,D>Q2(..Xގ:"BC{{;@,('G<̛7-wtt.201P[[|<. yIHH@II л(1D~(HPZZ##Ba`0 VsJŋqujjj㼊T*EII bcC2t451\šRĝTWWݑp9yEYYuz{{)G(ݎ*:/2JG<Ġ2koo/*++aSYHJLR$tQ2111(++Ctt4@ףzp%r^FYY%r2%R΋BzTTTf2fOr6!cQ2 `@EE?ㅄՊ  ȉo451Y,TVVd2Ww(%b i( xCS#QTTJKKP(b82⋧DN_#T*EYY✗rDyy9fɘf<..eeexC>044r  oxxr^7>>%%%HJ5%'HP\\'Iol||<))snDž O\4_YX& yaҥ|!5BD@ WTR `@k \T8&d*(!"K.BJFQ6HRaҥTL9uY$ON!o``d$2{ xb6 8700*̂ZŋqpG|8-BJJ ф:@J|"OII… )d>q"'pdϭejj*(d>ǹzFFl.\@ =zzzp!IQ2'^UUN'pTOӹ])33GE"%s+((@vv6kjj(@ww7jjj://;;GE"%s&77999FzggQN<''GE"%s2󑗗!pTᣣuuu|" D233 mڴZ-?C8pdeeQ'9 ,V˟`#v8}8Z-`n2 WbH D 7.A$!##:DB86["f_' eIxdN1XY ͡\Tҟz  () H.G'Dslᇰ () ȉ5w=Ij$}7޽GD2JoV#GQP~ OyJO = 3XIDAT'dNf8~)NpaZ 18;<0ksrvP}=:^{9VqP? >2eŋv-Y,hݹf & f׭|""sǨ^(F9aV8e+tz+ԏ<"pT@KɜL?pw݅ĻH&6sݿi⮻6e(b Cs%*׮Euׅ8ɓ_au>qH~$t I`ΞE[o&<D]=bR{f6 VUpĄuJyQ(/0JB&dN1<>@ߡC`6'@jh!dՀB@gBHD !9p8IENDB`snakemake-5.10.0/examples/latex/document.tex000066400000000000000000000000001361131222100210050ustar00rootroot00000000000000snakemake-5.10.0/examples/latex/fig1.pdf000066400000000000000000000000001361131222100177660ustar00rootroot00000000000000snakemake-5.10.0/examples/latex/response-to-editor.tex000066400000000000000000000000001361131222100227310ustar00rootroot00000000000000snakemake-5.10.0/examples/latex/tex.rules000066400000000000000000000011371361131222100203350ustar00rootroot00000000000000ruleorder: tex2pdf_with_bib > tex2pdf_without_bib rule tex2pdf_with_bib: input: '{name}.tex', '{name}.bib' output: '{name}.pdf' shell: """ pdflatex {wildcards.name} bibtex {wildcards.name} pdflatex {wildcards.name} pdflatex {wildcards.name} """ rule tex2pdf_without_bib: input: '{name}.tex' output: '{name}.pdf' shell: """ pdflatex {wildcards.name} pdflatex {wildcards.name} """ rule texclean: shell: "rm -f *.log *.aux *.bbl *.blg *.synctex.gz" snakemake-5.10.0/examples/mirna/000077500000000000000000000000001361131222100164505ustar00rootroot00000000000000snakemake-5.10.0/examples/mirna/dag.dot000066400000000000000000000227361361131222100177250ustar00rootroot00000000000000digraph snakemake_dag { 35[label = "do_readlengths_of_one_file"]; 34 -> 35; 103[label = "count_mirbase_mappable"]; 102 -> 103; 143[label = "count_mirna_expression_of_one_dataset"]; 142 -> 143; 141 -> 143; 42[label = "do_readlengths_pdfs"]; 41 -> 42; 164[label = "annotate"]; 147 -> 164; 90 -> 164; 2[label = "compute_readcounts\nds: 554"]; 10[label = "run_cutadapt\nds: 552"]; 34[label = "run_cutadapt\nds: 560"]; 153[label = "rna_type"]; 152 -> 153; 11[label = "do_readlengths_of_one_file"]; 10 -> 11; 138[label = "sort_a_bam_file"]; 110 -> 138; 38[label = "do_readlengths_of_one_file"]; 37 -> 38; 56[label = "do_readlengths_of_one_file"]; 55 -> 56; 36[label = "do_readlengths_pdfs"]; 35 -> 36; 137[label = "count_mirna_expression_of_one_dataset"]; 135 -> 137; 136 -> 137; 13[label = "run_cutadapt\nds: 553"]; 37[label = "run_cutadapt\nds: 561"]; 41[label = "do_readlengths_of_one_file"]; 40 -> 41; 109[label = "count_mirbase_mappable"]; 108 -> 109; 132[label = "sort_a_bam_file"]; 106 -> 132; 165[label = "rna_type"]; 164 -> 165; 18[label = "do_readlengths_pdfs"]; 17 -> 18; 40[label = "do_shortreads\nds: 552"]; 16[label = "run_cutadapt\nds: 554"]; 84[label = "map_ds_against_hg"]; 16 -> 84; 81 -> 84; 151[label = "rna_type"]; 150 -> 151; 155[label = "rna_type"]; 154 -> 155; 51[label = "do_readlengths_pdfs"]; 50 -> 51; 166[label = "annotate"]; 91 -> 166; 147 -> 166; 20[label = "do_readlengths_of_one_file"]; 19 -> 20; 43[label = "do_shortreads\nds: 553"]; 64[label = "do_shortreads\nds: 560"]; 0[label = "compute_readcounts\nds: 552"]; 139[label = "index_a_bam_file"]; 138 -> 139; 5[label = "compute_readcounts\nds: 557"]; 19[label = "run_cutadapt\nds: 555"]; 54[label = "do_readlengths_pdfs"]; 53 -> 54; 21[label = "do_readlengths_pdfs"]; 20 -> 21; 152[label = "annotate"]; 84 -> 152; 147 -> 152; 47[label = "do_readlengths_of_one_file"]; 46 -> 47; 46[label = "do_shortreads\nds: 554"]; 23[label = "do_readlengths_of_one_file"]; 22 -> 23; 150[label = "annotate"]; 147 -> 150; 83 -> 150; 24[label = "do_readlengths_pdfs"]; 23 -> 24; 57[label = "do_readlengths_pdfs"]; 56 -> 57; 118[label = "index_a_bam_file"]; 117 -> 118; 22[label = "run_cutadapt\nds: 556"]; 49[label = "do_shortreads\nds: 555"]; 140[label = "count_mirna_expression_of_one_dataset"]; 138 -> 140; 139 -> 140; 170[label = "all"]; 57 -> 170; 101 -> 170; 54 -> 170; 21 -> 170; 24 -> 170; 85 -> 170; 103 -> 170; 2 -> 170; 27 -> 170; 144 -> 170; 63 -> 170; 78 -> 170; 82 -> 170; 105 -> 170; 3 -> 170; 86 -> 170; 6 -> 170; 0 -> 170; 107 -> 170; 97 -> 170; 80 -> 170; 36 -> 170; 12 -> 170; 39 -> 170; 8 -> 170; 109 -> 170; 88 -> 170; 18 -> 170; 71 -> 170; 83 -> 170; 5 -> 170; 4 -> 170; 89 -> 170; 60 -> 170; 48 -> 170; 145 -> 170; 113 -> 170; 90 -> 170; 42 -> 170; 169 -> 170; 73 -> 170; 7 -> 170; 84 -> 170; 91 -> 170; 30 -> 170; 51 -> 170; 1 -> 170; 146 -> 170; 87 -> 170; 9 -> 170; 95 -> 170; 33 -> 170; 69 -> 170; 111 -> 170; 99 -> 170; 45 -> 170; 15 -> 170; 66 -> 170; 55[label = "do_shortreads\nds: 557"]; 26[label = "do_readlengths_of_one_file"]; 25 -> 26; 60[label = "do_readlengths_pdfs"]; 59 -> 60; 93[label = "build_bwa_index"]; 92 -> 93; 27[label = "do_readlengths_pdfs"]; 26 -> 27; 52[label = "do_shortreads\nds: 556"]; 135[label = "sort_a_bam_file"]; 108 -> 135; 4[label = "compute_readcounts\nds: 556"]; 59[label = "do_readlengths_of_one_file"]; 58 -> 59; 63[label = "do_readlengths_pdfs"]; 62 -> 63; 154[label = "annotate"]; 147 -> 154; 85 -> 154; 29[label = "do_readlengths_of_one_file"]; 28 -> 29; 6[label = "compute_readcounts\nds: 558"]; 14[label = "do_readlengths_of_one_file"]; 13 -> 14; 3[label = "compute_readcounts\nds: 555"]; 114[label = "sort_a_bam_file"]; 94 -> 114; 73[label = "do_readlengths_pdfs"]; 72 -> 73; 7[label = "compute_readcounts\nds: 559"]; 120[label = "sort_a_bam_file"]; 98 -> 120; 142[label = "index_a_bam_file"]; 141 -> 142; 58[label = "do_shortreads\nds: 558"]; 158[label = "annotate"]; 87 -> 158; 147 -> 158; 62[label = "do_readlengths_of_one_file"]; 61 -> 62; 9[label = "compute_readcounts\nds: 561"]; 28[label = "run_cutadapt\nds: 558"]; 157[label = "rna_type"]; 156 -> 157; 12[label = "do_readlengths_pdfs"]; 11 -> 12; 31[label = "run_cutadapt\nds: 559"]; 61[label = "do_shortreads\nds: 559"]; 168[label = "rnatypes"]; 165 -> 168; 151 -> 168; 149 -> 168; 153 -> 168; 161 -> 168; 163 -> 168; 159 -> 168; 157 -> 168; 155 -> 168; 167 -> 168; 65[label = "do_readlengths_of_one_file"]; 64 -> 65; 136[label = "index_a_bam_file"]; 135 -> 136; 126[label = "sort_a_bam_file"]; 102 -> 126; 50[label = "do_readlengths_of_one_file"]; 49 -> 50; 122[label = "count_mirna_expression_of_one_dataset"]; 121 -> 122; 120 -> 122; 147[label = "hgtrack"]; 39[label = "do_readlengths_pdfs"]; 38 -> 39; 144[label = "normalize_expressions"]; 128 -> 144; 116 -> 144; 122 -> 144; 119 -> 144; 137 -> 144; 131 -> 144; 125 -> 144; 143 -> 144; 140 -> 144; 134 -> 144; 113[label = "count_mirbase_mappable"]; 112 -> 113; 68[label = "do_readlengths_of_one_file"]; 67 -> 68; 45[label = "do_readlengths_pdfs"]; 44 -> 45; 82[label = "map_ds_against_hg"]; 10 -> 82; 81 -> 82; 86[label = "map_ds_against_hg"]; 22 -> 86; 81 -> 86; 117[label = "sort_a_bam_file"]; 96 -> 117; 159[label = "rna_type"]; 158 -> 159; 67[label = "do_shortreads\nds: 561"]; 8[label = "compute_readcounts\nds: 560"]; 88[label = "map_ds_against_hg"]; 28 -> 88; 81 -> 88; 99[label = "count_mirbase_mappable"]; 98 -> 99; 71[label = "do_readlengths_pdfs"]; 70 -> 71; 161[label = "rna_type"]; 160 -> 161; 25[label = "run_cutadapt\nds: 557"]; 89[label = "map_ds_against_hg"]; 31 -> 89; 81 -> 89; 32[label = "do_readlengths_of_one_file"]; 31 -> 32; 124[label = "index_a_bam_file"]; 123 -> 124; 90[label = "map_ds_against_hg"]; 34 -> 90; 81 -> 90; 141[label = "sort_a_bam_file"]; 112 -> 141; 131[label = "count_mirna_expression_of_one_dataset"]; 129 -> 131; 130 -> 131; 160[label = "annotate"]; 147 -> 160; 88 -> 160; 91[label = "map_ds_against_hg"]; 37 -> 91; 81 -> 91; 95[label = "count_mirbase_mappable"]; 94 -> 95; 97[label = "count_mirbase_mappable"]; 96 -> 97; 87[label = "map_ds_against_hg"]; 25 -> 87; 81 -> 87; 70[label = "do_readlengths_summary"]; 23 -> 70; 11 -> 70; 17 -> 70; 26 -> 70; 29 -> 70; 32 -> 70; 14 -> 70; 35 -> 70; 20 -> 70; 38 -> 70; 133[label = "index_a_bam_file"]; 132 -> 133; 149[label = "rna_type"]; 148 -> 149; 94[label = "map_ds_against_mirbase"]; 93 -> 94; 40 -> 94; 92 -> 94; 92[label = "compute_mirnas_with_context"]; 116[label = "count_mirna_expression_of_one_dataset"]; 114 -> 116; 115 -> 116; 125[label = "count_mirna_expression_of_one_dataset"]; 123 -> 125; 124 -> 125; 33[label = "do_readlengths_pdfs"]; 32 -> 33; 96[label = "map_ds_against_mirbase"]; 93 -> 96; 43 -> 96; 92 -> 96; 78[label = "do_readlengths_pdfs"]; 77 -> 78; 101[label = "count_mirbase_mappable"]; 100 -> 101; 17[label = "do_readlengths_of_one_file"]; 16 -> 17; 98[label = "map_ds_against_mirbase"]; 93 -> 98; 46 -> 98; 92 -> 98; 146[label = "correlate_seq_with_rtpcr"]; 144 -> 146; 119[label = "count_mirna_expression_of_one_dataset"]; 117 -> 119; 118 -> 119; 69[label = "do_readlengths_pdfs"]; 68 -> 69; 72[label = "do_readlengths_summary"]; 50 -> 72; 41 -> 72; 56 -> 72; 53 -> 72; 47 -> 72; 44 -> 72; 68 -> 72; 59 -> 72; 65 -> 72; 62 -> 72; 100[label = "map_ds_against_mirbase"]; 93 -> 100; 49 -> 100; 92 -> 100; 162[label = "annotate"]; 89 -> 162; 147 -> 162; 53[label = "do_readlengths_of_one_file"]; 52 -> 53; 105[label = "count_mirbase_mappable"]; 104 -> 105; 167[label = "rna_type"]; 166 -> 167; 48[label = "do_readlengths_pdfs"]; 47 -> 48; 102[label = "map_ds_against_mirbase"]; 93 -> 102; 52 -> 102; 92 -> 102; 107[label = "count_mirbase_mappable"]; 106 -> 107; 148[label = "annotate"]; 82 -> 148; 147 -> 148; 111[label = "count_mirbase_mappable"]; 110 -> 111; 169[label = "plot_rnatypes"]; 168 -> 169; 104[label = "map_ds_against_mirbase"]; 93 -> 104; 55 -> 104; 92 -> 104; 80[label = "plot_mirna_distancematrix_histogram"]; 79 -> 80; 127[label = "index_a_bam_file"]; 126 -> 127; 106[label = "map_ds_against_mirbase"]; 93 -> 106; 58 -> 106; 92 -> 106; 134[label = "count_mirna_expression_of_one_dataset"]; 133 -> 134; 132 -> 134; 108[label = "map_ds_against_mirbase"]; 93 -> 108; 61 -> 108; 92 -> 108; 77[label = "compute_mirna_lengths"]; 79[label = "compute_fasta_distancematrix\nprefix: mirbase/mirnas"]; 85[label = "map_ds_against_hg"]; 19 -> 85; 81 -> 85; 163[label = "rna_type"]; 162 -> 163; 110[label = "map_ds_against_mirbase"]; 64 -> 110; 92 -> 110; 93 -> 110; 66[label = "do_readlengths_pdfs"]; 65 -> 66; 129[label = "sort_a_bam_file"]; 104 -> 129; 121[label = "index_a_bam_file"]; 120 -> 121; 30[label = "do_readlengths_pdfs"]; 29 -> 30; 112[label = "map_ds_against_mirbase"]; 67 -> 112; 92 -> 112; 93 -> 112; 1[label = "compute_readcounts\nds: 553"]; 128[label = "count_mirna_expression_of_one_dataset"]; 126 -> 128; 127 -> 128; 130[label = "index_a_bam_file"]; 129 -> 130; 44[label = "do_readlengths_of_one_file"]; 43 -> 44; 81[label = "build_bwa_index\nprefix: hgref/hg1kv37.fasta.gz"]; 15[label = "do_readlengths_pdfs"]; 14 -> 15; 145[label = "differential_expressions"]; 144 -> 145; 156[label = "annotate"]; 147 -> 156; 86 -> 156; 83[label = "map_ds_against_hg"]; 13 -> 83; 81 -> 83; 123[label = "sort_a_bam_file"]; 100 -> 123; 115[label = "index_a_bam_file"]; 114 -> 115; } snakemake-5.10.0/examples/mirna/dag.png000066400000000000000000110377131361131222100177260ustar00rootroot00000000000000PNG  IHDRb NbKGD IDATxy|T3Y&df2L&;* ,BRB[z mj[{jmjֽEJQj `Y$HL&d{s܄M,=3dgT`P/#L?|i|iJz{η_zdaaaqqqXjX="K!\xģ.+ J)IRgggKK$I`rުC> n;t|755.$Tϧ@ p8cbbӸn!fV)rK=cbb϶`0T^7@U D677Kx|>\9+rWl'!hmm*`0ȧj:66V>Uhұ&**J> FDDt>uCfpCu ^yZgӭuymhλvIh[I% .kţtK&ox(<<\_DmAd/_loookk^$X5EzXEpS;N+)rw !]9):EXSN=hC`9|!%z18f9,W1,B=ˋE(_)'H<-3}G@|KEFF(F# CDD^?5bh4$=E @ .nean<8yG,و*rbXdE8R4 Gk>"/~ZOJ\ŏzGNX,rHďt:c?qqqF XFz4b@f3\."$B"r:;;E8tΩ"Vv~9BљXD 0UӉ> D{T"(x^()g񋨩I݂do!Kr?n[!t:H*u:F5 b2..NՊ^7OKzAd!`*E>OwttFũ {XdX233@҈)΍ 2qs!FZ]]m۫l6[uujZ\i4rrrrJJJZZZZZlVv > 2l22qzallFcttRPJ}}fNlbMtttZt1HMMR~D@v2zzULL̐!C*B8FZ.!:::$IRT匌ԴC*]>DpٵvX|&>cX(;3fłXqrhF999922R 2z&5noo`0ǟ-d,GzEkkkyyyUUUruu$)"""555!C(];"ׇmhhO娱 *66VNǟ-d9666+++++kԨQGcNt0DQSScZ]l6[S)WT.IIIiLLrN>-BǏ/))x<$ Çcǎ7nѣccc.+e\[[[[[[__p8v{]]]]]6>O^jEboqBB|:tPd4|SN}N*))9uTUUU0TÇ5j>yԨQ J Ad"y^&l"^3s&j&Idf6  j0!c"fY+=uTq/1"''gĉ999999J  24ml6[ϖS 7L&)))I1Qc4>>^ٽvXGGǐ!C&X,J `p! 0|ZjۭV-ju8>Oh4ɉIIIhXDbFe78#W\\g}CsA2 p%/ZNS BbYxxxzz,bV|'OrŒeڴiJ `! 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Highlighting can be forced in a vim session with `:set syntax=snakemake`. To install via Vundle use: Plugin 'https://github.com/snakemake/snakemake.git', {'rtp': 'misc/vim/'} snakemake-5.10.0/misc/vim/syntax/000077500000000000000000000000001361131222100166005ustar00rootroot00000000000000snakemake-5.10.0/misc/vim/syntax/snakemake.vim000066400000000000000000000045671361131222100212700ustar00rootroot00000000000000" Vim syntax file " Language: Snakemake (extended from python.vim) " Maintainer: Jay Hesselberth (jay.hesselberth@gmail.com) " Last Change: 2019 Nov 22 " " Usage " " copy to $HOME/.vim/syntax directory and add: " " au BufNewFile,BufRead Snakefile set syntax=snakemake " au BufNewFile,BufRead *.snake set syntax=snakemake " " to your $HOME/.vimrc file " " force coloring in a vim session with: " " :set syntax=snakemake " " load settings from system python.vim (7.4) source $VIMRUNTIME/syntax/python.vim source $VIMRUNTIME/indent/python.vim " " Snakemake rules, as of version 5.8 " " " rule = "rule" (identifier | "") ":" ruleparams " include = "include:" stringliteral " workdir = "workdir:" stringliteral " ni = NEWLINE INDENT " ruleparams = [ni input] [ni output] [ni params] [ni message] [ni threads] [ni (run | shell)] NEWLINE snakemake " input = "input" ":" parameter_list " output = "output" ":" parameter_list " params = "params" ":" parameter_list " message = "message" ":" stringliteral " threads = "threads" ":" integer " resources = "resources" ":" parameter_list " version = "version" ":" statement " run = "run" ":" ni statement " shell = "shell" ":" stringliteral " singularity = "singularity" ":" stringliteral " conda = "conda" ":" stringliteral " shadow = "shadow" ":" stringliteral " group = "group" ":" stringliteral syn keyword pythonStatement include workdir onsuccess onerror onstart syn keyword pythonStatement ruleorder localrules configfile group syn keyword pythonStatement wrapper conda shadow syn keyword pythonStatement input output params wildcards priority message threads resources singularity wildcard_constraints syn keyword pythonStatement version run shell benchmark snakefile log script syn keyword pythonStatement rule subworkflow checkpoint nextgroup=pythonFunction skipwhite syn keyword pythonBuiltinObj config checkpoints rules syn keyword pythonBuiltinFunc directory ancient pipe unpack expand temp touch protected " similar to special def and class treatment from python.vim, except " parenthetical part of def and class syn match pythonFunction \ "\%(\%(rule\s\|subworkflow\s\|checkpoint\s\)\s*\)\@<=\h\w*" contained syn sync match pythonSync grouphere NONE "^\s*\%(rule\|subworkflow\|checkpoint\)\s\+\h\w*\s*" let b:current_syntax = "snakemake" " vim:set sw=2 sts=2 ts=8 noet: snakemake-5.10.0/motoState.p000066400000000000000000000054241361131222100156710ustar00rootroot00000000000000}qXtest-remote-bucketqcmoto.s3.models FakeBucket q)q}q(XnameqhX region_nameqX us-east-1qXkeysqcmoto.s3.utils _VersionedKeyStore q )q (Xtest.txtq cmoto.s3.models FakeKey q )q }q(hh X last_modifiedqcdatetime datetime qC   qqRqXaclqcmoto.s3.models FakeAcl q)q}qXgrantsq]qcmoto.s3.models FakeGrant q)q}q(Xgranteesq]qcmoto.s3.models FakeGrantee q)q }q!(Xidq"X@75aa57f09aa0c8caeab4f8c24e99d10f8e7faeebf76c078efc7c6caea54ba06aq#Xuriq$Xq%X display_nameq&h%ubaX permissionsq']q(X FULL_CONTROLq)aubasbXwebsite_redirect_locationq*NX_storage_classq+XSTANDARDq,X _metadataq-}q.X Content-MD5q/XW8jMiY+lhpgarIV37vixHA==q0sX_expiryq1NX_etagq2X 5bc8cc898fa586981aac8577eef8b11cq3X _version_idq4NX _is_versionedq5X_taggingq6cmoto.s3.models FakeTagging q7)q8}q9Xtag_setq:cmoto.s3.models FakeTagSet q;)q<}q=Xtagsq>]q?sbsbX_max_buffer_sizeq@JXvalueqACH0 1 2 0 1 2 0 1 2 0 1 2 qBubX prefixab.txtqCh )qD}qE(hX prefixab.txtqFhhC  &qGqHRqIhhh*Nh+XSTANDARDqJh-}qKX Content-MD5qLXnNjTuf4V0VmDLLoZuDND4Q==qMsh1Nh2X 9cd8d3b9fe15d159832cba19b83343e1qNh4Nh5h6h7)qO}qPh:h;)qQ}qRh>]qSsbsbX_max_buffer_sizeqTJhAC$0 1 2 0 1 2 qUubX prefixaa.txtqVh )qW}qX(hX prefixaa.txtqYhhC  & qZq[Rq\hhh*Nh+XSTANDARDq]h-}q^X Content-MD5q_XnNjTuf4V0VmDLLoZuDND4Q==q`sh1Nh2X 9cd8d3b9fe15d159832cba19b83343e1qah4Nh5h6h7)qb}qch:h;)qd}qeh>]qfsbsbX_max_buffer_sizeqgJhAC$0 1 2 0 1 2 qhubX ab_cut.txtqih )qj}qk(hX ab_cut.txtqlhhC  '.IqmqnRqohhh*Nh+XSTANDARDqph-}qqX Content-MD5qrXnNjTuf4V0VmDLLoZuDND4Q==qssh1Nh2X 9cd8d3b9fe15d159832cba19b83343e1qth4Nh5h6h7)qu}qvh:h;)qw}qxh>]qysbsbX_max_buffer_sizeqzJhAC$0 1 2 0 1 2 q{ubX aa_cut.txtq|h )q}}q~(hX aa_cut.txtqhhC  (qqRqhhh*Nh+XSTANDARDqh-}qX Content-MD5qXnNjTuf4V0VmDLLoZuDND4Q==qsh1Nh2X 9cd8d3b9fe15d159832cba19b83343e1qh4Nh5h6h7)q}qh:h;)q}qh>]qsbsbX_max_buffer_sizeqJhAC$0 1 2 0 1 2 qubXout.txtqh )q}q(hXout.txtqhhC  ) ?qqRqhhh*Nh+XSTANDARDqh-}qX Content-MD5qXW8jMiY+lhpgarIV37vixHA==qsh1Nh2X 5bc8cc898fa586981aac8577eef8b11cqh4Nh5h6h7)q}qh:h;)q}qh>]qsbsbX_max_buffer_sizeqJhACH0 1 2 0 1 2 0 1 2 0 1 2 qubuX multipartsq}qXversioning_statusqNXrulesq]qXpolicyqNXwebsite_configurationqNhhh>h7)q}qh:h;)q}qh>]qsbsbXcorsq]qXloggingq}qXnotification_configurationqNubs.snakemake-5.10.0/setup.cfg000066400000000000000000000002121361131222100153400ustar00rootroot00000000000000[versioneer] VCS = git style = pep440 versionfile_source = snakemake/_version.py versionfile_build = snakemake/_version.py tag_prefix = v snakemake-5.10.0/setup.py000066400000000000000000000044171361131222100152440ustar00rootroot00000000000000# -*- coding: UTF-8 -*- from __future__ import print_function __author__ = "Johannes Köster" __copyright__ = "Copyright 2015, Johannes Köster" __email__ = "koester@jimmy.harvard.edu" __license__ = "MIT" import sys import versioneer if sys.version_info < (3, 5): print("At least Python 3.5 is required.\n", file=sys.stderr) exit(1) try: from setuptools import setup except ImportError: print("Please install setuptools before installing snakemake.", file=sys.stderr) exit(1) setup( name="snakemake", version=versioneer.get_version(), cmdclass=versioneer.get_cmdclass(), author="Johannes Köster", author_email="johannes.koester@tu-dortmund.de", description="Snakemake is a workflow management system that aims to reduce the complexity " "of creating workflows by providing a fast and comfortable execution environment, " "together with a clean and modern specification language in python style. " "Snakemake workflows are essentially Python scripts extended by declarative " "code to define rules. Rules describe how to create output files from input files.", zip_safe=False, license="MIT", url="https://snakemake.readthedocs.io", packages=["snakemake", "snakemake.remote", "snakemake.report", "snakemake.caching", "snakemake.deployment"], entry_points={ "console_scripts": [ "snakemake = snakemake:main", "snakemake-bash-completion = snakemake:bash_completion", ] }, package_data={"": ["*.css", "*.sh", "*.html"]}, install_requires=[ "wrapt", "requests", "ratelimiter", "pyyaml", "configargparse", "appdirs", "datrie", "jsonschema", "docutils", "gitpython", "psutil", "nbformat", "toposort", ], extras_require={"reports": ["jinja2", "networkx", "pygments", "pygraphviz"], "messaging": ["slacker"]}, classifiers=[ "Development Status :: 5 - Production/Stable", "Environment :: Console", "Intended Audience :: Science/Research", "License :: OSI Approved :: MIT License", "Natural Language :: English", "Programming Language :: Python :: 3.5", "Topic :: Scientific/Engineering :: Bio-Informatics", ], ) snakemake-5.10.0/snakemake/000077500000000000000000000000001361131222100154635ustar00rootroot00000000000000snakemake-5.10.0/snakemake/__init__.py000066400000000000000000002552371361131222100176120ustar00rootroot00000000000000__author__ = "Johannes Köster" __copyright__ = "Copyright 2015-2019, Johannes Köster" __email__ = "koester@jimmy.harvard.edu" __license__ = "MIT" import os import subprocess import glob from argparse import ArgumentError import logging as _logging import re import sys import inspect import threading import webbrowser from functools import partial import importlib import shutil from importlib.machinery import SourceFileLoader from snakemake.workflow import Workflow from snakemake.dag import Batch from snakemake.exceptions import print_exception, WorkflowError from snakemake.logging import setup_logger, logger, SlackLogger from snakemake.io import load_configfile from snakemake.shell import shell from snakemake.utils import update_config, available_cpu_count from snakemake.common import Mode, __version__ from snakemake.resources import parse_resources, DefaultResources SNAKEFILE_CHOICES = [ "Snakefile", "snakefile", "workflow/Snakefile", "workflow/snakefile", ] def snakemake( snakefile, batch=None, cache=None, report=None, listrules=False, list_target_rules=False, cores=1, nodes=1, local_cores=1, resources=dict(), overwrite_threads=dict(), default_resources=None, config=dict(), configfiles=None, config_args=None, workdir=None, targets=None, dryrun=False, touch=False, forcetargets=False, forceall=False, forcerun=[], until=[], omit_from=[], prioritytargets=[], stats=None, printreason=False, printshellcmds=False, debug_dag=False, printdag=False, printrulegraph=False, printfilegraph=False, printd3dag=False, nocolor=False, quiet=False, keepgoing=False, cluster=None, cluster_config=None, cluster_sync=None, drmaa=None, drmaa_log_dir=None, jobname="snakejob.{rulename}.{jobid}.sh", immediate_submit=False, standalone=False, ignore_ambiguity=False, snakemakepath=None, lock=True, unlock=False, cleanup_metadata=None, cleanup_conda=False, cleanup_shadow=False, cleanup_scripts=True, force_incomplete=False, ignore_incomplete=False, list_version_changes=False, list_code_changes=False, list_input_changes=False, list_params_changes=False, list_untracked=False, list_resources=False, summary=False, archive=None, delete_all_output=False, delete_temp_output=False, detailed_summary=False, latency_wait=3, wait_for_files=None, print_compilation=False, debug=False, notemp=False, keep_remote_local=False, nodeps=False, keep_target_files=False, allowed_rules=None, jobscript=None, greediness=None, no_hooks=False, overwrite_shellcmd=None, updated_files=None, log_handler=[], keep_logger=False, max_jobs_per_second=None, max_status_checks_per_second=100, restart_times=0, attempt=1, verbose=False, force_use_threads=False, use_conda=False, use_singularity=False, use_env_modules=False, singularity_args="", conda_prefix=None, list_conda_envs=False, singularity_prefix=None, shadow_prefix=None, create_envs_only=False, mode=Mode.default, wrapper_prefix=None, kubernetes=None, kubernetes_envvars=None, container_image=None, tibanna=False, tibanna_sfn=None, precommand="", default_remote_provider=None, default_remote_prefix="", assume_shared_fs=True, cluster_status=None, export_cwl=None, show_failed_logs=False, keep_incomplete=False, messaging=None, ): """Run snakemake on a given snakefile. This function provides access to the whole snakemake functionality. It is not thread-safe. Args: snakefile (str): the path to the snakefile batch (Batch): whether to compute only a partial DAG, defined by the given Batch object (default None) report (str): create an HTML report for a previous run at the given path listrules (bool): list rules (default False) list_target_rules (bool): list target rules (default False) cores (int): the number of provided cores (ignored when using cluster support) (default 1) nodes (int): the number of provided cluster nodes (ignored without cluster support) (default 1) local_cores (int): the number of provided local cores if in cluster mode (ignored without cluster support) (default 1) resources (dict): provided resources, a dictionary assigning integers to resource names, e.g. {gpu=1, io=5} (default {}) default_resources (DefaultResources): default values for resources not defined in rules (default None) config (dict): override values for workflow config workdir (str): path to working directory (default None) targets (list): list of targets, e.g. rule or file names (default None) dryrun (bool): only dry-run the workflow (default False) touch (bool): only touch all output files if present (default False) forcetargets (bool): force given targets to be re-created (default False) forceall (bool): force all output files to be re-created (default False) forcerun (list): list of files and rules that shall be re-created/re-executed (default []) prioritytargets (list): list of targets that shall be run with maximum priority (default []) stats (str): path to file that shall contain stats about the workflow execution (default None) printreason (bool): print the reason for the execution of each job (default false) printshellcmds (bool): print the shell command of each job (default False) printdag (bool): print the dag in the graphviz dot language (default False) printrulegraph (bool): print the graph of rules in the graphviz dot language (default False) printfilegraph (bool): print the graph of rules with their input and output files in the graphviz dot language (default False) printd3dag (bool): print a D3.js compatible JSON representation of the DAG (default False) nocolor (bool): do not print colored output (default False) quiet (bool): do not print any default job information (default False) keepgoing (bool): keep goind upon errors (default False) cluster (str): submission command of a cluster or batch system to use, e.g. qsub (default None) cluster_config (str,list): configuration file for cluster options, or list thereof (default None) cluster_sync (str): blocking cluster submission command (like SGE 'qsub -sync y') (default None) drmaa (str): if not None use DRMAA for cluster support, str specifies native args passed to the cluster when submitting a job drmaa_log_dir (str): the path to stdout and stderr output of DRMAA jobs (default None) jobname (str): naming scheme for cluster job scripts (default "snakejob.{rulename}.{jobid}.sh") immediate_submit (bool): immediately submit all cluster jobs, regardless of dependencies (default False) standalone (bool): kill all processes very rudely in case of failure (do not use this if you use this API) (default False) (deprecated) ignore_ambiguity (bool): ignore ambiguous rules and always take the first possible one (default False) snakemakepath (str): deprecated parameter whose value is ignored. Do not use. lock (bool): lock the working directory when executing the workflow (default True) unlock (bool): just unlock the working directory (default False) cleanup_metadata (list): just cleanup metadata of given list of output files (default None) cleanup_conda (bool): just cleanup unused conda environments (default False) cleanup_shadow (bool): just cleanup old shadow directories (default False) cleanup_scripts (bool): delete wrapper scripts used for execution (default True) force_incomplete (bool): force the re-creation of incomplete files (default False) ignore_incomplete (bool): ignore incomplete files (default False) list_version_changes (bool): list output files with changed rule version (default False) list_code_changes (bool): list output files with changed rule code (default False) list_input_changes (bool): list output files with changed input files (default False) list_params_changes (bool): list output files with changed params (default False) list_untracked (bool): list files in the workdir that are not used in the workflow (default False) summary (bool): list summary of all output files and their status (default False) archive (str): archive workflow into the given tarball delete_all_output (bool) remove all files generated by the workflow (default False) delete_temp_output (bool) remove all temporary files generated by the workflow (default False) latency_wait (int): how many seconds to wait for an output file to appear after the execution of a job, e.g. to handle filesystem latency (default 3) wait_for_files (list): wait for given files to be present before executing the workflow list_resources (bool): list resources used in the workflow (default False) summary (bool): list summary of all output files and their status (default False). If no option is specified a basic summary will be ouput. If 'detailed' is added as an option e.g --summary detailed, extra info about the input and shell commands will be included detailed_summary (bool): list summary of all input and output files and their status (default False) print_compilation (bool): print the compilation of the snakefile (default False) debug (bool): allow to use the debugger within rules notemp (bool): ignore temp file flags, e.g. do not delete output files marked as temp after use (default False) keep_remote_local (bool): keep local copies of remote files (default False) nodeps (bool): ignore dependencies (default False) keep_target_files (bool): do not adjust the paths of given target files relative to the working directory. allowed_rules (set): restrict allowed rules to the given set. If None or empty, all rules are used. jobscript (str): path to a custom shell script template for cluster jobs (default None) greediness (float): set the greediness of scheduling. This value between 0 and 1 determines how careful jobs are selected for execution. The default value (0.5 if prioritytargets are used, 1.0 else) provides the best speed and still acceptable scheduling quality. overwrite_shellcmd (str): a shell command that shall be executed instead of those given in the workflow. This is for debugging purposes only. updated_files(list): a list that will be filled with the files that are updated or created during the workflow execution verbose (bool): show additional debug output (default False) max_jobs_per_second (int): maximal number of cluster/drmaa jobs per second, None to impose no limit (default None) restart_times (int): number of times to restart failing jobs (default 0) attempt (int): initial value of Job.attempt. This is intended for internal use only (default 1). force_use_threads: whether to force use of threads over processes. helpful if shared memory is full or unavailable (default False) use_conda (bool): use conda environments for each job (defined with conda directive of rules) use_singularity (bool): run jobs in singularity containers (if defined with singularity directive) use_env_modules (bool): load environment modules if defined in rules singularity_args (str): additional arguments to pass to singularity conda_prefix (str): the directory in which conda environments will be created (default None) singularity_prefix (str): the directory to which singularity images will be pulled (default None) shadow_prefix (str): prefix for shadow directories. The job-specific shadow directories will be created in $SHADOW_PREFIX/shadow/ (default None) create_envs_only (bool): if specified, only builds the conda environments specified for each job, then exits. list_conda_envs (bool): list conda environments and their location on disk. mode (snakemake.common.Mode): execution mode wrapper_prefix (str): prefix for wrapper script URLs (default None) kubernetes (str): submit jobs to kubernetes, using the given namespace. kubernetes_envvars (list): environment variables that shall be passed to kubernetes jobs. container_image (str): Docker image to use, e.g., for kubernetes. default_remote_provider (str): default remote provider to use instead of local files (e.g. S3, GS) default_remote_prefix (str): prefix for default remote provider (e.g. name of the bucket). tibanna (str): submit jobs to AWS cloud using Tibanna. tibanna_sfn (str): Step function (Unicorn) name of Tibanna (e.g. tibanna_unicorn_monty). This must be deployed first using tibanna cli. precommand (str): commands to run on AWS cloud before the snakemake command (e.g. wget, git clone, unzip, etc). Use with --tibanna. assume_shared_fs (bool): assume that cluster nodes share a common filesystem (default true). cluster_status (str): status command for cluster execution. If None, Snakemake will rely on flag files. Otherwise, it expects the command to return "success", "failure" or "running" when executing with a cluster jobid as single argument. export_cwl (str): Compile workflow to CWL and save to given file log_handler (function): redirect snakemake output to this custom log handler, a function that takes a log message dictionary (see below) as its only argument (default None). The log message dictionary for the log handler has to following entries: keep_incomplete (bool): keep incomplete output files of failed jobs log_handler (list): redirect snakemake output to this list of custom log handler, each a function that takes a log message dictionary (see below) as its only argument (default []). The log message dictionary for the log handler has to following entries: :level: the log level ("info", "error", "debug", "progress", "job_info") :level="info", "error" or "debug": :msg: the log message :level="progress": :done: number of already executed jobs :total: number of total jobs :level="job_info": :input: list of input files of a job :output: list of output files of a job :log: path to log file of a job :local: whether a job is executed locally (i.e. ignoring cluster) :msg: the job message :reason: the job reason :priority: the job priority :threads: the threads of the job Returns: bool: True if workflow execution was successful. """ assert not immediate_submit or ( immediate_submit and notemp ), "immediate_submit has to be combined with notemp (it does not support temp file handling)" if tibanna: assume_shared_fs = False default_remote_provider = "S3" default_remote_prefix = default_remote_prefix.rstrip("/") assert ( default_remote_prefix ), "default_remote_prefix needed if tibanna is specified" assert tibanna_sfn, "tibanna_sfn needed if tibanna is specified" if updated_files is None: updated_files = list() if cluster or cluster_sync or drmaa or tibanna: cores = sys.maxsize else: nodes = sys.maxsize if isinstance(cluster_config, str): # Loading configuration from one file is still supported for # backward compatibility cluster_config = [cluster_config] if cluster_config: # Load all configuration files configs = [load_configfile(f) for f in cluster_config] # Merge in the order as specified, overriding earlier values with # later ones cluster_config_content = configs[0] for other in configs[1:]: update_config(cluster_config_content, other) else: cluster_config_content = dict() run_local = not (cluster or cluster_sync or drmaa or kubernetes or tibanna) if run_local and not dryrun: # clean up all previously recorded jobids. shell.cleanup() # force thread use for any kind of cluster use_threads = ( force_use_threads or (os.name != "posix") or cluster or cluster_sync or drmaa ) if not keep_logger: stdout = ( ( dryrun and not (printdag or printd3dag or printrulegraph or printfilegraph) ) or listrules or list_target_rules or list_resources ) setup_logger( handler=log_handler, quiet=quiet, printreason=printreason, printshellcmds=printshellcmds, debug_dag=debug_dag, nocolor=nocolor, stdout=stdout, debug=verbose, use_threads=use_threads, mode=mode, show_failed_logs=show_failed_logs, ) if greediness is None: greediness = 0.5 if prioritytargets else 1.0 else: if not (0 <= greediness <= 1.0): logger.error("Error: greediness must be a float between 0 and 1.") return False if not os.path.exists(snakefile): logger.error('Error: Snakefile "{}" not found.'.format(snakefile)) return False snakefile = os.path.abspath(snakefile) cluster_mode = ( (cluster is not None) + (cluster_sync is not None) + (drmaa is not None) ) if cluster_mode > 1: logger.error("Error: cluster and drmaa args are mutually exclusive") return False if debug and (cores > 1 or cluster_mode): logger.error( "Error: debug mode cannot be used with more than one core or cluster execution." ) return False overwrite_config = dict() if configfiles is None: configfiles = [] for f in configfiles: # get values to override. Later configfiles override earlier ones. overwrite_config.update(load_configfile(f)) # convert provided paths to absolute paths configfiles = list(map(os.path.abspath, configfiles)) # directly specified elements override any configfiles if config: overwrite_config.update(config) if config_args is None: config_args = unparse_config(config) if workdir: olddir = os.getcwd() if not os.path.exists(workdir): logger.info("Creating specified working directory {}.".format(workdir)) os.makedirs(workdir) workdir = os.path.abspath(workdir) os.chdir(workdir) logger.setup_logfile() try: # handle default remote provider _default_remote_provider = None if default_remote_provider is not None: try: rmt = importlib.import_module( "snakemake.remote." + default_remote_provider ) except ImportError as e: raise WorkflowError("Unknown default remote provider.") if rmt.RemoteProvider.supports_default: _default_remote_provider = rmt.RemoteProvider( keep_local=True, is_default=True ) else: raise WorkflowError( "Remote provider {} does not (yet) support to " "be used as default provider." ) workflow = Workflow( snakefile=snakefile, jobscript=jobscript, overwrite_shellcmd=overwrite_shellcmd, overwrite_config=overwrite_config, overwrite_workdir=workdir, overwrite_configfiles=configfiles, overwrite_clusterconfig=cluster_config_content, overwrite_threads=overwrite_threads, config_args=config_args, debug=debug, verbose=verbose, use_conda=use_conda or list_conda_envs or cleanup_conda, use_singularity=use_singularity, use_env_modules=use_env_modules, conda_prefix=conda_prefix, singularity_prefix=singularity_prefix, shadow_prefix=shadow_prefix, singularity_args=singularity_args, mode=mode, wrapper_prefix=wrapper_prefix, printshellcmds=printshellcmds, restart_times=restart_times, attempt=attempt, default_remote_provider=_default_remote_provider, default_remote_prefix=default_remote_prefix, run_local=run_local, default_resources=default_resources, cache=cache, cores=cores, nodes=nodes, resources=resources, ) success = True workflow.include( snakefile, overwrite_first_rule=True, print_compilation=print_compilation ) workflow.check() if not print_compilation: if listrules: workflow.list_rules() elif list_target_rules: workflow.list_rules(only_targets=True) elif list_resources: workflow.list_resources() else: # if not printdag and not printrulegraph: # handle subworkflows subsnakemake = partial( snakemake, local_cores=local_cores, cache=cache, default_resources=default_resources, dryrun=dryrun, touch=touch, printreason=printreason, printshellcmds=printshellcmds, debug_dag=debug_dag, nocolor=nocolor, quiet=quiet, keepgoing=keepgoing, cluster=cluster, cluster_sync=cluster_sync, drmaa=drmaa, drmaa_log_dir=drmaa_log_dir, jobname=jobname, immediate_submit=immediate_submit, standalone=standalone, ignore_ambiguity=ignore_ambiguity, restart_times=restart_times, attempt=attempt, lock=lock, unlock=unlock, cleanup_metadata=cleanup_metadata, cleanup_conda=cleanup_conda, cleanup_shadow=cleanup_shadow, cleanup_scripts=cleanup_scripts, force_incomplete=force_incomplete, ignore_incomplete=ignore_incomplete, latency_wait=latency_wait, verbose=verbose, notemp=notemp, keep_remote_local=keep_remote_local, nodeps=nodeps, jobscript=jobscript, greediness=greediness, no_hooks=no_hooks, overwrite_shellcmd=overwrite_shellcmd, config=config, config_args=config_args, cluster_config=cluster_config, keep_logger=True, force_use_threads=use_threads, use_conda=use_conda, use_singularity=use_singularity, use_env_modules=use_env_modules, conda_prefix=conda_prefix, singularity_prefix=singularity_prefix, shadow_prefix=shadow_prefix, singularity_args=singularity_args, list_conda_envs=list_conda_envs, kubernetes=kubernetes, kubernetes_envvars=kubernetes_envvars, container_image=container_image, create_envs_only=create_envs_only, default_remote_provider=default_remote_provider, default_remote_prefix=default_remote_prefix, tibanna=tibanna, tibanna_sfn=tibanna_sfn, precommand=precommand, assume_shared_fs=assume_shared_fs, cluster_status=cluster_status, max_jobs_per_second=max_jobs_per_second, max_status_checks_per_second=max_status_checks_per_second, ) success = workflow.execute( targets=targets, dryrun=dryrun, touch=touch, local_cores=local_cores, forcetargets=forcetargets, forceall=forceall, forcerun=forcerun, prioritytargets=prioritytargets, until=until, omit_from=omit_from, quiet=quiet, keepgoing=keepgoing, printshellcmds=printshellcmds, printreason=printreason, printrulegraph=printrulegraph, printfilegraph=printfilegraph, printdag=printdag, cluster=cluster, cluster_sync=cluster_sync, jobname=jobname, drmaa=drmaa, drmaa_log_dir=drmaa_log_dir, kubernetes=kubernetes, kubernetes_envvars=kubernetes_envvars, container_image=container_image, tibanna=tibanna, tibanna_sfn=tibanna_sfn, precommand=precommand, max_jobs_per_second=max_jobs_per_second, max_status_checks_per_second=max_status_checks_per_second, printd3dag=printd3dag, immediate_submit=immediate_submit, ignore_ambiguity=ignore_ambiguity, stats=stats, force_incomplete=force_incomplete, ignore_incomplete=ignore_incomplete, list_version_changes=list_version_changes, list_code_changes=list_code_changes, list_input_changes=list_input_changes, list_params_changes=list_params_changes, list_untracked=list_untracked, list_conda_envs=list_conda_envs, summary=summary, archive=archive, delete_all_output=delete_all_output, delete_temp_output=delete_temp_output, latency_wait=latency_wait, wait_for_files=wait_for_files, detailed_summary=detailed_summary, nolock=not lock, unlock=unlock, notemp=notemp, keep_remote_local=keep_remote_local, nodeps=nodeps, keep_target_files=keep_target_files, cleanup_metadata=cleanup_metadata, cleanup_conda=cleanup_conda, cleanup_shadow=cleanup_shadow, cleanup_scripts=cleanup_scripts, subsnakemake=subsnakemake, updated_files=updated_files, allowed_rules=allowed_rules, greediness=greediness, no_hooks=no_hooks, force_use_threads=use_threads, create_envs_only=create_envs_only, assume_shared_fs=assume_shared_fs, cluster_status=cluster_status, report=report, export_cwl=export_cwl, batch=batch, keepincomplete=keep_incomplete, ) except BrokenPipeError: # ignore this exception and stop. It occurs if snakemake output is piped into less and less quits before reading the whole output. # in such a case, snakemake shall stop scheduling and quit with error 1 success = False except (Exception, BaseException) as ex: if "workflow" in locals(): print_exception(ex, workflow.linemaps) else: print_exception(ex, dict()) success = False if workdir: os.chdir(olddir) if "workflow" in locals() and workflow.persistence: workflow.persistence.unlock() if not keep_logger: logger.cleanup() return success def parse_set_threads(args): errmsg = "Invalid threads definition: entries have to be defined as RULE=THREADS pairs (with THREADS being a positive integer)." overwrite_threads = dict() if args.set_threads is not None: for entry in args.set_threads: rule, threads = parse_key_value_arg(entry, errmsg=errmsg) try: threads = int(threads) except ValueError: raise ValueError(errmsg) if threads < 0: raise ValueError(errmsg) overwrite_threads[rule] = threads return overwrite_threads def parse_batch(args): errmsg = "Invalid batch definition: batch entry has to be defined as RULE=BATCH/BATCHES (with integers BATCH <= BATCHES, BATCH >= 1)." if args.batch is not None: rule, batchdef = parse_key_value_arg(args.batch, errmsg=errmsg) try: batch, batches = batchdef.split("/") batch = int(batch) batches = int(batches) except ValueError: raise ValueError(errmsg) if batch > batches or batch < 1: raise ValueError(errmsg) return Batch(rule, batch, batches) return None def parse_key_value_arg(arg, errmsg): try: key, val = arg.split("=", 1) except ValueError: raise ValueError(errmsg) return key, val def parse_config(args): """Parse config from args.""" parsers = [int, float, eval, str] config = dict() if args.config is not None: valid = re.compile(r"[a-zA-Z_]\w*$") for entry in args.config: key, val = parse_key_value_arg( entry, errmsg="Invalid config definition: Config entries have to be defined as name=value pairs.", ) if not valid.match(key): raise ValueError( "Invalid config definition: Config entry must start with a valid identifier." ) v = None for parser in parsers: try: v = parser(val) # avoid accidental interpretation as function if not callable(v): break except: pass assert v is not None config[key] = v return config def unparse_config(config): if not isinstance(config, dict): raise ValueError("config is not a dict") items = [] for key, value in config.items(): if isinstance(value, dict): raise ValueError("config may only be a flat dict") encoded = "'{}'".format(value) if isinstance(value, str) else value items.append("{}={}".format(key, encoded)) return items APPDIRS = None def get_appdirs(): global APPDIRS if APPDIRS is None: from appdirs import AppDirs APPDIRS = AppDirs("snakemake", "snakemake") return APPDIRS def get_profile_file(profile, file, return_default=False): dirs = get_appdirs() if os.path.isabs(profile): search_dirs = [os.path.dirname(profile)] profile = os.path.basename(profile) else: search_dirs = [os.getcwd(), dirs.user_config_dir, dirs.site_config_dir] get_path = lambda d: os.path.join(d, profile, file) for d in search_dirs: p = get_path(d) if os.path.exists(p): return p if return_default: return file return None def get_argument_parser(profile=None): """Generate and return argument parser.""" import configargparse from configargparse import YAMLConfigFileParser dirs = get_appdirs() config_files = [] if profile: if profile == "": print("Error: invalid profile name.", file=sys.stderr) exit(1) config_file = get_profile_file(profile, "config.yaml") if config_file is None: print( "Error: profile given but no config.yaml found. " "Profile has to be given as either absolute path, relative " "path or name of a directory available in either " "{site} or {user}.".format( site=dirs.site_config_dir, user=dirs.user_config_dir ), file=sys.stderr, ) exit(1) config_files = [config_file] parser = configargparse.ArgumentParser( description="Snakemake is a Python based language and execution " "environment for GNU Make-like workflows.", default_config_files=config_files, config_file_parser_class=YAMLConfigFileParser, ) group_exec = parser.add_argument_group("EXECUTION") group_exec.add_argument( "target", nargs="*", default=None, help="Targets to build. May be rules or files.", ) group_exec.add_argument( "--dry-run", "--dryrun", "-n", dest="dryrun", action="store_true", help="Do not execute anything, and display what would be done. " "If you have a very large workflow, use --dry-run --quiet to just " "print a summary of the DAG of jobs.", ) group_exec.add_argument( "--profile", help=""" Name of profile to use for configuring Snakemake. Snakemake will search for a corresponding folder in {} and {}. Alternatively, this can be an absolute or relative path. The profile folder has to contain a file 'config.yaml'. This file can be used to set default values for command line options in YAML format. For example, '--cluster qsub' becomes 'cluster: qsub' in the YAML file. Profiles can be obtained from https://github.com/snakemake-profiles. """.format( dirs.site_config_dir, dirs.user_config_dir ), ) group_exec.add_argument( "--cache", nargs="+", metavar="RULE", help="Store output files of given rules in a central cache given by the environment " "variable $SNAKEMAKE_OUTPUT_CACHE. Likewise, retrieve output files of the given rules " "from this cache if they have been created before (by anybody writing to the same cache), " "instead of actually executing the rules. Output files are identified by hashing all " "steps, parameters and software stack (conda envs or containers) needed to create them.", ) group_exec.add_argument( "--snakefile", "-s", metavar="FILE", help=( "The workflow definition in form of a snakefile." "Usually, you should not need to specify this. " "By default, Snakemake will search for {} " "beneath the current working " "directory, in this order. " "Only if you definitely want a different layout, " "you need to use this parameter." ).format(", ".join(map("'{}'".format, SNAKEFILE_CHOICES))), ) group_exec.add_argument( "--cores", "--jobs", "-j", action="store", const=available_cpu_count(), nargs="?", metavar="N", help=( "Use at most N cores in parallel. " "If N is omitted or 'all', the limit is set to the number of " "available cores." ), ) group_exec.add_argument( "--local-cores", action="store", default=available_cpu_count(), metavar="N", type=int, help=( "In cluster mode, use at most N cores of the host machine in parallel " " (default: number of CPU cores of the host). The cores are used to execute " "local rules. This option is ignored when not in cluster mode." ), ) group_exec.add_argument( "--resources", "--res", nargs="*", metavar="NAME=INT", help=( "Define additional resources that shall constrain the scheduling " "analogously to threads (see above). A resource is defined as " "a name and an integer value. E.g. --resources gpu=1. Rules can " "use resources by defining the resource keyword, e.g. " "resources: gpu=1. If now two rules require 1 of the resource " "'gpu' they won't be run in parallel by the scheduler." ), ) group_exec.add_argument( "--set-threads", metavar="RULE=THREADS", nargs="*", help="Overwrite thread usage of rules. This allows to fine-tune workflow " "parallelization. In particular, this is helpful to target certain cluster nodes " "by e.g. shifting a rule to use more, or less threads than defined in the workflow. " "Thereby, THREADS has to be a positive integer, and RULE has to be the name of the rule.", ) group_exec.add_argument( "--default-resources", "--default-res", nargs="*", metavar="NAME=INT", help=( "Define default values of resources for rules that do not define their own values. " "In addition to plain integers, python expressions over inputsize are allowed (e.g. '2*input.size')." "When specifying this without any arguments (--default-resources), it defines 'mem_mb=max(2*input.size, 1000)' " "'disk_mb=max(2*input.size, 1000)', i.e., default disk and mem usage is twice the input file size but at least 1GB." ), ) group_exec.add_argument( "--config", "-C", nargs="*", metavar="KEY=VALUE", help=( "Set or overwrite values in the workflow config object. " "The workflow config object is accessible as variable config inside " "the workflow. Default values can be set by providing a JSON file " "(see Documentation)." ), ) group_exec.add_argument( "--configfile", "--configfiles", nargs="+", metavar="FILE", help=( "Specify or overwrite the config file of the workflow (see the docs). " "Values specified in JSON or YAML format are available in the global config " "dictionary inside the workflow. Multiple files overwrite each other in " "the given order." ), ) group_exec.add_argument( "--directory", "-d", metavar="DIR", action="store", help=( "Specify working directory (relative paths in " "the snakefile will use this as their origin)." ), ) group_exec.add_argument( "--touch", "-t", action="store_true", help=( "Touch output files (mark them up to date without really " "changing them) instead of running their commands. This is " "used to pretend that the rules were executed, in order to " "fool future invocations of snakemake. Fails if a file does " "not yet exist. Note that this will only touch files that would " "otherwise be recreated by Snakemake (e.g. because their input " "files are newer). For enforcing a touch, combine this with " "--force, --forceall, or --forcerun. Note however that you loose " "the provenance information when the files have been created in " "realitiy. Hence, this should be used only as a last resort." ), ) group_exec.add_argument( "--keep-going", "-k", action="store_true", help="Go on with independent jobs if a job fails.", ) group_exec.add_argument( "--force", "-f", action="store_true", help=( "Force the execution of the selected target or the first rule " "regardless of already created output." ), ) group_exec.add_argument( "--forceall", "-F", action="store_true", help=( "Force the execution of the selected (or the first) rule and " "all rules it is dependent on regardless of already created " "output." ), ) group_exec.add_argument( "--forcerun", "-R", nargs="*", metavar="TARGET", help=( "Force the re-execution or creation of the given rules or files." " Use this option if you changed a rule and want to have all its " "output in your workflow updated." ), ) group_exec.add_argument( "--prioritize", "-P", nargs="+", metavar="TARGET", help=( "Tell the scheduler to assign creation of given targets " "(and all their dependencies) highest priority. (EXPERIMENTAL)" ), ) group_exec.add_argument( "--batch", metavar="RULE=BATCH/BATCHES", help=( "Only create the given BATCH of the input files of the given RULE. " "This can be used to iteratively run parts of very large workflows. " "Only the execution plan of the relevant part of the workflow has to " "be calculated, thereby speeding up DAG computation. " "It is recommended to provide the most suitable rule for batching when " "documenting a workflow. It should be some aggregating rule that " "would be executed only once, and has a large number of input files. " "For example, it can be a rule that aggregates over samples." ), ) group_exec.add_argument( "--until", "-U", nargs="+", metavar="TARGET", help=( "Runs the pipeline until it reaches the specified rules or " "files. Only runs jobs that are dependencies of the specified " "rule or files, does not run sibling DAGs. " ), ) group_exec.add_argument( "--omit-from", "-O", nargs="+", metavar="TARGET", help=( "Prevent the execution or creation of the given rules or files " "as well as any rules or files that are downstream of these targets " "in the DAG. Also runs jobs in sibling DAGs that are independent of the " "rules or files specified here." ), ) group_exec.add_argument( "--rerun-incomplete", "--ri", action="store_true", help=("Re-run all " "jobs the output of which is recognized as incomplete."), ) group_exec.add_argument( "--shadow-prefix", metavar="DIR", help=( "Specify a directory in which the 'shadow' directory is created. " "If not supplied, the value is set to the '.snakemake' directory relative " "to the working directory." ), ) group_utils = parser.add_argument_group("UTILITIES") group_utils.add_argument( "--report", nargs="?", const="report.html", metavar="HTMLFILE", help="Create an HTML report with results and statistics. " "If no filename is given, report.html is the default.", ) group_utils.add_argument( "--export-cwl", action="store", metavar="FILE", help="Compile workflow to CWL and store it in given FILE.", ) group_utils.add_argument( "--list", "-l", action="store_true", help="Show available rules in given Snakefile.", ) group_utils.add_argument( "--list-target-rules", "--lt", action="store_true", help="Show available target rules in given Snakefile.", ) group_utils.add_argument( "--dag", action="store_true", help="Do not execute anything and print the directed " "acyclic graph of jobs in the dot language. Recommended " "use on Unix systems: snakemake --dag | dot | display", ) group_utils.add_argument( "--rulegraph", action="store_true", help="Do not execute anything and print the dependency graph " "of rules in the dot language. This will be less " "crowded than above DAG of jobs, but also show less information. " "Note that each rule is displayed once, hence the displayed graph will be " "cyclic if a rule appears in several steps of the workflow. " "Use this if above option leads to a DAG that is too large. " "Recommended use on Unix systems: snakemake --rulegraph | dot | display", ) group_utils.add_argument( "--filegraph", action="store_true", help="Do not execute anything and print the dependency graph " "of rules with their input and output files in the dot language. " "This is an intermediate solution between above DAG of jobs and the rule graph. " "Note that each rule is displayed once, hence the displayed graph will be " "cyclic if a rule appears in several steps of the workflow. " "Use this if above option leads to a DAG that is too large. " "Recommended use on Unix systems: snakemake --filegraph | dot | display", ) group_utils.add_argument( "--d3dag", action="store_true", help="Print the DAG in D3.js compatible JSON format.", ) group_utils.add_argument( "--summary", "-S", action="store_true", help="Print a summary of all files created by the workflow. The " "has the following columns: filename, modification time, " "rule version, status, plan.\n" "Thereby rule version contains the version" "the file was created with (see the version keyword of rules), and " "status denotes whether the file is missing, its input files are " "newer or if version or implementation of the rule changed since " "file creation. Finally the last column denotes whether the file " "will be updated or created during the next workflow execution.", ) group_utils.add_argument( "--detailed-summary", "-D", action="store_true", help="Print a summary of all files created by the workflow. The " "has the following columns: filename, modification time, " "rule version, input file(s), shell command, status, plan.\n" "Thereby rule version contains the version " "the file was created with (see the version keyword of rules), and " "status denotes whether the file is missing, its input files are " "newer or if version or implementation of the rule changed since " "file creation. The input file and shell command columns are self " "explanatory. Finally the last column denotes whether the file " "will be updated or created during the next workflow execution.", ) group_utils.add_argument( "--archive", metavar="FILE", help="Archive the workflow into the given tar archive FILE. The archive " "will be created such that the workflow can be re-executed on a vanilla " "system. The function needs conda and git to be installed. " "It will archive every file that is under git version control. " "Note that it is best practice to have the Snakefile, config files, and " "scripts under version control. Hence, they will be included in the archive. " "Further, it will add input files that are not generated by " "by the workflow itself and conda environments. Note that symlinks are " "dereferenced. Supported " "formats are .tar, .tar.gz, .tar.bz2 and .tar.xz.", ) group_utils.add_argument( "--cleanup-metadata", "--cm", nargs="+", metavar="FILE", help="Cleanup the metadata " "of given files. That means that snakemake removes any tracked " "version info, and any marks that files are incomplete.", ) group_utils.add_argument( "--cleanup-shadow", action="store_true", help="Cleanup old shadow directories which have not been deleted due " "to failures or power loss.", ) group_utils.add_argument( "--skip-script-cleanup", action="store_true", help="Don't delete wrapper scripts used for execution", ) group_utils.add_argument( "--unlock", action="store_true", help="Remove a lock on the working directory." ) group_utils.add_argument( "--list-version-changes", "--lv", action="store_true", help="List all output files that have been created with " "a different version (as determined by the version keyword).", ) group_utils.add_argument( "--list-code-changes", "--lc", action="store_true", help="List all output files for which the rule body (run or shell) have " "changed in the Snakefile.", ) group_utils.add_argument( "--list-input-changes", "--li", action="store_true", help="List all output files for which the defined input files have changed " "in the Snakefile (e.g. new input files were added in the rule " "definition or files were renamed). For listing input file " "modification in the filesystem, use --summary.", ) group_utils.add_argument( "--list-params-changes", "--lp", action="store_true", help="List all output files for which the defined params have changed " "in the Snakefile.", ) group_utils.add_argument( "--list-untracked", "--lu", action="store_true", help="List all files in the working directory that are not used in the " "workflow. This can be used e.g. for identifying leftover files. Hidden files " "and directories are ignored.", ) group_utils.add_argument( "--delete-all-output", action="store_true", help="Remove all files generated by the workflow. Use together with --dry-run " "to list files without actually deleting anything. Note that this will " "not recurse into subworkflows. Write-protected files are not removed. " "Nevertheless, use with care!", ) group_utils.add_argument( "--delete-temp-output", action="store_true", help="Remove all temporary files generated by the workflow. Use together " "with --dry-run to list files without actually deleting anything. Note " "that this will not recurse into subworkflows.", ) group_utils.add_argument( "--bash-completion", action="store_true", help="Output code to register bash completion for snakemake. Put the " "following in your .bashrc (including the accents): " "`snakemake --bash-completion` or issue it in an open terminal " "session.", ) group_utils.add_argument( "--keep-incomplete", action="store_true", help="Do not remove incomplete output files by failed jobs.", ) group_utils.add_argument("--version", "-v", action="version", version=__version__) group_output = parser.add_argument_group("OUTPUT") group_output.add_argument( "--reason", "-r", action="store_true", help="Print the reason for each executed rule.", ) group_output.add_argument( "--gui", nargs="?", const="8000", metavar="PORT", type=str, help="Serve an HTML based user interface to the given network and " "port e.g. 168.129.10.15:8000. By default Snakemake is only " "available in the local network (default port: 8000). To make " "Snakemake listen to all ip addresses add the special host address " "0.0.0.0 to the url (0.0.0.0:8000). This is important if Snakemake " "is used in a virtualised environment like Docker. If possible, a " "browser window is opened.", ) group_output.add_argument( "--printshellcmds", "-p", action="store_true", help="Print out the shell commands that will be executed.", ) group_output.add_argument( "--debug-dag", action="store_true", help="Print candidate and selected jobs (including their wildcards) while " "inferring DAG. This can help to debug unexpected DAG topology or errors.", ) group_output.add_argument( "--stats", metavar="FILE", help="Write stats about Snakefile execution in JSON format to the given file.", ) group_output.add_argument( "--nocolor", action="store_true", help="Do not use a colored output." ) group_output.add_argument( "--quiet", "-q", action="store_true", help="Do not output any progress or rule information.", ) group_output.add_argument( "--print-compilation", action="store_true", help="Print the python representation of the workflow.", ) group_output.add_argument( "--verbose", action="store_true", help="Print debugging output." ) group_behavior = parser.add_argument_group("BEHAVIOR") group_behavior.add_argument( "--force-use-threads", dest="force_use_threads", action="store_true", help="Force threads rather than processes. Helpful if shared memory (/dev/shm) is full or unavailable.", ) group_behavior.add_argument( "--allow-ambiguity", "-a", action="store_true", help=( "Don't check for ambiguous rules and simply use the first if " "several can produce the same file. This allows the user to " "prioritize rules by their order in the snakefile." ), ) group_behavior.add_argument( "--nolock", action="store_true", help="Do not lock the working directory" ) group_behavior.add_argument( "--ignore-incomplete", "--ii", action="store_true", help="Do not check for incomplete output files.", ) group_behavior.add_argument( "--latency-wait", "--output-wait", "-w", type=int, default=5, metavar="SECONDS", help="Wait given seconds if an output file of a job is not present after " "the job finished. This helps if your filesystem " "suffers from latency (default 5).", ) group_behavior.add_argument( "--wait-for-files", nargs="*", metavar="FILE", help="Wait --latency-wait seconds for these " "files to be present before executing the workflow. " "This option is used internally to handle filesystem latency in cluster " "environments.", ) group_behavior.add_argument( "--notemp", "--nt", action="store_true", help="Ignore temp() declarations. This is useful when running only " "a part of the workflow, since temp() would lead to deletion of " "probably needed files by other parts of the workflow.", ) group_behavior.add_argument( "--keep-remote", action="store_true", help="Keep local copies of remote input files.", ) group_behavior.add_argument( "--keep-target-files", action="store_true", help="Do not adjust the paths of given target files relative to the working directory.", ) group_behavior.add_argument( "--allowed-rules", nargs="+", help="Only consider given rules. If omitted, all rules in Snakefile are " "used. Note that this is intended primarily for internal use and may " "lead to unexpected results otherwise.", ) group_behavior.add_argument( "--max-jobs-per-second", default=10, type=float, help="Maximal number of cluster/drmaa jobs per second, default is 10, " "fractions allowed.", ) group_behavior.add_argument( "--max-status-checks-per-second", default=10, type=float, help="Maximal number of job status checks per second, default is 10, " "fractions allowed.", ) group_behavior.add_argument( "--restart-times", default=0, type=int, help="Number of times to restart failing jobs (defaults to 0).", ) group_behavior.add_argument( "--attempt", default=1, type=int, help="Internal use only: define the initial value of the attempt " "parameter (default: 1).", ) group_behavior.add_argument( "--wrapper-prefix", default="https://github.com/snakemake/snakemake-wrappers/raw/", help="Prefix for URL created from wrapper directive (default: " "https://github.com/snakemake/snakemake-wrappers/raw/). Set this to " "a different URL to use your fork or a local clone of the repository, " "e.g., use a git URL like 'git+file://path/to/your/local/clone@'.", ) group_behavior.add_argument( "--default-remote-provider", choices=["S3", "GS", "FTP", "SFTP", "S3Mocked", "gfal", "gridftp", "iRODS"], help="Specify default remote provider to be used for " "all input and output files that don't yet specify " "one.", ) group_behavior.add_argument( "--default-remote-prefix", default="", help="Specify prefix for default remote provider. E.g. " "a bucket name.", ) group_behavior.add_argument( "--no-shared-fs", action="store_true", help="Do not assume that jobs share a common file " "system. When this flag is activated, Snakemake will " "assume that the filesystem on a cluster node is not " "shared with other nodes. For example, this will lead " "to downloading remote files on each cluster node " "separately. Further, it won't take special measures " "to deal with filesystem latency issues. This option " "will in most cases only make sense in combination with " "--default-remote-provider. Further, when using --cluster " "you will have to also provide --cluster-status. " "Only activate this if you " "know what you are doing.", ) group_behavior.add_argument( "--greediness", type=float, default=None, help="Set the greediness of scheduling. This value between 0 and 1 " "determines how careful jobs are selected for execution. The default " "value (1.0) provides the best speed and still acceptable scheduling " "quality.", ) group_behavior.add_argument( "--no-hooks", action="store_true", help="Do not invoke onstart, onsuccess or onerror hooks after execution.", ) group_behavior.add_argument( "--overwrite-shellcmd", help="Provide a shell command that shall be executed instead of those " "given in the workflow. " "This is for debugging purposes only.", ) group_behavior.add_argument( "--debug", action="store_true", help="Allow to debug rules with e.g. PDB. This flag " "allows to set breakpoints in run blocks.", ) group_behavior.add_argument( "--runtime-profile", metavar="FILE", help="Profile Snakemake and write the output to FILE. This requires yappi " "to be installed.", ) group_behavior.add_argument( "--mode", choices=[Mode.default, Mode.subprocess, Mode.cluster], default=Mode.default, type=int, help="Set execution mode of Snakemake (internal use only).", ) group_behavior.add_argument( "--show-failed-logs", action="store_true", help="Automatically display logs of failed jobs.", ) group_behavior.add_argument( "--log-handler-script", metavar="FILE", default=None, help="Provide a custom script containing a function 'def log_handler(msg):'. " "Snakemake will call this function for every logging output (given as a dictionary msg)" "allowing to e.g. send notifications in the form of e.g. slack messages or emails.", ) group_behavior.add_argument( "--log-service", default=None, choices=["none", "slack"], help="Set a specific messaging service for logging output." "Snakemake will notify the service on errors and completed execution." "Currently only slack is supported.", ) group_cluster = parser.add_argument_group("CLUSTER") # TODO extend below description to explain the wildcards that can be used cluster_mode_group = group_cluster.add_mutually_exclusive_group() cluster_mode_group.add_argument( "--cluster", "-c", metavar="CMD", help=( "Execute snakemake rules with the given submit command, " "e.g. qsub. Snakemake compiles jobs into scripts that are " "submitted to the cluster with the given command, once all input " "files for a particular job are present.\n" "The submit command can be decorated to make it aware of certain " "job properties (name, rulename, input, output, params, wildcards, log, threads " "and dependencies (see the argument below)), e.g.:\n" "$ snakemake --cluster 'qsub -pe threaded {threads}'." ), ), cluster_mode_group.add_argument( "--cluster-sync", metavar="CMD", help=( "cluster submission command will block, returning the remote exit" "status upon remote termination (for example, this should be used" "if the cluster command is 'qsub -sync y' (SGE)" ), ), cluster_mode_group.add_argument( "--drmaa", nargs="?", const="", metavar="ARGS", help="Execute snakemake on a cluster accessed via DRMAA, " "Snakemake compiles jobs into scripts that are " "submitted to the cluster with the given command, once all input " "files for a particular job are present. ARGS can be used to " "specify options of the underlying cluster system, " "thereby using the job properties name, rulename, input, output, params, wildcards, log, " "threads and dependencies, e.g.: " "--drmaa ' -pe threaded {threads}'. Note that ARGS must be given in quotes and " "with a leading whitespace.", ) group_cluster.add_argument( "--cluster-config", "-u", metavar="FILE", default=[], action="append", help=( "A JSON or YAML file that defines the wildcards used in 'cluster'" "for specific rules, instead of having them specified in the Snakefile. " "For example, for rule 'job' you may define: " "{ 'job' : { 'time' : '24:00:00' } } to specify the time for rule 'job'. " "You can specify more than one file. The configuration files are merged " "with later values overriding earlier ones. This option is deprecated in favor " "of using --profile, see docs." ), ), group_cluster.add_argument( "--immediate-submit", "--is", action="store_true", help="Immediately submit all jobs to the cluster instead of waiting " "for present input files. This will fail, unless you make " "the cluster aware of job dependencies, e.g. via:\n" "$ snakemake --cluster 'sbatch --dependency {dependencies}.\n" "Assuming that your submit script (here sbatch) outputs the " "generated job id to the first stdout line, {dependencies} will " "be filled with space separated job ids this job depends on.", ) group_cluster.add_argument( "--jobscript", "--js", metavar="SCRIPT", help="Provide a custom job script for submission to the cluster. " "The default script resides as 'jobscript.sh' in the " "installation directory.", ) group_cluster.add_argument( "--jobname", "--jn", default="snakejob.{name}.{jobid}.sh", metavar="NAME", help="Provide a custom name for the jobscript that is submitted to the " 'cluster (see --cluster). NAME is "snakejob.{name}.{jobid}.sh" ' "per default. The wildcard {jobid} has to be present in the name.", ) group_cluster.add_argument( "--cluster-status", help="Status command for cluster execution. This is only considered " "in combination with the --cluster flag. If provided, Snakemake will " "use the status command to determine if a job has finished successfully " "or failed. For this it is necessary that the submit command provided " "to --cluster returns the cluster job id. Then, the status command " "will be invoked with the job id. Snakemake expects it to return " "'success' if the job was successfull, 'failed' if the job failed and " "'running' if the job still runs.", ) group_cluster.add_argument( "--drmaa-log-dir", metavar="DIR", help="Specify a directory in which stdout and stderr files of DRMAA" " jobs will be written. The value may be given as a relative path," " in which case Snakemake will use the current invocation directory" " as the origin. If given, this will override any given '-o' and/or" " '-e' native specification. If not given, all DRMAA stdout and" " stderr files are written to the current working directory.", ) group_cloud = parser.add_argument_group("CLOUD") group_kubernetes = parser.add_argument_group("KUBERNETES") group_tibanna = parser.add_argument_group("TIBANNA") group_kubernetes.add_argument( "--kubernetes", metavar="NAMESPACE", nargs="?", const="default", help="Execute workflow in a kubernetes cluster (in the cloud). " "NAMESPACE is the namespace you want to use for your job (if nothing " "specified: 'default'). " "Usually, this requires --default-remote-provider and " "--default-remote-prefix to be set to a S3 or GS bucket where your . " "data shall be stored. It is further advisable to activate conda " "integration via --use-conda.", ) group_kubernetes.add_argument( "--kubernetes-env", nargs="+", metavar="ENVVAR", default=[], help="Specify environment variables to pass to the kubernetes job.", ) group_kubernetes.add_argument( "--container-image", metavar="IMAGE", help="Docker image to use, e.g., when submitting jobs to kubernetes. " "By default, this is 'https://hub.docker.com/r/snakemake/snakemake', tagged with " "the same version as the currently running Snakemake instance. " "Note that overwriting this value is up to your responsibility. " "Any used image has to contain a working snakemake installation " "that is compatible with (or ideally the same as) the currently " "running version.", ) group_tibanna.add_argument( "--tibanna", action="store_true", help="Execute workflow on AWS cloud using Tibanna. This requires " "--default-remote-prefix to be set to S3 bucket name and prefix" " (e.g. 'bucketname/subdirectory') where input is already stored" " and output will be sent to. Using --tibanna implies --default-resources" " is set as default. Optionally, use --precommand to" " specify any preparation command to run before snakemake command" " on the cloud (inside snakemake container on Tibanna VM)." " Also, --use-conda, --use-singularity, --config, --configfile are" " supported and will be carried over.", ) group_tibanna.add_argument( "--tibanna-sfn", help="Name of Tibanna Unicorn step function (e.g. tibanna_unicorn_monty)." "This works as serverless scheduler/resource allocator and must be " "deployed first using tibanna cli. (e.g. tibanna deploy_unicorn --usergroup=" "monty --buckets=bucketname)", ) group_tibanna.add_argument( "--precommand", help="Any command to execute before snakemake command on AWS cloud " "such as wget, git clone, unzip, etc. This is used with --tibanna." "Do not include input/output download/upload commands - file transfer" " between S3 bucket and the run environment (container) is automatically" " handled by Tibanna.", ) group_conda = parser.add_argument_group("CONDA") group_conda.add_argument( "--use-conda", action="store_true", help="If defined in the rule, run job in a conda environment. " "If this flag is not set, the conda directive is ignored.", ) group_conda.add_argument( "--list-conda-envs", action="store_true", help="List all conda environments and their location on " "disk.", ) group_conda.add_argument( "--cleanup-conda", action="store_true", help="Cleanup unused conda environments.", ) group_conda.add_argument( "--conda-prefix", metavar="DIR", help="Specify a directory in which the 'conda' and 'conda-archive' " "directories are created. These are used to store conda environments " "and their archives, respectively. If not supplied, the value is set " "to the '.snakemake' directory relative to the invocation directory. " "If supplied, the `--use-conda` flag must also be set. The value may " "be given as a relative path, which will be extrapolated to the " "invocation directory, or as an absolute path.", ) group_conda.add_argument( "--create-envs-only", action="store_true", help="If specified, only creates the job-specific " "conda environments then exits. The `--use-conda` " "flag must also be set.", ) group_singularity = parser.add_argument_group("SINGULARITY") group_singularity.add_argument( "--use-singularity", action="store_true", help="If defined in the rule, run job within a singularity container. " "If this flag is not set, the singularity directive is ignored.", ) group_singularity.add_argument( "--singularity-prefix", metavar="DIR", help="Specify a directory in which singularity images will be stored." "If not supplied, the value is set " "to the '.snakemake' directory relative to the invocation directory. " "If supplied, the `--use-singularity` flag must also be set. The value " "may be given as a relative path, which will be extrapolated to the " "invocation directory, or as an absolute path.", ) group_singularity.add_argument( "--singularity-args", default="", metavar="ARGS", help="Pass additional args to singularity.", ) group_env_modules = parser.add_argument_group("ENVIRONMENT MODULES") group_env_modules.add_argument( "--use-envmodules", action="store_true", help="If defined in the rule, run job within the given environment " "modules, loaded in the given order. This can be combined with " "--use-conda and --use-singularity, which will then be only used as a " "fallback for rules which don't define environment modules.", ) return parser def main(argv=None): """Main entry point.""" parser = get_argument_parser() args = parser.parse_args(argv) if args.profile: # reparse args while inferring config file from profile parser = get_argument_parser(args.profile) args = parser.parse_args(argv) def adjust_path(f): if os.path.exists(f) or os.path.isabs(f): return f else: return get_profile_file(args.profile, f, return_default=True) # update file paths to be relative to the profile # (if they do not exist relative to CWD) if args.jobscript: args.jobscript = adjust_path(args.jobscript) if args.cluster: args.cluster = adjust_path(args.cluster) if args.cluster_sync: args.cluster_sync = adjust_path(args.cluster_sync) if args.cluster_status: args.cluster_status = adjust_path(args.cluster_status) if args.bash_completion: cmd = b"complete -o bashdefault -C snakemake-bash-completion snakemake" sys.stdout.buffer.write(cmd) sys.exit(0) if args.batch is not None and args.forceall: print( "--batch may not be combined with --forceall, because recomputed upstream " "jobs in subsequent batches may render already obtained results outdated." ) try: resources = parse_resources(args.resources) config = parse_config(args) if (args.default_resources is not None and not args.default_resources) or ( args.tibanna and not args.default_resources ): args.default_resources = [ "mem_mb=max(2*input.size, 1000)", "disk_mb=max(2*input.size, 1000)", ] default_resources = DefaultResources(args.default_resources) batch = parse_batch(args) overwrite_threads = parse_set_threads(args) except ValueError as e: print(e, file=sys.stderr) print("", file=sys.stderr) sys.exit(1) if args.cores is not None: if args.cores == "all": args.cores = available_cpu_count() else: try: args.cores = int(args.cores) except ValueError: print( "Error parsing number of cores (--cores, --jobs, -j): must be integer, empty, or 'all'.", file=sys.stderr, ) sys.exit(1) if args.cluster or args.cluster_sync or args.drmaa: if args.cores is None: if args.dryrun: args.cores = 1 else: print( "Error: you need to specify the maximum number of jobs to " "be queued or executed at the same time with --jobs.", file=sys.stderr, ) sys.exit(1) elif args.cores is None: # if nothing specified, use all avaiable cores args.cores = available_cpu_count() if args.drmaa_log_dir is not None: if not os.path.isabs(args.drmaa_log_dir): args.drmaa_log_dir = os.path.abspath(os.path.expanduser(args.drmaa_log_dir)) if args.runtime_profile: import yappi yappi.start() if args.immediate_submit and not args.notemp: print( "Error: --immediate-submit has to be combined with --notemp, " "because temp file handling is not supported in this mode.", file=sys.stderr, ) sys.exit(1) if (args.conda_prefix or args.create_envs_only) and not args.use_conda: print( "Error: --use-conda must be set if --conda-prefix or " "--create-envs-only is set.", file=sys.stderr, ) sys.exit(1) if args.singularity_prefix and not args.use_singularity: print( "Error: --use_singularity must be set if --singularity-prefix " "is set.", file=sys.stderr, ) sys.exit(1) if args.kubernetes and ( not args.default_remote_provider or not args.default_remote_prefix ): print( "Error: --kubernetes must be combined with " "--default-remote-provider and --default-remote-prefix, see " "https://snakemake.readthedocs.io/en/stable/executable.html" "#executing-a-snakemake-workflow-via-kubernetes", file=sys.stderr, ) sys.exit(1) if args.tibanna: if not args.default_remote_prefix: print( "Error: --tibanna must be combined with --default-remote-prefix " "to provide bucket name and subdirectory (prefix) " "(e.g. 'bucketname/projectname'", file=sys.stderr, ) sys.exit(1) args.default_remote_prefix = args.default_remote_prefix.rstrip("/") if not args.tibanna_sfn: args.tibanna_sfn = os.environ.get("TIBANNA_DEFAULT_STEP_FUNCTION_NAME", "") if not args.tibanna_sfn: print( "Error: to use --tibanna, either --tibanna-sfn or environment variable " "TIBANNA_DEFAULT_STEP_FUNCTION_NAME must be set and exported " "to provide name of the tibanna unicorn step function " "(e.g. 'tibanna_unicorn_monty'). The step function must be deployed first " "using tibanna cli (e.g. tibanna deploy_unicorn --usergroup=monty " "--buckets=bucketname)", file=sys.stderr, ) sys.exit(1) if args.delete_all_output and args.delete_temp_output: print( "Error: --delete-all-output and --delete-temp-output are mutually exclusive.", file=sys.stderr, ) sys.exit(1) if args.snakefile is None: for p in SNAKEFILE_CHOICES: if os.path.exists(p): args.snakefile = p break if args.snakefile is None: print( "Error: no Snakefile found, tried {}.".format( ", ".join(SNAKEFILE_CHOICES), file=sys.stderr ) ) sys.exit(1) if args.gui is not None: try: import snakemake.gui as gui except ImportError: print( "Error: GUI needs Flask to be installed. Install " "with easy_install or contact your administrator.", file=sys.stderr, ) sys.exit(1) _logging.getLogger("werkzeug").setLevel(_logging.ERROR) _snakemake = partial(snakemake, os.path.abspath(args.snakefile)) gui.register(_snakemake, args) if ":" in args.gui: host, port = args.gui.split(":") else: port = args.gui host = "127.0.0.1" url = "http://{}:{}".format(host, port) print("Listening on {}.".format(url), file=sys.stderr) def open_browser(): try: webbrowser.open(url) except: pass print("Open this address in your browser to access the GUI.", file=sys.stderr) threading.Timer(0.5, open_browser).start() success = True try: gui.app.run(debug=False, threaded=True, port=int(port), host=host) except (KeyboardInterrupt, SystemExit): # silently close pass else: log_handler = [] if args.log_handler_script is not None: if not os.path.exists(args.log_handler_script): print( "Error: no log handler script found, {}.".format( args.log_handler_script ), file=sys.stderr, ) sys.exit(1) log_script = SourceFileLoader("log", args.log_handler_script).load_module() try: log_handler.append(log_script.log_handler) except: print( 'Error: Invalid log handler script, {}. Expect python function "log_handler(msg)".'.format( args.log_handler_script ), file=sys.stderr, ) sys.exit(1) if args.log_service == "slack": slack_logger = logging.SlackLogger() log_handler.append(slack_logger.log_handler) success = snakemake( args.snakefile, batch=batch, cache=args.cache, report=args.report, listrules=args.list, list_target_rules=args.list_target_rules, cores=args.cores, local_cores=args.local_cores, nodes=args.cores, resources=resources, overwrite_threads=overwrite_threads, default_resources=default_resources, config=config, configfiles=args.configfile, config_args=args.config, workdir=args.directory, targets=args.target, dryrun=args.dryrun, printshellcmds=args.printshellcmds, printreason=args.reason, debug_dag=args.debug_dag, printdag=args.dag, printrulegraph=args.rulegraph, printfilegraph=args.filegraph, printd3dag=args.d3dag, touch=args.touch, forcetargets=args.force, forceall=args.forceall, forcerun=args.forcerun, prioritytargets=args.prioritize, until=args.until, omit_from=args.omit_from, stats=args.stats, nocolor=args.nocolor, quiet=args.quiet, keepgoing=args.keep_going, cluster=args.cluster, cluster_config=args.cluster_config, cluster_sync=args.cluster_sync, drmaa=args.drmaa, drmaa_log_dir=args.drmaa_log_dir, kubernetes=args.kubernetes, kubernetes_envvars=args.kubernetes_env, container_image=args.container_image, tibanna=args.tibanna, tibanna_sfn=args.tibanna_sfn, precommand=args.precommand, jobname=args.jobname, immediate_submit=args.immediate_submit, standalone=True, ignore_ambiguity=args.allow_ambiguity, lock=not args.nolock, unlock=args.unlock, cleanup_metadata=args.cleanup_metadata, cleanup_conda=args.cleanup_conda, cleanup_shadow=args.cleanup_shadow, cleanup_scripts=not args.skip_script_cleanup, force_incomplete=args.rerun_incomplete, ignore_incomplete=args.ignore_incomplete, list_version_changes=args.list_version_changes, list_code_changes=args.list_code_changes, list_input_changes=args.list_input_changes, list_params_changes=args.list_params_changes, list_untracked=args.list_untracked, summary=args.summary, detailed_summary=args.detailed_summary, archive=args.archive, delete_all_output=args.delete_all_output, delete_temp_output=args.delete_temp_output, print_compilation=args.print_compilation, verbose=args.verbose, debug=args.debug, jobscript=args.jobscript, notemp=args.notemp, keep_remote_local=args.keep_remote, greediness=args.greediness, no_hooks=args.no_hooks, overwrite_shellcmd=args.overwrite_shellcmd, latency_wait=args.latency_wait, wait_for_files=args.wait_for_files, keep_target_files=args.keep_target_files, allowed_rules=args.allowed_rules, max_jobs_per_second=args.max_jobs_per_second, max_status_checks_per_second=args.max_status_checks_per_second, restart_times=args.restart_times, attempt=args.attempt, force_use_threads=args.force_use_threads, use_conda=args.use_conda, conda_prefix=args.conda_prefix, list_conda_envs=args.list_conda_envs, use_singularity=args.use_singularity, use_env_modules=args.use_envmodules, singularity_prefix=args.singularity_prefix, shadow_prefix=args.shadow_prefix, singularity_args=args.singularity_args, create_envs_only=args.create_envs_only, mode=args.mode, wrapper_prefix=args.wrapper_prefix, default_remote_provider=args.default_remote_provider, default_remote_prefix=args.default_remote_prefix, assume_shared_fs=not args.no_shared_fs, cluster_status=args.cluster_status, export_cwl=args.export_cwl, show_failed_logs=args.show_failed_logs, keep_incomplete=args.keep_incomplete, log_handler=log_handler, ) if args.runtime_profile: with open(args.runtime_profile, "w") as out: profile = yappi.get_func_stats() profile.sort("totaltime") profile.print_all(out=out) sys.exit(0 if success else 1) def bash_completion(snakefile="Snakefile"): """Entry point for bash completion.""" if not len(sys.argv) >= 2: print( "Calculate bash completion for snakemake. This tool shall not be invoked by hand." ) sys.exit(1) def print_candidates(candidates): if candidates: candidates = sorted(set(candidates)) ## Use bytes for avoiding '^M' under Windows. sys.stdout.buffer.write(b"\n".join(s.encode() for s in candidates)) prefix = sys.argv[2] if prefix.startswith("-"): print_candidates( action.option_strings[0] for action in get_argument_parser()._actions if action.option_strings and action.option_strings[0].startswith(prefix) ) else: candidates = [] files = glob.glob("{}*".format(prefix)) if files: candidates.extend(files) if os.path.exists(snakefile): workflow = Workflow(snakefile=snakefile) workflow.include(snakefile) candidates.extend( [file for file in workflow.concrete_files if file.startswith(prefix)] + [rule.name for rule in workflow.rules if rule.name.startswith(prefix)] ) if len(candidates) > 0: print_candidates(candidates) sys.exit(0) snakemake-5.10.0/snakemake/__main__.py000066400000000000000000000001631361131222100175550ustar00rootroot00000000000000# This script makes it possible to invoke snakemake with 'python3 -m snakemake' from snakemake import main main() snakemake-5.10.0/snakemake/_version.py000066400000000000000000000441251361131222100176670ustar00rootroot00000000000000# This file helps to compute a version number in source trees obtained from # git-archive tarball (such as those provided by githubs download-from-tag # feature). Distribution tarballs (built by setup.py sdist) and build # directories (produced by setup.py build) will contain a much shorter file # that just contains the computed version number. # This file is released into the public domain. Generated by # versioneer-0.18 (https://github.com/warner/python-versioneer) """Git implementation of _version.py.""" import errno import os import re import subprocess import sys def get_keywords(): """Get the keywords needed to look up the version information.""" # these strings will be replaced by git during git-archive. # setup.py/versioneer.py will grep for the variable names, so they must # each be defined on a line of their own. _version.py will just call # get_keywords(). git_refnames = " (tag: v5.10.0)" git_full = "28674b1605d2cc0bd66e5e608bf15c7b407b2b95" git_date = "2020-01-20 12:52:49 +0100" keywords = {"refnames": git_refnames, "full": git_full, "date": git_date} return keywords class VersioneerConfig: """Container for Versioneer configuration parameters.""" def get_config(): """Create, populate and return the VersioneerConfig() object.""" # these strings are filled in when 'setup.py versioneer' creates # _version.py cfg = VersioneerConfig() cfg.VCS = "git" cfg.style = "pep440" cfg.tag_prefix = "v" cfg.parentdir_prefix = "None" cfg.versionfile_source = "snakemake/_version.py" cfg.verbose = False return cfg class NotThisMethod(Exception): """Exception raised if a method is not valid for the current scenario.""" LONG_VERSION_PY = {} HANDLERS = {} def register_vcs_handler(vcs, method): # decorator """Decorator to mark a method as the handler for a particular VCS.""" def decorate(f): """Store f in HANDLERS[vcs][method].""" if vcs not in HANDLERS: HANDLERS[vcs] = {} HANDLERS[vcs][method] = f return f return decorate def run_command(commands, args, cwd=None, verbose=False, hide_stderr=False, env=None): """Call the given command(s).""" assert isinstance(commands, list) p = None for c in commands: try: dispcmd = str([c] + args) # remember shell=False, so use git.cmd on windows, not just git p = subprocess.Popen( [c] + args, cwd=cwd, env=env, stdout=subprocess.PIPE, stderr=(subprocess.PIPE if hide_stderr else None), ) break except EnvironmentError: e = sys.exc_info()[1] if e.errno == errno.ENOENT: continue if verbose: print("unable to run %s" % dispcmd) print(e) return None, None else: if verbose: print("unable to find command, tried %s" % (commands,)) return None, None stdout = p.communicate()[0].strip() if sys.version_info[0] >= 3: stdout = stdout.decode() if p.returncode != 0: if verbose: print("unable to run %s (error)" % dispcmd) print("stdout was %s" % stdout) return None, p.returncode return stdout, p.returncode def versions_from_parentdir(parentdir_prefix, root, verbose): """Try to determine the version from the parent directory name. Source tarballs conventionally unpack into a directory that includes both the project name and a version string. We will also support searching up two directory levels for an appropriately named parent directory """ rootdirs = [] for i in range(3): dirname = os.path.basename(root) if dirname.startswith(parentdir_prefix): return { "version": dirname[len(parentdir_prefix) :], "full-revisionid": None, "dirty": False, "error": None, "date": None, } else: rootdirs.append(root) root = os.path.dirname(root) # up a level if verbose: print( "Tried directories %s but none started with prefix %s" % (str(rootdirs), parentdir_prefix) ) raise NotThisMethod("rootdir doesn't start with parentdir_prefix") @register_vcs_handler("git", "get_keywords") def git_get_keywords(versionfile_abs): """Extract version information from the given file.""" # the code embedded in _version.py can just fetch the value of these # keywords. When used from setup.py, we don't want to import _version.py, # so we do it with a regexp instead. This function is not used from # _version.py. keywords = {} try: f = open(versionfile_abs, "r") for line in f.readlines(): if line.strip().startswith("git_refnames ="): mo = re.search(r'=\s*"(.*)"', line) if mo: keywords["refnames"] = mo.group(1) if line.strip().startswith("git_full ="): mo = re.search(r'=\s*"(.*)"', line) if mo: keywords["full"] = mo.group(1) if line.strip().startswith("git_date ="): mo = re.search(r'=\s*"(.*)"', line) if mo: keywords["date"] = mo.group(1) f.close() except EnvironmentError: pass return keywords @register_vcs_handler("git", "keywords") def git_versions_from_keywords(keywords, tag_prefix, verbose): """Get version information from git keywords.""" if not keywords: raise NotThisMethod("no keywords at all, weird") date = keywords.get("date") if date is not None: # git-2.2.0 added "%cI", which expands to an ISO-8601 -compliant # datestamp. However we prefer "%ci" (which expands to an "ISO-8601 # -like" string, which we must then edit to make compliant), because # it's been around since git-1.5.3, and it's too difficult to # discover which version we're using, or to work around using an # older one. date = date.strip().replace(" ", "T", 1).replace(" ", "", 1) refnames = keywords["refnames"].strip() if refnames.startswith("$Format"): if verbose: print("keywords are unexpanded, not using") raise NotThisMethod("unexpanded keywords, not a git-archive tarball") refs = set([r.strip() for r in refnames.strip("()").split(",")]) # starting in git-1.8.3, tags are listed as "tag: foo-1.0" instead of # just "foo-1.0". If we see a "tag: " prefix, prefer those. TAG = "tag: " tags = set([r[len(TAG) :] for r in refs if r.startswith(TAG)]) if not tags: # Either we're using git < 1.8.3, or there really are no tags. We use # a heuristic: assume all version tags have a digit. The old git %d # expansion behaves like git log --decorate=short and strips out the # refs/heads/ and refs/tags/ prefixes that would let us distinguish # between branches and tags. By ignoring refnames without digits, we # filter out many common branch names like "release" and # "stabilization", as well as "HEAD" and "master". tags = set([r for r in refs if re.search(r"\d", r)]) if verbose: print("discarding '%s', no digits" % ",".join(refs - tags)) if verbose: print("likely tags: %s" % ",".join(sorted(tags))) for ref in sorted(tags): # sorting will prefer e.g. "2.0" over "2.0rc1" if ref.startswith(tag_prefix): r = ref[len(tag_prefix) :] if verbose: print("picking %s" % r) return { "version": r, "full-revisionid": keywords["full"].strip(), "dirty": False, "error": None, "date": date, } # no suitable tags, so version is "0+unknown", but full hex is still there if verbose: print("no suitable tags, using unknown + full revision id") return { "version": "0+unknown", "full-revisionid": keywords["full"].strip(), "dirty": False, "error": "no suitable tags", "date": None, } @register_vcs_handler("git", "pieces_from_vcs") def git_pieces_from_vcs(tag_prefix, root, verbose, run_command=run_command): """Get version from 'git describe' in the root of the source tree. This only gets called if the git-archive 'subst' keywords were *not* expanded, and _version.py hasn't already been rewritten with a short version string, meaning we're inside a checked out source tree. """ GITS = ["git"] if sys.platform == "win32": GITS = ["git.cmd", "git.exe"] out, rc = run_command(GITS, ["rev-parse", "--git-dir"], cwd=root, hide_stderr=True) if rc != 0: if verbose: print("Directory %s not under git control" % root) raise NotThisMethod("'git rev-parse --git-dir' returned error") # if there is a tag matching tag_prefix, this yields TAG-NUM-gHEX[-dirty] # if there isn't one, this yields HEX[-dirty] (no NUM) describe_out, rc = run_command( GITS, [ "describe", "--tags", "--dirty", "--always", "--long", "--match", "%s*" % tag_prefix, ], cwd=root, ) # --long was added in git-1.5.5 if describe_out is None: raise NotThisMethod("'git describe' failed") describe_out = describe_out.strip() full_out, rc = run_command(GITS, ["rev-parse", "HEAD"], cwd=root) if full_out is None: raise NotThisMethod("'git rev-parse' failed") full_out = full_out.strip() pieces = {} pieces["long"] = full_out pieces["short"] = full_out[:7] # maybe improved later pieces["error"] = None # parse describe_out. It will be like TAG-NUM-gHEX[-dirty] or HEX[-dirty] # TAG might have hyphens. git_describe = describe_out # look for -dirty suffix dirty = git_describe.endswith("-dirty") pieces["dirty"] = dirty if dirty: git_describe = git_describe[: git_describe.rindex("-dirty")] # now we have TAG-NUM-gHEX or HEX if "-" in git_describe: # TAG-NUM-gHEX mo = re.search(r"^(.+)-(\d+)-g([0-9a-f]+)$", git_describe) if not mo: # unparseable. Maybe git-describe is misbehaving? pieces["error"] = "unable to parse git-describe output: '%s'" % describe_out return pieces # tag full_tag = mo.group(1) if not full_tag.startswith(tag_prefix): if verbose: fmt = "tag '%s' doesn't start with prefix '%s'" print(fmt % (full_tag, tag_prefix)) pieces["error"] = "tag '%s' doesn't start with prefix '%s'" % ( full_tag, tag_prefix, ) return pieces pieces["closest-tag"] = full_tag[len(tag_prefix) :] # distance: number of commits since tag pieces["distance"] = int(mo.group(2)) # commit: short hex revision ID pieces["short"] = mo.group(3) else: # HEX: no tags pieces["closest-tag"] = None count_out, rc = run_command(GITS, ["rev-list", "HEAD", "--count"], cwd=root) pieces["distance"] = int(count_out) # total number of commits # commit date: see ISO-8601 comment in git_versions_from_keywords() date = run_command(GITS, ["show", "-s", "--format=%ci", "HEAD"], cwd=root)[ 0 ].strip() pieces["date"] = date.strip().replace(" ", "T", 1).replace(" ", "", 1) return pieces def plus_or_dot(pieces): """Return a + if we don't already have one, else return a .""" if "+" in pieces.get("closest-tag", ""): return "." return "+" def render_pep440(pieces): """Build up version string, with post-release "local version identifier". Our goal: TAG[+DISTANCE.gHEX[.dirty]] . Note that if you get a tagged build and then dirty it, you'll get TAG+0.gHEX.dirty Exceptions: 1: no tags. git_describe was just HEX. 0+untagged.DISTANCE.gHEX[.dirty] """ if pieces["closest-tag"]: rendered = pieces["closest-tag"] if pieces["distance"] or pieces["dirty"]: rendered += plus_or_dot(pieces) rendered += "%d.g%s" % (pieces["distance"], pieces["short"]) if pieces["dirty"]: rendered += ".dirty" else: # exception #1 rendered = "0+untagged.%d.g%s" % (pieces["distance"], pieces["short"]) if pieces["dirty"]: rendered += ".dirty" return rendered def render_pep440_pre(pieces): """TAG[.post.devDISTANCE] -- No -dirty. Exceptions: 1: no tags. 0.post.devDISTANCE """ if pieces["closest-tag"]: rendered = pieces["closest-tag"] if pieces["distance"]: rendered += ".post.dev%d" % pieces["distance"] else: # exception #1 rendered = "0.post.dev%d" % pieces["distance"] return rendered def render_pep440_post(pieces): """TAG[.postDISTANCE[.dev0]+gHEX] . The ".dev0" means dirty. Note that .dev0 sorts backwards (a dirty tree will appear "older" than the corresponding clean one), but you shouldn't be releasing software with -dirty anyways. Exceptions: 1: no tags. 0.postDISTANCE[.dev0] """ if pieces["closest-tag"]: rendered = pieces["closest-tag"] if pieces["distance"] or pieces["dirty"]: rendered += ".post%d" % pieces["distance"] if pieces["dirty"]: rendered += ".dev0" rendered += plus_or_dot(pieces) rendered += "g%s" % pieces["short"] else: # exception #1 rendered = "0.post%d" % pieces["distance"] if pieces["dirty"]: rendered += ".dev0" rendered += "+g%s" % pieces["short"] return rendered def render_pep440_old(pieces): """TAG[.postDISTANCE[.dev0]] . The ".dev0" means dirty. Eexceptions: 1: no tags. 0.postDISTANCE[.dev0] """ if pieces["closest-tag"]: rendered = pieces["closest-tag"] if pieces["distance"] or pieces["dirty"]: rendered += ".post%d" % pieces["distance"] if pieces["dirty"]: rendered += ".dev0" else: # exception #1 rendered = "0.post%d" % pieces["distance"] if pieces["dirty"]: rendered += ".dev0" return rendered def render_git_describe(pieces): """TAG[-DISTANCE-gHEX][-dirty]. Like 'git describe --tags --dirty --always'. Exceptions: 1: no tags. HEX[-dirty] (note: no 'g' prefix) """ if pieces["closest-tag"]: rendered = pieces["closest-tag"] if pieces["distance"]: rendered += "-%d-g%s" % (pieces["distance"], pieces["short"]) else: # exception #1 rendered = pieces["short"] if pieces["dirty"]: rendered += "-dirty" return rendered def render_git_describe_long(pieces): """TAG-DISTANCE-gHEX[-dirty]. Like 'git describe --tags --dirty --always -long'. The distance/hash is unconditional. Exceptions: 1: no tags. HEX[-dirty] (note: no 'g' prefix) """ if pieces["closest-tag"]: rendered = pieces["closest-tag"] rendered += "-%d-g%s" % (pieces["distance"], pieces["short"]) else: # exception #1 rendered = pieces["short"] if pieces["dirty"]: rendered += "-dirty" return rendered def render(pieces, style): """Render the given version pieces into the requested style.""" if pieces["error"]: return { "version": "unknown", "full-revisionid": pieces.get("long"), "dirty": None, "error": pieces["error"], "date": None, } if not style or style == "default": style = "pep440" # the default if style == "pep440": rendered = render_pep440(pieces) elif style == "pep440-pre": rendered = render_pep440_pre(pieces) elif style == "pep440-post": rendered = render_pep440_post(pieces) elif style == "pep440-old": rendered = render_pep440_old(pieces) elif style == "git-describe": rendered = render_git_describe(pieces) elif style == "git-describe-long": rendered = render_git_describe_long(pieces) else: raise ValueError("unknown style '%s'" % style) return { "version": rendered, "full-revisionid": pieces["long"], "dirty": pieces["dirty"], "error": None, "date": pieces.get("date"), } def get_versions(): """Get version information or return default if unable to do so.""" # I am in _version.py, which lives at ROOT/VERSIONFILE_SOURCE. If we have # __file__, we can work backwards from there to the root. Some # py2exe/bbfreeze/non-CPython implementations don't do __file__, in which # case we can only use expanded keywords. cfg = get_config() verbose = cfg.verbose try: return git_versions_from_keywords(get_keywords(), cfg.tag_prefix, verbose) except NotThisMethod: pass try: root = os.path.realpath(__file__) # versionfile_source is the relative path from the top of the source # tree (where the .git directory might live) to this file. Invert # this to find the root from __file__. for i in cfg.versionfile_source.split("/"): root = os.path.dirname(root) except NameError: return { "version": "0+unknown", "full-revisionid": None, "dirty": None, "error": "unable to find root of source tree", "date": None, } try: pieces = git_pieces_from_vcs(cfg.tag_prefix, root, verbose) return render(pieces, cfg.style) except NotThisMethod: pass try: if cfg.parentdir_prefix: return versions_from_parentdir(cfg.parentdir_prefix, root, verbose) except NotThisMethod: pass return { "version": "0+unknown", "full-revisionid": None, "dirty": None, "error": "unable to compute version", "date": None, } snakemake-5.10.0/snakemake/benchmark.py000066400000000000000000000232161361131222100177730ustar00rootroot00000000000000__author__ = "Manuel Holtgrewe" __copyright__ = "Copyright 2017, Manuel Holtgrewe" __email__ = "manuel.holtgrewe@bihealth.de" __license__ = "MIT" import contextlib import datetime from itertools import chain import os import sys import time import threading import psutil from snakemake.exceptions import WorkflowError #: Interval (in seconds) between measuring resource usage BENCHMARK_INTERVAL = 30 #: Interval (in seconds) between measuring resource usage before #: BENCHMARK_INTERVAL BENCHMARK_INTERVAL_SHORT = 0.5 class BenchmarkRecord: """Record type for benchmark times""" @classmethod def get_header(klass): return "\t".join( ( "s", "h:m:s", "max_rss", "max_vms", "max_uss", "max_pss", "io_in", "io_out", "mean_load", ) ) def __init__( self, running_time=None, max_rss=None, max_vms=None, max_uss=None, max_pss=None, io_in=None, io_out=None, cpu_seconds=None, ): #: Running time in seconds self.running_time = running_time #: Maximal RSS in MB self.max_rss = max_rss #: Maximal VMS in MB self.max_vms = max_vms #: Maximal USS in MB self.max_uss = max_uss #: Maximal PSS in MB self.max_pss = max_pss #: I/O read in bytes self.io_in = io_in #: I/O written in bytes self.io_out = io_out #: Count of CPU seconds, divide by running time to get mean load estimate self.cpu_seconds = cpu_seconds or 0 #: First time when we measured CPU load, for estimating total running time self.first_time = None #: Previous point when measured CPU load, for estimating total running time self.prev_time = None def to_tsv(self): """Return ``str`` with the TSV representation of this record""" def to_tsv_str(x): """Conversion of value to str for TSV (None becomes "-")""" if x is None: return "-" elif isinstance(x, float): return "{:.2f}".format(x) else: return str(x) def timedelta_to_str(x): """Conversion of timedelta to str without fractions of seconds""" mm, ss = divmod(x.seconds, 60) hh, mm = divmod(mm, 60) s = "%d:%02d:%02d" % (hh, mm, ss) if x.days: def plural(n): return n, abs(n) != 1 and "s" or "" s = ("%d day%s, " % plural(x.days)) + s return s return "\t".join( map( to_tsv_str, ( "{:.4f}".format(self.running_time), timedelta_to_str(datetime.timedelta(seconds=self.running_time)), self.max_rss, self.max_vms, self.max_uss, self.max_pss, self.io_in, self.io_out, 100.0 * self.cpu_seconds / self.running_time, ), ) ) class DaemonTimer(threading.Thread): """Variant of threading.Timer that is deaemonized""" def __init__(self, interval, function, args=None, kwargs=None): threading.Thread.__init__(self, daemon=True) self.interval = interval self.function = function self.args = args if args is not None else [] self.kwargs = kwargs if kwargs is not None else {} self.finished = threading.Event() def cancel(self): """Stop the timer if it hasn't finished yet.""" self.finished.set() def run(self): self.finished.wait(self.interval) if not self.finished.is_set(): self.function(*self.args, **self.kwargs) self.finished.set() class ScheduledPeriodicTimer: """Scheduling of periodic events Up to self._interval, schedule actions per second, above schedule events in self._interval second gaps. """ def __init__(self, interval): self._times_called = 0 self._interval = interval self._timer = None self._stopped = True def start(self): """Start the intervalic timer""" self.work() self._times_called += 1 self._stopped = False if self._times_called > self._interval: self._timer = DaemonTimer(self._interval, self._action) else: self._timer = DaemonTimer(BENCHMARK_INTERVAL_SHORT, self._action) self._timer.start() def _action(self): """Internally, called by timer""" self.work() self._times_called += 1 if self._times_called > self._interval: self._timer = DaemonTimer(self._interval, self._action) else: self._timer = DaemonTimer(BENCHMARK_INTERVAL_SHORT, self._action) self._timer.start() def work(self): """Override to perform the action""" raise NotImplementedError("Override me!") def cancel(self): """Call to cancel any events""" self._timer.cancel() self._stopped = True class BenchmarkTimer(ScheduledPeriodicTimer): """Allows easy observation of a given PID for resource usage""" def __init__(self, pid, bench_record, interval=BENCHMARK_INTERVAL): ScheduledPeriodicTimer.__init__(self, interval) #: PID of observed process self.pid = pid self.main = psutil.Process(self.pid) #: ``BenchmarkRecord`` to write results to self.bench_record = bench_record #: Cache of processes to keep track of cpu percent self.procs = {} def work(self): """Write statistics""" try: self._update_record() except psutil.NoSuchProcess: pass # skip, process died in flight except AttributeError: pass # skip, process died in flight def _update_record(self): """Perform the actual measurement""" # Memory measurements rss, vms, uss, pss = 0, 0, 0, 0 # I/O measurements io_in, io_out = 0, 0 check_io = True # CPU seconds cpu_seconds = 0 # Iterate over process and all children try: this_time = time.time() for proc in chain((self.main,), self.main.children(recursive=True)): proc = self.procs.setdefault(proc.pid, proc) with proc.oneshot(): if self.bench_record.prev_time: cpu_seconds += ( proc.cpu_percent() / 100 * (this_time - self.bench_record.prev_time) ) meminfo = proc.memory_full_info() rss += meminfo.rss vms += meminfo.vms uss += meminfo.uss pss += meminfo.pss if check_io: try: ioinfo = proc.io_counters() io_in += ioinfo.read_bytes io_out += ioinfo.write_bytes except NotImplementedError as nie: # OS doesn't track IO check_io = False self.bench_record.prev_time = this_time if not self.bench_record.first_time: self.bench_record.prev_time = this_time rss /= 1024 * 1024 vms /= 1024 * 1024 uss /= 1024 * 1024 pss /= 1024 * 1024 if check_io: io_in /= 1024 * 1024 io_out /= 1024 * 1024 else: io_in = None io_out = None except psutil.Error as e: return # Update benchmark record's RSS and VMS self.bench_record.max_rss = max(self.bench_record.max_rss or 0, rss) self.bench_record.max_vms = max(self.bench_record.max_vms or 0, vms) self.bench_record.max_uss = max(self.bench_record.max_uss or 0, uss) self.bench_record.max_pss = max(self.bench_record.max_pss or 0, pss) self.bench_record.io_in = io_in self.bench_record.io_out = io_out self.bench_record.cpu_seconds += cpu_seconds @contextlib.contextmanager def benchmarked(pid=None, benchmark_record=None, interval=BENCHMARK_INTERVAL): """Measure benchmark parameters while within the context manager Yields a ``BenchmarkRecord`` with the results (values are set after leaving context). If ``pid`` is ``None`` then the PID of the current process will be used. If ``benchmark_record`` is ``None`` then a new ``BenchmarkRecord`` is created and returned, otherwise, the object passed as this parameter is returned. Usage:: with benchmarked() as bench_result: pass """ result = benchmark_record or BenchmarkRecord() if pid is False: yield result else: start_time = time.time() bench_thread = BenchmarkTimer(int(pid or os.getpid()), result, interval) bench_thread.start() yield result bench_thread.cancel() result.running_time = time.time() - start_time def print_benchmark_records(records, file_): """Write benchmark records to file-like object""" print(BenchmarkRecord.get_header(), file=file_) for r in records: print(r.to_tsv(), file=file_) def write_benchmark_records(records, path): """Write benchmark records to file at path""" with open(path, "wt") as f: print_benchmark_records(records, f) snakemake-5.10.0/snakemake/caching/000077500000000000000000000000001361131222100170575ustar00rootroot00000000000000snakemake-5.10.0/snakemake/caching/__init__.py000066400000000000000000000041671361131222100212000ustar00rootroot00000000000000__authors__ = "Johannes Köster, Sven Nahnsen" __copyright__ = "Copyright 2019, Johannes Köster, Sven Nahnsen" __email__ = "johannes.koester@uni-due.de" __license__ = "MIT" from abc import ABCMeta, abstractmethod import os from snakemake.jobs import Job from snakemake.io import is_flagged, get_flag_value, apply_wildcards from snakemake.exceptions import WorkflowError, CacheMissException from snakemake.caching.hash import ProvenanceHashMap LOCATION_ENVVAR = "SNAKEMAKE_OUTPUT_CACHE" class AbstractOutputFileCache: __metaclass__ = ABCMeta def __init__(self): try: self.cache_location = os.environ[LOCATION_ENVVAR] except KeyError: raise WorkflowError( "Output file cache activated (--cache), but no cache " "location specified. Please set the environment variable " "${}.".format(LOCATION_ENVVAR) ) self.provenance_hash_map = ProvenanceHashMap() @abstractmethod def store(self, job: Job): pass @abstractmethod def fetch(self, job: Job): pass @abstractmethod def exists(self, job: Job): pass def get_outputfiles(self, job: Job): if job.rule.output[0].is_multiext: prefix_len = len( apply_wildcards(job.rule.output[0].multiext_prefix, job.wildcards) ) yield from ((f, f[prefix_len:]) for f in job.output) else: yield (job.output[0], "") def raise_write_error(self, entry, exception=None): raise WorkflowError( "Given output cache entry {} ($SNAKEMAKE_OUTPUT_CACHE={}) is not writeable.".format( entry, self.cache_location ), *[exception], ) def raise_read_error(self, entry, exception=None): raise WorkflowError( "Given output cache entry {} ($SNAKEMAKE_OUTPUT_CACHE={}) is not readable.".format( entry, self.cache_location ), *[exception], ) def raise_cache_miss_exception(self, job): raise CacheMissException("Job {} not yet cached.".format(job)) snakemake-5.10.0/snakemake/caching/hash.py000066400000000000000000000070741361131222100203640ustar00rootroot00000000000000__authors__ = "Johannes Köster, Sven Nahnsen" __copyright__ = "Copyright 2019, Johannes Köster, Sven Nahnsen" __email__ = "johannes.koester@uni-due.de" __license__ = "MIT" import hashlib import json from snakemake.jobs import Job from snakemake import script from snakemake import wrapper # ATTENTION: increase version number whenever the hashing algorithm below changes! __version__ = "0.1" class ProvenanceHashMap: def __init__(self): self._hashes = dict() def get_provenance_hash(self, job: Job): versioned_hash = hashlib.sha256() # Ensure that semantic version changes in this module versioned_hash.update(self._get_provenance_hash(job).encode()) versioned_hash.update(__version__.encode()) return versioned_hash.hexdigest() def _get_provenance_hash(self, job: Job): """ Recursively calculate hash for the output of the given job and all upstream jobs in a blockchain fashion. This is based on an idea of Sven Nahnsen. Fails if job has more than one output file. The reason is that there is no way to generate a per-output file hash without generating the files. This hash, however, shall work without having to generate the files, just by describing all steps down to a given job. """ if job in self._hashes: return self._hashes[job] workflow = job.dag.workflow h = hashlib.sha256() # Hash shell command or script. if job.is_shell: # We cannot use the formatted shell command, because it also contains threads, # resources, and filenames (which shall be irrelevant for the hash). h.update(job.rule.shellcmd.encode()) elif job.is_script: _, source, _ = script.get_source(job.rule.script) h.update(source) elif job.is_wrapper: _, source, _ = script.get_source( wrapper.get_script(job.rule.wrapper, prefix=workflow.wrapper_prefix) ) h.update(source) # Hash params. for key, value in sorted(job.params._allitems()): h.update(key.encode()) # If this raises a TypeError, we cannot calculate a reliable hash. h.update(json.dumps(value, sort_keys=True).encode()) # Hash input files that are not generated by other jobs. for f in job.input: if not any( f in depfiles for depfiles in job.dag.dependencies[job].values() ): with open(f, "b") as f: # Read and update hash string value in blocks of 4K for byte_block in iter(lambda: f.read(4096), b""): h.update(byte_block) # Hash used containers or conda environments. if workflow.use_conda and job.conda_env: if workflow.use_singularity and job.conda_env.singularity_img_url: h.update(job.conda_env.singularity_img_url.encode()) h.update(job.conda_env.content) elif workflow.use_singularity and job.singularity_img_url: h.update(job.singularity_img_url.encode()) # Generate hashes of dependencies, and add them in a blockchain fashion (as input to the current hash). for dep_hash in sorted( self._get_provenance_hash(dep) for dep in set(job.dag.dependencies[job].keys()) ): h.update(dep_hash.encode()) provenance_hash = h.hexdigest() # Store for re-use. self._hashes[job] = provenance_hash return provenance_hash snakemake-5.10.0/snakemake/caching/local.py000066400000000000000000000105761361131222100205340ustar00rootroot00000000000000__authors__ = "Johannes Köster, Sven Nahnsen" __copyright__ = "Copyright 2019, Johannes Köster, Sven Nahnsen" __email__ = "johannes.koester@uni-due.de" __license__ = "MIT" from tempfile import TemporaryDirectory from pathlib import Path import os import shutil import stat from snakemake.logging import logger from snakemake.jobs import Job from snakemake.exceptions import WorkflowError from snakemake.caching.hash import ProvenanceHashMap from snakemake.caching import LOCATION_ENVVAR, AbstractOutputFileCache class OutputFileCache(AbstractOutputFileCache): """ A cache for output files that uses a provenance hash value that describes all steps, parameters, and software needed to generate each output file. """ def __init__(self): super().__init__() self.path = Path(self.cache_location) def check_writeable(self, cachefile): if not (os.access(cachefile.parent, os.W_OK) or os.access(cachefile, os.W_OK)): self.raise_write_error(cachefile) def check_readable(self, cachefile): if not os.access(cachefile, os.R_OK): self.raise_read_error(cachefile) def store(self, job: Job): """ Store generated job output in the cache. """ with TemporaryDirectory(dir=self.path) as tmpdirname: tmpdir = Path(tmpdirname) for outputfile, cachefile in self.get_outputfiles_and_cachefiles(job): self.check_writeable(cachefile) logger.info("Moving output file {} to cache.".format(outputfile)) tmp = tmpdir / cachefile.name # First move is performed into a tempdir (it might involve a copy if not on the same FS). # This is important, such that network filesystem latency # does not lead to concurrent writes to the same file. # We can use the plain copy method of shutil, because we do not care about the metadata. shutil.move(outputfile, tmp, copy_function=shutil.copy) # make readable/writeable for all os.chmod( tmp, stat.S_IRUSR | stat.S_IWUSR | stat.S_IRGRP | stat.S_IWGRP | stat.S_IROTH | stat.S_IWOTH, ) # Move to the actual path (now we are on the same FS, hence move is atomic). # Here we use the default copy function, also copying metadata (which is important here). # It will always work, because we are guaranteed to be in the same FS. shutil.move(tmp, cachefile) # now restore the outputfile via a symlink self.symlink(cachefile, outputfile, utime=False) def fetch(self, job: Job): """ Retrieve cached output file and copy to the place where the job expects it's output. """ for outputfile, cachefile in self.get_outputfiles_and_cachefiles(job): if not cachefile.exists(): self.raise_cache_miss_exception(job) self.check_readable(cachefile) self.symlink(cachefile, outputfile) def exists(self, job: Job): """ Return True if job is already cached """ for outputfile, cachefile in self.get_outputfiles_and_cachefiles(job): if not cachefile.exists(): return False self.check_readable(cachefile) return True def get_outputfiles_and_cachefiles(self, job: Job): provenance_hash = self.provenance_hash_map.get_provenance_hash(job) base_path = self.path / provenance_hash return ( (outputfile, base_path.with_suffix(ext)) for outputfile, ext in self.get_outputfiles(job) ) def symlink(self, path, outputfile, utime=True): if os.utime in os.supports_follow_symlinks or not utime: logger.info("Symlinking output file {} from cache.".format(outputfile)) os.symlink(path, outputfile) if utime: os.utime(outputfile, follow_symlinks=False) else: logger.info( "Copying output file {} from cache (OS does not support updating the modification date of symlinks).".format( outputfile ) ) shutil.copyfile(path, outputfile) snakemake-5.10.0/snakemake/caching/remote.py000066400000000000000000000040111361131222100207200ustar00rootroot00000000000000__authors__ = "Johannes Köster, Sven Nahnsen" __copyright__ = "Copyright 2019, Johannes Köster, Sven Nahnsen" __email__ = "johannes.koester@uni-due.de" __license__ = "MIT" from snakemake.caching.hash import ProvenanceHashMap from snakemake.caching import AbstractOutputFileCache from snakemake.jobs import Job from snakemake.io import get_flag_value, IOFile class OutputFileCache(AbstractOutputFileCache): """ A cache for output files that uses a provenance hash value that describes all steps, parameters, and software needed to generate each output file. This is the remote version. """ def __init__(self, remote_provider): super().__init__() self.remote_provider = remote_provider def store(self, job: Job): for entry in self._get_remotes(job): # upload to remote try: entry.upload() except Exception as e: self.raise_write_error(entry, exception=e) def fetch(self, job: Job): for entry in self._get_remotes(job): if not entry.exists(): self.raise_cache_miss_exception(job) # download to outputfile try: entry.download() except Exception as e: self.raise_read_error(entry, exception=e) def exists(self, job: Job): for entry in self._get_remotes(job): try: return entry.exists() except Exception as e: self.raise_read_error(entry, exception=e) def _get_remotes(self, job: Job, check_output_exists=False): provenance_hash = self.provenance_hash_map.get_provenance_hash(job) for outputfile, ext in self.get_outputfiles(job): f = self.remote_provider.remote( "{}/{}{}".format(self.cache_location, provenance_hash, ext) ) remote = get_flag_value(f, "remote_object") # set local copy of the remote file remote._iofile = outputfile yield remote snakemake-5.10.0/snakemake/checkpoints.py000066400000000000000000000024101361131222100203440ustar00rootroot00000000000000from snakemake.exceptions import IncompleteCheckpointException, WorkflowError from snakemake.io import checkpoint_target class Checkpoints: """ A namespace for checkpoints so that they can be accessed via dot notation. """ def __init__(self): self.future_output = None def register(self, rule): setattr(self, rule.name, Checkpoint(rule, self)) class Checkpoint: __slots__ = ["rule", "checkpoints"] def __init__(self, rule, checkpoints): self.rule = rule self.checkpoints = checkpoints def get(self, **wildcards): missing = self.rule.wildcard_names.difference(wildcards.keys()) if missing: raise WorkflowError( "Missing wildcard values for {}".format(", ".join(missing)) ) output, _ = self.rule.expand_output(wildcards) if self.checkpoints.future_output is None or any( (not f.exists or f in self.checkpoints.future_output) for f in output ): raise IncompleteCheckpointException(self.rule, checkpoint_target(output[0])) return CheckpointJob(self.rule, output) class CheckpointJob: __slots__ = ["rule", "output"] def __init__(self, rule, output): self.output = output self.rule = rule snakemake-5.10.0/snakemake/common.py000066400000000000000000000045061361131222100173320ustar00rootroot00000000000000__author__ = "Johannes Köster" __copyright__ = "Copyright 2016-2019, Johannes Köster" __email__ = "johannes.koester@protonmail.com" __license__ = "MIT" from functools import update_wrapper import inspect import uuid import os from ._version import get_versions __version__ = get_versions()["version"] del get_versions MIN_PY_VERSION = (3, 5) DYNAMIC_FILL = "__snakemake_dynamic__" SNAKEMAKE_SEARCHPATH = os.path.dirname(os.path.dirname(__file__)) UUID_NAMESPACE = uuid.uuid5(uuid.NAMESPACE_URL, "https://snakemake.readthedocs.io") class TBDInt(int): """An integer that prints into """ def __str__(self): return "" # A string that prints as TBD TBDString = "" def num_if_possible(s): """Convert string to number if possible, otherwise return string.""" try: return int(s) except ValueError: try: return float(s) except ValueError: return s def get_last_stable_version(): return __version__.split("+")[0] def get_container_image(): return "snakemake/snakemake:v{}".format(get_last_stable_version()) def get_uuid(name): return uuid.uuid5(UUID_NAMESPACE, name) class Mode: """ Enum for execution mode of Snakemake. This handles the behavior of e.g. the logger. """ default = 0 subprocess = 1 cluster = 2 class lazy_property(property): __slots__ = ["method", "cached", "__doc__"] @staticmethod def clean(instance, method): delattr(instance, method) def __init__(self, method): self.method = method self.cached = "_{}".format(method.__name__) super().__init__(method, doc=method.__doc__) def __get__(self, instance, owner): cached = ( getattr(instance, self.cached) if hasattr(instance, self.cached) else None ) if cached is not None: return cached value = self.method(instance) setattr(instance, self.cached, value) return value def strip_prefix(text, prefix): if text.startswith(prefix): return text[len(prefix) :] return text def log_location(msg): callerframerecord = inspect.stack()[1] frame = callerframerecord[0] info = inspect.getframeinfo(frame) logger.debug( "{}: {info.filename}, {info.function}, {info.lineno}".format(msg, info=info) ) snakemake-5.10.0/snakemake/cwl.py000066400000000000000000000206011361131222100166210ustar00rootroot00000000000000__author__ = "Johannes Köster" __copyright__ = "Copyright 2018-2019, Johannes Köster" __email__ = "johannes.koester@uni-due.de" __license__ = "MIT" from urllib.request import pathname2url import os import subprocess import tempfile import json import shutil import uuid from itertools import chain from snakemake.utils import format from snakemake.logging import logger from snakemake.exceptions import WorkflowError from snakemake.shell import shell from snakemake.common import get_container_image, Mode from snakemake.io import is_flagged def cwl( path, basedir, input, output, params, wildcards, threads, resources, log, config, rulename, use_singularity, bench_record, jobid, ): """ Load cwl from the given basedir + path and execute it. """ if shutil.which("cwltool") is None: raise WorkflowError( "'cwltool' must be in PATH in order to execute cwl directive." ) if not path.startswith("http"): if path.startswith("file://"): path = path[7:] elif path.startswith("file:"): path = path[5:] if not os.path.isabs(path): path = os.path.abspath(os.path.join(basedir, path)) path = "file://" + path path = format(path, stepout=1) if path.startswith("file://"): sourceurl = "file:" + pathname2url(path[7:]) else: sourceurl = path def file_spec(f): if isinstance(f, str): return {"path": os.path.abspath(f), "class": "File"} return [file_spec(f_) for f_ in f] inputs = dict() inputs.update({name: file_spec(f) for name, f in input.items()}) inputs.update({name: p for name, p in params.items()}) inputs.update({name: f for name, f in output.items()}) inputs.update({name: f for name, f in log.items()}) args = "--singularity" if use_singularity else "" with tempfile.NamedTemporaryFile(mode="w") as input_file: json.dump(inputs, input_file) input_file.flush() cmd = "cwltool {} {} {}".format(args, sourceurl, input_file.name) shell(cmd, bench_record=bench_record) def job_to_cwl(job, dag, outputs, inputs): """Convert a job with its dependencies to a CWL workflow step. """ if job.dynamic_output: raise WorkflowError("Dynamic output is not supported by CWL conversion.") for f in job.output: if os.path.isabs(f): raise WorkflowError( "All output files have to be relative to the " "working directory." ) get_output_id = lambda job, i: "#main/job-{}/{}".format(job.jobid, i) dep_ids = { o: get_output_id(dep, i) for dep, files in dag.dependencies[job].items() for i, o in enumerate(dep.output) if o in files } files = [f for f in job.input if f not in dep_ids] if job.conda_env_file: files.add(os.path.relpath(job.conda_env_file)) out = [get_output_id(job, i) for i, _ in enumerate(job.output)] def workdir_entry(i, f): location = "??inputs.input_files[{}].location??".format(i) if f.is_directory: entry = { "class": "Directory", "basename": os.path.basename(f), "location": location, } else: entry = { "class": "File", "basename": os.path.basename(f), "location": location, } return "$({})".format( json.dumps(outer_entry(f, entry)).replace('"??', "").replace('??"', "") ).replace('"', "'") def outer_entry(f, entry): parent = os.path.dirname(f) if parent: return outer_entry( parent, { "class": "Directory", "basename": os.path.basename(parent), "listing": [entry], }, ) else: return entry if job in dag.targetjobs: # TODO this maps output files into the cwd after the workflow is complete. # We need to find a way to define subdirectories though. Otherwise, # there can be name clashes, and it will also become very crowded. outputs.append( { "type": {"type": "array", "items": "File"}, "outputSource": "#main/job-{}/output_files".format(job.jobid), "id": "#main/output/job-{}".format(job.jobid), } ) cwl = { "run": "#snakemake-job", "requirements": { "InitialWorkDirRequirement": { "listing": [ {"writable": True, "entry": workdir_entry(i, f)} for i, f in enumerate( chain( files, (f for dep in dag.dependencies[job] for f in dep.output), ) ) ] } }, "in": { "cores": {"default": job.threads}, "target_files": {"default": job.output._plainstrings()}, "rules": {"default": [job.rule.name]}, }, "out": ["output_files"], "id": "#main/job-{}".format(job.jobid), } if files: inputs.append( { "type": {"type": "array", "items": "File"}, "default": [{"class": "File", "location": f} for f in files], "id": "#main/input/job-{}".format(job.jobid), } ) input_files = [] if files: input_files.append("#main/input/job-{}".format(job.jobid)) input_files.extend( "#main/job-{}/output_files".format(dep.jobid) for dep in dag.dependencies[job] ) cwl["in"]["input_files"] = {"source": input_files, "linkMerge": "merge_flattened"} return cwl def dag_to_cwl(dag): """Convert a given DAG to a CWL workflow, which is returned as JSON object. """ snakemake_cwl = { "class": "CommandLineTool", "id": "#snakemake-job", "label": "Snakemake job executor", "hints": [{"dockerPull": get_container_image(), "class": "DockerRequirement"}], "baseCommand": "snakemake", "requirements": {"ResourceRequirement": {"coresMin": "$(inputs.cores)"}}, "arguments": [ "--force", "--keep-target-files", "--keep-remote", "--force-use-threads", "--wrapper-prefix", dag.workflow.wrapper_prefix, "--notemp", "--quiet", "--use-conda", "--no-hooks", "--nolock", "--mode", str(Mode.subprocess), ], "inputs": { "snakefile": { "type": "File", "default": { "class": "File", "location": os.path.relpath(dag.workflow.snakefile), }, "inputBinding": {"prefix": "--snakefile"}, }, "sources": { "type": "File[]", "default": [ {"class": "File", "location": f} for f in dag.workflow.get_sources() ], }, "cores": { "type": "int", "default": 1, "inputBinding": {"prefix": "--cores"}, }, "rules": { "type": "string[]?", "inputBinding": {"prefix": "--allowed-rules"}, }, "input_files": {"type": "File[]", "default": []}, "target_files": {"type": "string[]?", "inputBinding": {"position": 0}}, }, "outputs": { "output_files": { "type": {"type": "array", "items": "File"}, "outputBinding": {"glob": "$(inputs.target_files)"}, } }, } groups = dag.get_jobs_or_groups() outputs = [] inputs = [] dag_cwl = [job_to_cwl(job, dag, outputs, inputs) for job in groups] return { "cwlVersion": "v1.0", "$graph": [ snakemake_cwl, { "class": "Workflow", "requirements": { "InlineJavascriptRequirement": {}, "MultipleInputFeatureRequirement": {}, }, "steps": dag_cwl, "inputs": inputs, "outputs": outputs, "id": "#main", }, ], } snakemake-5.10.0/snakemake/dag.py000077500000000000000000002133261361131222100166020ustar00rootroot00000000000000__author__ = "Johannes Köster" __copyright__ = "Copyright 2015-2019, Johannes Köster" __email__ = "koester@jimmy.harvard.edu" __license__ = "MIT" import html import os import shutil import textwrap import time import tarfile from collections import defaultdict, Counter from itertools import chain, filterfalse, groupby from functools import partial from pathlib import Path import uuid import math from snakemake.io import PeriodicityDetector, wait_for_files, is_flagged from snakemake.jobs import Job, Reason, GroupJob from snakemake.exceptions import MissingInputException from snakemake.exceptions import MissingRuleException, AmbiguousRuleException from snakemake.exceptions import CyclicGraphException, MissingOutputException from snakemake.exceptions import IncompleteFilesException, ImproperOutputException from snakemake.exceptions import PeriodicWildcardError from snakemake.exceptions import RemoteFileException, WorkflowError, ChildIOException from snakemake.exceptions import InputFunctionException from snakemake.logging import logger from snakemake.common import DYNAMIC_FILL from snakemake.deployment import conda, singularity from snakemake.output_index import OutputIndex from snakemake import workflow class Batch: """Definition of a batch for calculating only a partial DAG.""" def __init__(self, rulename: str, idx: int, batches: int): assert idx <= batches assert idx > 0 self.rulename = rulename self.idx = idx self.batches = batches def get_batch(self, items: list): """Return the defined batch of the given items. Items are usually input files.""" # make sure that we always consider items in the same order if len(items) < self.batches: raise WorkflowError( "Batching rule {} has less input files than batches. " "Please choose a smaller number of batches.".format(self.rulename) ) items = sorted(items) batch_len = math.floor(len(items) / self.batches) # self.batch is one-based, hence we have to subtract 1 idx = self.idx - 1 i = idx * batch_len if self.is_final: # extend the last batch to cover rest of list return items[i:] else: return items[i : i + batch_len] @property def is_final(self): return self.idx == self.batches def __str__(self): return "{}/{} (rule {})".format(self.idx, self.batches, self.rulename) class DAG: """Directed acyclic graph of jobs.""" def __init__( self, workflow, rules=None, dryrun=False, targetfiles=None, targetrules=None, forceall=False, forcerules=None, forcefiles=None, priorityfiles=None, priorityrules=None, untilfiles=None, untilrules=None, omitfiles=None, omitrules=None, ignore_ambiguity=False, force_incomplete=False, ignore_incomplete=False, notemp=False, keep_remote_local=False, batch=None, ): self.dryrun = dryrun self.dependencies = defaultdict(partial(defaultdict, set)) self.depending = defaultdict(partial(defaultdict, set)) self._needrun = set() self._priority = dict() self._reason = defaultdict(Reason) self._finished = set() self._dynamic = set() self._len = 0 self.workflow = workflow self.rules = set(rules) self.ignore_ambiguity = ignore_ambiguity self.targetfiles = targetfiles self.targetrules = targetrules self.priorityfiles = priorityfiles self.priorityrules = priorityrules self.targetjobs = set() self.prioritytargetjobs = set() self._ready_jobs = set() self.notemp = notemp self.keep_remote_local = keep_remote_local self._jobid = dict() self.job_cache = dict() self.conda_envs = dict() self.singularity_imgs = dict() self._progress = 0 self._group = dict() self.forcerules = set() self.forcefiles = set() self.untilrules = set() self.untilfiles = set() self.omitrules = set() self.omitfiles = set() self.updated_subworkflow_files = set() if forceall: self.forcerules.update(self.rules) elif forcerules: self.forcerules.update(forcerules) if forcefiles: self.forcefiles.update(forcefiles) if untilrules: self.untilrules.update(set(rule.name for rule in untilrules)) if untilfiles: self.untilfiles.update(untilfiles) if omitrules: self.omitrules.update(set(rule.name for rule in omitrules)) if omitfiles: self.omitfiles.update(omitfiles) self.omitforce = set() self.batch = batch if batch is not None and not batch.is_final: # Since not all input files of a batching rule are considered, we cannot run # beyond that rule. # For the final batch, we do not need to omit anything. self.omitrules.add(batch.rulename) self.force_incomplete = force_incomplete self.ignore_incomplete = ignore_incomplete self.periodic_wildcard_detector = PeriodicityDetector() self.update_output_index() def init(self, progress=False): """ Initialise the DAG. """ for job in map(self.rule2job, self.targetrules): job = self.update([job], progress=progress) self.targetjobs.add(job) for file in self.targetfiles: job = self.update(self.file2jobs(file), file=file, progress=progress) self.targetjobs.add(job) self.cleanup() self.update_needrun() self.set_until_jobs() self.delete_omitfrom_jobs() self.update_jobids() self.check_directory_outputs() # check if remaining jobs are valid for i, job in enumerate(self.jobs): job.is_valid() def check_directory_outputs(self): """Check that no output file is contained in a directory output of the same or another rule.""" outputs = sorted( { path(f) for job in self.jobs for f in job.output for path in (os.path.abspath, os.path.realpath) } ) for i in range(len(outputs) - 1): a, b = outputs[i : i + 2] try: common = os.path.commonpath([a, b]) except ValueError: # commonpath raises error if windows drives are different. continue if common == os.path.commonpath([a]): raise ChildIOException(parent=outputs[i], child=outputs[i + 1]) @property def checkpoint_jobs(self): for job in self.needrun_jobs: if job.is_checkpoint: yield job def update_checkpoint_outputs(self): workflow.checkpoints.future_output = set( f for job in self.checkpoint_jobs for f in job.output ) def update_jobids(self): for job in self.jobs: if job not in self._jobid: self._jobid[job] = len(self._jobid) def cleanup(self): self.job_cache.clear() final_jobs = set(self.jobs) todelete = [job for job in self.dependencies if job not in final_jobs] for job in todelete: del self.dependencies[job] try: del self.depending[job] except KeyError: pass def create_conda_envs( self, dryrun=False, forceall=False, init_only=False, quiet=False ): # First deduplicate based on job.conda_env_file jobs = self.jobs if forceall else self.needrun_jobs env_set = { (job.conda_env_file, job.singularity_img_url) for job in jobs if job.conda_env_file } # Then based on md5sum values self.conda_envs = dict() for (env_file, simg_url) in env_set: simg = None if simg_url: assert ( simg_url in self.singularity_imgs ), "bug: must first pull singularity images" simg = self.singularity_imgs[simg_url] env = conda.Env(env_file, self, singularity_img=simg) self.conda_envs[(env_file, simg_url)] = env if not init_only: for env in self.conda_envs.values(): if not dryrun or not quiet: env.create(dryrun) def pull_singularity_imgs(self, dryrun=False, forceall=False, quiet=False): # First deduplicate based on job.conda_env_file jobs = self.jobs if forceall else self.needrun_jobs img_set = {job.singularity_img_url for job in jobs if job.singularity_img_url} for img_url in img_set: img = singularity.Image(img_url, self) if not dryrun or not quiet: img.pull(dryrun) self.singularity_imgs[img_url] = img def update_output_index(self): """Update the OutputIndex.""" self.output_index = OutputIndex(self.rules) def check_incomplete(self): """Check if any output files are incomplete. This is done by looking up markers in the persistence module.""" if not self.ignore_incomplete: incomplete = self.incomplete_files if incomplete: if self.force_incomplete: logger.debug("Forcing incomplete files:") logger.debug("\t" + "\n\t".join(incomplete)) self.forcefiles.update(incomplete) else: raise IncompleteFilesException(incomplete) def incomplete_external_jobid(self, job): """Return the external jobid of the job if it is marked as incomplete. Returns None, if job is not incomplete, or if no external jobid has been registered or if force_incomplete is True. """ if self.force_incomplete: return None jobids = self.workflow.persistence.external_jobids(job) if len(jobids) == 1: return jobids[0] elif len(jobids) > 1: raise WorkflowError( "Multiple different external jobids registered " "for output files of incomplete job {} ({}). This job " "cannot be resumed. Execute Snakemake with --rerun-incomplete " "to fix this issue.".format(job.jobid, jobids) ) def check_dynamic(self): """Check dynamic output and update downstream rules if necessary.""" for job in filter( lambda job: (job.dynamic_output and not self.needrun(job)), self.jobs ): self.update_dynamic(job) self.postprocess() @property def dynamic_output_jobs(self): """Iterate over all jobs with dynamic output files.""" return (job for job in self.jobs if job.dynamic_output) @property def jobs(self): """ All jobs in the DAG. """ for job in self.bfs(self.dependencies, *self.targetjobs): yield job @property def needrun_jobs(self): """ Jobs that need to be executed. """ for job in filter( self.needrun, self.bfs(self.dependencies, *self.targetjobs, stop=self.noneedrun_finished), ): yield job @property def local_needrun_jobs(self): """Iterate over all jobs that need to be run and are marked as local.""" return filter(lambda job: job.is_local, self.needrun_jobs) @property def finished_jobs(self): """ Iterate over all jobs that have been finished.""" for job in filter(self.finished, self.bfs(self.dependencies, *self.targetjobs)): yield job @property def ready_jobs(self): """Jobs that are ready to execute.""" return self._ready_jobs def needrun(self, job): """Return whether a given job needs to be executed.""" return job in self._needrun def priority(self, job): """Return priority of given job.""" return self._priority[job] def noneedrun_finished(self, job): """ Return whether a given job is finished or was not required to run at all. """ return not self.needrun(job) or self.finished(job) def reason(self, job): """ Return the reason of the job execution. """ return self._reason[job] def finished(self, job): """ Return whether a job is finished. """ return job in self._finished def dynamic(self, job): """ Return whether a job is dynamic (i.e. it is only a placeholder for those that are created after the job with dynamic output has finished. """ if job.is_group(): for j in job: if j in self._dynamic: return True else: return job in self._dynamic def requested_files(self, job): """Return the files a job requests.""" return set(*self.depending[job].values()) @property def incomplete_files(self): """Return list of incomplete files.""" return list( chain( *( job.output for job in filter( self.workflow.persistence.incomplete, filterfalse(self.needrun, self.jobs), ) ) ) ) @property def newversion_files(self): """Return list of files where the current version is newer than the recorded version. """ return list( chain( *( job.output for job in filter(self.workflow.persistence.newversion, self.jobs) ) ) ) def missing_temp(self, job): """ Return whether a temp file that is input of the given job is missing. """ for job_, files in self.depending[job].items(): if self.needrun(job_) and any(not f.exists for f in files): return True return False def check_and_touch_output( self, job, wait=3, ignore_missing_output=False, no_touch=False, force_stay_on_remote=False, ): """ Raise exception if output files of job are missing. """ expanded_output = [job.shadowed_path(path) for path in job.expanded_output] if job.benchmark: expanded_output.append(job.benchmark) if not ignore_missing_output: try: wait_for_files( expanded_output, latency_wait=wait, force_stay_on_remote=force_stay_on_remote, ignore_pipe=True, ) except IOError as e: raise MissingOutputException( str(e) + "\nThis might be due to " "filesystem latency. If that is the case, consider to increase the " "wait time with --latency-wait.", rule=job.rule, ) # Ensure that outputs are of the correct type (those flagged with directory() # are directories and not files and vice versa). for f in expanded_output: if (f.is_directory and not os.path.isdir(f)) or ( os.path.isdir(f) and not f.is_directory ): raise ImproperOutputException(job.rule, [f]) # It is possible, due to archive expansion or cluster clock skew, that # the files appear older than the input. But we know they must be new, # so touch them to update timestamps. This also serves to touch outputs # when using the --touch flag. # Note that if the input files somehow have a future date then this will # not currently be spotted and the job will always be re-run. if not no_touch: for f in expanded_output: # This won't create normal files if missing, but will create # the flag file for directories. if f.exists_local: f.touch() def unshadow_output(self, job, only_log=False): """ Move files from shadow directory to real output paths. """ if not job.shadow_dir or not job.expanded_output: return files = job.log if only_log else chain(job.expanded_output, job.log) for real_output in files: shadow_output = job.shadowed_path(real_output).file # Remake absolute symlinks as relative if os.path.islink(shadow_output): dest = os.readlink(shadow_output) if os.path.isabs(dest): rel_dest = os.path.relpath(dest, job.shadow_dir) os.remove(shadow_output) os.symlink(rel_dest, shadow_output) if os.path.realpath(shadow_output) == os.path.realpath(real_output): continue logger.debug( "Moving shadow output {} to destination {}".format( shadow_output, real_output ) ) shutil.move(shadow_output, real_output) shutil.rmtree(job.shadow_dir) def check_periodic_wildcards(self, job): """ Raise an exception if a wildcard of the given job appears to be periodic, indicating a cyclic dependency. """ for wildcard, value in job.wildcards_dict.items(): periodic_substring = self.periodic_wildcard_detector.is_periodic(value) if periodic_substring is not None: raise PeriodicWildcardError( "The value {} in wildcard {} is periodically repeated ({}). " "This would lead to an infinite recursion. " "To avoid this, e.g. restrict the wildcards in this rule to certain values.".format( periodic_substring, wildcard, value ), rule=job.rule, ) def handle_protected(self, job): """ Write-protect output files that are marked with protected(). """ for f in job.expanded_output: if f in job.protected_output: logger.info("Write-protecting output file {}.".format(f)) f.protect() def handle_touch(self, job): """ Touches those output files that are marked for touching. """ for f in job.expanded_output: if f in job.touch_output: f = job.shadowed_path(f) logger.info("Touching output file {}.".format(f)) f.touch_or_create() assert os.path.exists(f) def temp_input(self, job): for job_, files in self.dependencies[job].items(): for f in filter(job_.temp_output.__contains__, files): yield f def temp_size(self, job): """Return the total size of temporary input files of the job. If none, return 0. """ return sum(f.size for f in self.temp_input(job)) def handle_temp(self, job): """ Remove temp files if they are no longer needed. Update temp_mtimes. """ if self.notemp: return is_temp = lambda f: is_flagged(f, "temp") # handle temp input needed = lambda job_, f: any( f in files for j, files in self.depending[job_].items() if not self.finished(j) and self.needrun(j) and j != job ) def unneeded_files(): # temp input for job_, files in self.dependencies[job].items(): tempfiles = set(f for f in job_.expanded_output if is_temp(f)) yield from filterfalse(partial(needed, job_), tempfiles & files) # temp output if not job.dynamic_output and ( job not in self.targetjobs or job.rule.name == self.workflow.first_rule ): tempfiles = ( f for f in job.expanded_output if is_temp(f) and f not in self.targetfiles ) yield from filterfalse(partial(needed, job), tempfiles) for f in unneeded_files(): logger.info("Removing temporary output file {}.".format(f)) f.remove(remove_non_empty_dir=True) def handle_log(self, job, upload_remote=True): for f in job.log: if not f.exists_local: # If log file was not created during job, create an empty one. f.touch_or_create() if upload_remote and f.is_remote and not f.should_stay_on_remote: f.upload_to_remote() if not f.exists_remote: raise RemoteFileException( "The file upload was attempted, but it does not " "exist on remote. Check that your credentials have " "read AND write permissions." ) def handle_remote(self, job, upload=True): """ Remove local files if they are no longer needed and upload. """ if upload: # handle output files files = list(job.expanded_output) if job.benchmark: files.append(job.benchmark) for f in files: if f.is_remote and not f.should_stay_on_remote: f.upload_to_remote() remote_mtime = f.mtime # immediately force local mtime to match remote, # since conversions from S3 headers are not 100% reliable # without this, newness comparisons may fail down the line f.touch(times=(remote_mtime, remote_mtime)) if not f.exists_remote: raise RemoteFileException( "The file upload was attempted, but it does not " "exist on remote. Check that your credentials have " "read AND write permissions." ) if not self.keep_remote_local: # handle input files needed = lambda job_, f: any( f in files for j, files in self.depending[job_].items() if not self.finished(j) and self.needrun(j) and j != job ) def unneeded_files(): putative = ( lambda f: f.is_remote and not f.protected and not f.should_keep_local ) generated_input = set() for job_, files in self.dependencies[job].items(): generated_input |= files for f in filter(putative, files): if not needed(job_, f): yield f for f, f_ in zip(job.output, job.rule.output): if putative(f) and not needed(job, f) and not f in self.targetfiles: if f in job.dynamic_output: for f_ in job.expand_dynamic(f_): yield f_ else: yield f for f in filter(putative, job.input): # TODO what about remote inputs that are used by multiple jobs? if f not in generated_input: yield f for f in unneeded_files(): if f.exists_local: logger.info("Removing local output file: {}".format(f)) f.remove() job.rmdir_empty_remote_dirs() def jobid(self, job): """Return job id of given job.""" if job.is_group(): return job.jobid else: return self._jobid[job] def update( self, jobs, file=None, visited=None, skip_until_dynamic=False, progress=False ): """ Update the DAG by adding given jobs and their dependencies. """ if visited is None: visited = set() producer = None exceptions = list() jobs = sorted(jobs, reverse=not self.ignore_ambiguity) cycles = list() for job in jobs: logger.dag_debug(dict(status="candidate", job=job)) if file in job.input: cycles.append(job) continue if job in visited: cycles.append(job) continue try: self.check_periodic_wildcards(job) self.update_( job, visited=set(visited), skip_until_dynamic=skip_until_dynamic, progress=progress, ) # TODO this might fail if a rule discarded here is needed # elsewhere if producer: if job < producer or self.ignore_ambiguity: break elif producer is not None: raise AmbiguousRuleException(file, job, producer) producer = job except ( MissingInputException, CyclicGraphException, PeriodicWildcardError, ) as ex: exceptions.append(ex) except RecursionError as e: raise WorkflowError( e, "If building the DAG exceeds the recursion limit, " "this is likely due to a cyclic dependency." "E.g. you might have a sequence of rules that " "can generate their own input. Try to make " "the output files more specific. " "A common pattern is to have different prefixes " "in the output files of different rules." + "\nProblematic file pattern: {}".format(file) if file else "", ) if producer is None: if cycles: job = cycles[0] raise CyclicGraphException(job.rule, file, rule=job.rule) if exceptions: raise exceptions[0] else: logger.dag_debug(dict(status="selected", job=producer)) n = len(self.dependencies) if progress and n % 1000 == 0 and n and self._progress != n: logger.info("Processed {} potential jobs.".format(n)) self._progress = n return producer def update_(self, job, visited=None, skip_until_dynamic=False, progress=False): """ Update the DAG by adding the given job and its dependencies. """ if job in self.dependencies: return if visited is None: visited = set() visited.add(job) dependencies = self.dependencies[job] potential_dependencies = self.collect_potential_dependencies(job) skip_until_dynamic = skip_until_dynamic and not job.dynamic_output missing_input = set() producer = dict() exceptions = dict() for file, jobs in potential_dependencies.items(): if not jobs: # no producing job found if not file.exists: # file not found, hence missing input missing_input.add(file) # file found, no problem continue try: selected_job = self.update( jobs, file=file, visited=visited, skip_until_dynamic=skip_until_dynamic or file in job.dynamic_input, progress=progress, ) producer[file] = selected_job except ( MissingInputException, CyclicGraphException, PeriodicWildcardError, ) as ex: if not file.exists: self.delete_job(job, recursive=False) # delete job from tree raise ex for file, job_ in producer.items(): dependencies[job_].add(file) self.depending[job_][job].add(file) if self.is_batch_rule(job.rule) and self.batch.is_final: # For the final batch, ensure that all input files from # previous batches are present on disk. if any( f for f in job.input if f not in potential_dependencies and not f.exists ): raise WorkflowError( "Unable to execute batch {} because not all previous batches " "have been completed before or files have been deleted.".format( self.batch ) ) if missing_input: self.delete_job(job, recursive=False) # delete job from tree raise MissingInputException(job.rule, missing_input) if skip_until_dynamic: self._dynamic.add(job) def update_needrun(self): """ Update the information whether a job needs to be executed. """ def output_mintime(job): for job_ in self.bfs(self.depending, job): t = job_.output_mintime if t: return t def needrun(job): reason = self.reason(job) noinitreason = not reason updated_subworkflow_input = self.updated_subworkflow_files.intersection( job.input ) if ( job not in self.omitforce and job.rule in self.forcerules or not self.forcefiles.isdisjoint(job.output) ): reason.forced = True elif updated_subworkflow_input: reason.updated_input.update(updated_subworkflow_input) elif job in self.targetjobs: # TODO find a way to handle added/removed input files here? if not job.output and not job.benchmark: if job.input: if job.rule.norun: reason.updated_input_run.update( [f for f in job.input if not f.exists] ) else: reason.nooutput = True else: reason.noio = True else: if job.rule in self.targetrules: missing_output = job.missing_output() else: missing_output = job.missing_output( requested=set(chain(*self.depending[job].values())) | self.targetfiles ) reason.missing_output.update(missing_output) if not reason: output_mintime_ = output_mintime(job) if output_mintime_: updated_input = [ f for f in job.input if f.exists and f.is_newer(output_mintime_) ] reason.updated_input.update(updated_input) if noinitreason and reason: reason.derived = False return job reason = self.reason _needrun = self._needrun dependencies = self.dependencies depending = self.depending _needrun.clear() candidates = set(self.jobs) queue = list(filter(reason, map(needrun, candidates))) visited = set(queue) while queue: job = queue.pop(0) _needrun.add(job) for job_, files in dependencies[job].items(): missing_output = job_.missing_output(requested=files) reason(job_).missing_output.update(missing_output) if missing_output and not job_ in visited: visited.add(job_) queue.append(job_) for job_, files in depending[job].items(): if job_ in candidates: reason(job_).updated_input_run.update(files) if not job_ in visited: visited.add(job_) queue.append(job_) # update len including finished jobs (because they have already increased the job counter) self._len = len(self._finished | self._needrun) def in_until(self, job): """Return whether given job has been specified via --until.""" return job.rule.name in self.untilrules or not self.untilfiles.isdisjoint( job.output ) def in_omitfrom(self, job): """Return whether given job has been specified via --omit-from.""" return job.rule.name in self.omitrules or not self.omitfiles.isdisjoint( job.output ) def until_jobs(self): """Returns a generator of jobs specified by untiljobs.""" return (job for job in self.jobs if self.in_until(job)) def omitfrom_jobs(self): """Returns a generator of jobs specified by omitfromjobs.""" return (job for job in self.jobs if self.in_omitfrom(job)) def downstream_of_omitfrom(self): """Returns the downstream of --omit-from rules or files and themselves.""" return self.bfs(self.depending, *self.omitfrom_jobs()) def delete_omitfrom_jobs(self): """Removes jobs downstream of jobs specified by --omit-from.""" if not self.omitrules and not self.omitfiles: return downstream_jobs = list( self.downstream_of_omitfrom() ) # need to cast as list before deleting jobs for job in downstream_jobs: self.delete_job(job, recursive=False, add_dependencies=True) def set_until_jobs(self): """Removes jobs downstream of jobs specified by --omit-from.""" if not self.untilrules and not self.untilfiles: return self.targetjobs = set(self.until_jobs()) def update_priority(self): """ Update job priorities. """ prioritized = ( lambda job: job.rule in self.priorityrules or not self.priorityfiles.isdisjoint(job.output) ) for job in self.needrun_jobs: self._priority[job] = job.rule.priority for job in self.bfs( self.dependencies, *filter(prioritized, self.needrun_jobs), stop=self.noneedrun_finished, ): self._priority[job] = Job.HIGHEST_PRIORITY def update_groups(self): groups = dict() for job in self.needrun_jobs: if job.group is None: continue stop = lambda j: j.group != job.group # BFS into depending needrun jobs if in same group # Note: never go up here (into depending), because it may contain # jobs that have been sorted out due to e.g. ruleorder. group = GroupJob( job.group, ( job for job in self.bfs(self.dependencies, job, stop=stop) if self.needrun(job) ), ) # merge with previously determined groups if present for j in group: if j in groups: other = groups[j] other.merge(group) group = other # update assignment for j in group: if j not in groups: groups[j] = group self._group = groups def update_ready(self, jobs=None): """ Update information whether a job is ready to execute. Given jobs must be needrun jobs! """ if jobs is None: jobs = self.needrun_jobs candidate_groups = set() for job in jobs: if not self.finished(job) and self._ready(job): if job.group is None: self._ready_jobs.add(job) else: group = self._group[job] group.finalize() candidate_groups.add(group) self._ready_jobs.update( group for group in candidate_groups if all(self._ready(job) for job in group) ) def get_jobs_or_groups(self): visited_groups = set() for job in self.jobs: if job.group is None: yield job else: group = self._group[job] if group in visited_groups: continue visited_groups.add(group) yield group def close_remote_objects(self): """Close all remote objects.""" for job in self.jobs: if not self.needrun(job): job.close_remote() def postprocess(self): """Postprocess the DAG. This has to be invoked after any change to the DAG topology.""" self.update_jobids() self.update_needrun() self.update_priority() self.handle_pipes() self.update_groups() self.update_ready() self.close_remote_objects() self.update_checkpoint_outputs() def handle_pipes(self): """Use pipes to determine job groups. Check if every pipe has exactly one consumer""" for job in self.needrun_jobs: candidate_groups = set() if job.group is not None: candidate_groups.add(job.group) all_depending = set() has_pipe = False for f in job.output: if is_flagged(f, "pipe"): if job.is_run: raise WorkflowError( "Rule defines pipe output but " "uses a 'run' directive. This is " "not possible for technical " "reasons. Consider using 'shell' or " "'script'.", rule=job.rule, ) has_pipe = True depending = [ j for j, files in self.depending[job].items() if f in files ] if len(depending) > 1: raise WorkflowError( "Output file {} is marked as pipe " "but more than one job depends on " "it. Make sure that any pipe " "output is only consumed by one " "job".format(f), rule=job.rule, ) elif len(depending) == 0: raise WorkflowError( "Output file {} is marked as pipe " "but it has no consumer. This is " "invalid because it can lead to " "a dead lock.".format(f), rule=job.rule, ) depending = depending[0] if depending.is_run: raise WorkflowError( "Rule consumes pipe input but " "uses a 'run' directive. This is " "not possible for technical " "reasons. Consider using 'shell' or " "'script'.", rule=job.rule, ) all_depending.add(depending) if depending.group is not None: candidate_groups.add(depending.group) if not has_pipe: continue if len(candidate_groups) > 1: raise WorkflowError( "An output file is marked as " "pipe, but consuming jobs " "are part of conflicting " "groups.", rule=job.rule, ) elif candidate_groups: # extend the candidate group to all involved jobs group = candidate_groups.pop() else: # generate a random unique group name group = str(uuid.uuid4()) job.group = group for j in all_depending: j.group = group def _ready(self, job): """Return whether the given job is ready to execute.""" group = self._group.get(job, None) if group is None: is_external_needrun_dep = self.needrun else: def is_external_needrun_dep(j): g = self._group.get(j, None) return self.needrun(j) and (g is None or g != group) return self._finished.issuperset( filter(is_external_needrun_dep, self.dependencies[job]) ) def update_checkpoint_dependencies(self, jobs=None): """Update dependencies of checkpoints.""" updated = False self.update_checkpoint_outputs() if jobs is None: jobs = [job for job in self.jobs if not self.needrun(job)] for job in jobs: if job.is_checkpoint: depending = list(self.depending[job]) # re-evaluate depending jobs, replace and update DAG for j in depending: logger.info("Updating job {} ({}).".format(self.jobid(j), j)) newjob = j.updated() self.replace_job(j, newjob, recursive=False) updated = True if updated: # This has to be done for each checkpoint, # otherwise, jobs may be missing in the end. self.postprocess() return updated def finish(self, job, update_dynamic=True): """Finish a given job (e.g. remove from ready jobs, mark depending jobs as ready).""" try: self._ready_jobs.remove(job) except KeyError: pass if job.is_group(): jobs = job else: jobs = [job] self._finished.update(jobs) updated_dag = False if update_dynamic: updated_dag = self.update_checkpoint_dependencies(jobs) # mark depending jobs as ready # skip jobs that are marked as until jobs self.update_ready( j for job in jobs for j in self.depending[job] if not self.in_until(job) and self.needrun(j) ) for job in jobs: if update_dynamic and job.dynamic_output: logger.info("Dynamically updating jobs") newjob = self.update_dynamic(job) if newjob: # simulate that this job ran and was finished before self.omitforce.add(newjob) self._needrun.add(newjob) self._finished.add(newjob) updated_dag = True self.postprocess() self.handle_protected(newjob) self.handle_touch(newjob) if updated_dag: # We might have new jobs, so we need to ensure that all conda envs # and singularity images are set up. if self.workflow.use_singularity: self.pull_singularity_imgs() if self.workflow.use_conda: self.create_conda_envs() def new_job(self, rule, targetfile=None, format_wildcards=None): """Create new job for given rule and (optional) targetfile. This will reuse existing jobs with the same wildcards.""" key = (rule, targetfile) if key in self.job_cache: assert targetfile is not None return self.job_cache[key] wildcards_dict = rule.get_wildcards(targetfile) job = Job( rule, self, wildcards_dict=wildcards_dict, format_wildcards=format_wildcards, targetfile=targetfile, ) self.cache_job(job) return job def cache_job(self, job): for f in job.products: self.job_cache[(job.rule, f)] = job def update_dynamic(self, job): """Update the DAG by evaluating the output of the given job that contains dynamic output files.""" dynamic_wildcards = job.dynamic_wildcards if not dynamic_wildcards: # this happens e.g. in dryrun if output is not yet present return depending = list( filter(lambda job_: not self.finished(job_), self.bfs(self.depending, job)) ) newrule, non_dynamic_wildcards = job.rule.dynamic_branch( dynamic_wildcards, input=False ) self.specialize_rule(job.rule, newrule) # no targetfile needed for job newjob = self.new_job(newrule, format_wildcards=non_dynamic_wildcards) self.replace_job(job, newjob) for job_ in depending: needs_update = any( f.get_wildcard_names() & dynamic_wildcards.keys() for f in job_.rule.dynamic_input ) if needs_update: newrule_ = job_.rule.dynamic_branch(dynamic_wildcards) if newrule_ is not None: self.specialize_rule(job_.rule, newrule_) if not self.dynamic(job_): logger.debug("Updating job {}.".format(job_)) newjob_ = self.new_job( newrule_, targetfile=job_.output[0] if job_.output else None ) unexpected_output = self.reason( job_ ).missing_output.intersection(newjob.existing_output) if unexpected_output: logger.warning( "Warning: the following output files of rule {} were not " "present when the DAG was created:\n{}".format( newjob_.rule, unexpected_output ) ) self.replace_job(job_, newjob_) return newjob def delete_job(self, job, recursive=True, add_dependencies=False): """Delete given job from DAG.""" if job in self.targetjobs: self.targetjobs.remove(job) if add_dependencies: for _job in self.dependencies[job]: self.targetjobs.add(_job) for job_ in self.depending[job]: del self.dependencies[job_][job] del self.depending[job] for job_ in self.dependencies[job]: depending = self.depending[job_] del depending[job] if not depending and recursive: self.delete_job(job_) del self.dependencies[job] if job in self._needrun: self._len -= 1 self._needrun.remove(job) del self._reason[job] if job in self._finished: self._finished.remove(job) if job in self._dynamic: self._dynamic.remove(job) if job in self._ready_jobs: self._ready_jobs.remove(job) # remove from cache for f in job.output: try: del self.job_cache[(job.rule, f)] except KeyError: pass def replace_job(self, job, newjob, recursive=True): """Replace given job with new job.""" add_to_targetjobs = job in self.targetjobs depending = list(self.depending[job].items()) if self.finished(job): self._finished.add(newjob) self.delete_job(job, recursive=recursive) if add_to_targetjobs: self.targetjobs.add(newjob) self.cache_job(newjob) self.update([newjob]) logger.debug("Replace {} with dynamic branch {}".format(job, newjob)) for job_, files in depending: # if not job_.dynamic_input: logger.debug("updating depending job {}".format(job_)) self.dependencies[job_][newjob].update(files) self.depending[newjob][job_].update(files) def specialize_rule(self, rule, newrule): """Specialize the given rule by inserting newrule into the DAG.""" assert newrule is not None self.rules.add(newrule) self.update_output_index() def is_batch_rule(self, rule): """Return True if the underlying rule is to be used for batching the DAG.""" return self.batch is not None and rule.name == self.batch.rulename def collect_potential_dependencies(self, job): """Collect all potential dependencies of a job. These might contain ambiguities. The keys of the returned dict represent the files to be considered.""" dependencies = defaultdict(list) # use a set to circumvent multiple jobs for the same file # if user specified it twice file2jobs = self.file2jobs input_files = list(job.unique_input) if self.is_batch_rule(job.rule): # only consider the defined partition of the input files input_batch = self.batch.get_batch(input_files) if len(input_batch) != len(input_files): logger.info( "Considering only batch {} for DAG computation.\n" "All jobs beyond the batching rule are omitted until the final batch.\n" "Don't forget to run the other batches too.".format(self.batch) ) input_files = input_batch for file in input_files: # omit the file if it comes from a subworkflow if file in job.subworkflow_input: continue try: if file in job.dependencies: jobs = [self.new_job(job.dependencies[file], targetfile=file)] else: jobs = file2jobs(file) dependencies[file].extend(jobs) except MissingRuleException as ex: # no dependency found dependencies[file] = [] return dependencies def bfs(self, direction, *jobs, stop=lambda job: False): """Perform a breadth-first traversal of the DAG.""" queue = list(jobs) visited = set(queue) while queue: job = queue.pop(0) if stop(job): # stop criterion reached for this node continue yield job for job_, _ in direction[job].items(): if not job_ in visited: queue.append(job_) visited.add(job_) def level_bfs(self, direction, *jobs, stop=lambda job: False): """Perform a breadth-first traversal of the DAG, but also yield the level together with each job.""" queue = [(job, 0) for job in jobs] visited = set(jobs) while queue: job, level = queue.pop(0) if stop(job): # stop criterion reached for this node continue yield level, job level += 1 for job_, _ in direction[job].items(): if not job_ in visited: queue.append((job_, level)) visited.add(job_) def dfs(self, direction, *jobs, stop=lambda job: False, post=True): """Perform depth-first traversal of the DAG.""" visited = set() def _dfs(job): """Inner function for DFS traversal.""" if stop(job): return if not post: yield job for job_ in direction[job]: if not job_ in visited: visited.add(job_) for j in _dfs(job_): yield j if post: yield job for job in jobs: for job_ in self._dfs(direction, job, visited, stop=stop, post=post): yield job_ def new_wildcards(self, job): """Return wildcards that are newly introduced in this job, compared to its ancestors.""" new_wildcards = set(job.wildcards.items()) for job_ in self.dependencies[job]: if not new_wildcards: return set() for wildcard in job_.wildcards.items(): new_wildcards.discard(wildcard) return new_wildcards def rule2job(self, targetrule): """Generate a new job from a given rule.""" if targetrule.has_wildcards(): raise WorkflowError( "Target rules may not contain wildcards. Please specify concrete files or a rule without wildcards." ) return self.new_job(targetrule) def file2jobs(self, targetfile): rules = self.output_index.match(targetfile) jobs = [] exceptions = list() for rule in rules: if rule.is_producer(targetfile): try: jobs.append(self.new_job(rule, targetfile=targetfile)) except InputFunctionException as e: exceptions.append(e) if not jobs: if exceptions: raise exceptions[0] raise MissingRuleException(targetfile) return jobs def rule_dot2(self): dag = defaultdict(list) visited = set() preselect = set() def preselect_parents(job): for parent in self.depending[job]: if parent in preselect: continue preselect.add(parent) preselect_parents(parent) def build_ruledag(job, key=lambda job: job.rule.name): if job in visited: return visited.add(job) deps = sorted(self.dependencies[job], key=key) deps = [ ( group[0] if preselect.isdisjoint(group) else preselect.intersection(group).pop() ) for group in (list(g) for _, g in groupby(deps, key)) ] dag[job].extend(deps) preselect_parents(job) for dep in deps: build_ruledag(dep) for job in self.targetjobs: build_ruledag(job) return self._dot(dag.keys(), print_wildcards=False, print_types=False, dag=dag) def rule_dot(self): graph = defaultdict(set) for job in self.jobs: graph[job.rule].update(dep.rule for dep in self.dependencies[job]) return self._dot(graph) def dot(self): def node2style(job): if not self.needrun(job): return "rounded,dashed" if self.dynamic(job) or job.dynamic_input: return "rounded,dotted" return "rounded" def format_wildcard(wildcard): name, value = wildcard if DYNAMIC_FILL in value: value = "..." return "{}: {}".format(name, value) node2rule = lambda job: job.rule node2label = lambda job: "\\n".join( chain( [job.rule.name], sorted(map(format_wildcard, self.new_wildcards(job))) ) ) dag = {job: self.dependencies[job] for job in self.jobs} return self._dot( dag, node2rule=node2rule, node2style=node2style, node2label=node2label ) def _dot( self, graph, node2rule=lambda node: node, node2style=lambda node: "rounded", node2label=lambda node: node, ): # color rules huefactor = 2 / (3 * len(self.rules)) rulecolor = { rule: "{:.2f} 0.6 0.85".format(i * huefactor) for i, rule in enumerate(self.rules) } # markup node_markup = '\t{}[label = "{}", color = "{}", style="{}"];'.format edge_markup = "\t{} -> {}".format # node ids ids = {node: i for i, node in enumerate(graph)} # calculate nodes nodes = [ node_markup( ids[node], node2label(node), rulecolor[node2rule(node)], node2style(node), ) for node in graph ] # calculate edges edges = [ edge_markup(ids[dep], ids[node]) for node, deps in graph.items() for dep in deps ] return textwrap.dedent( """\ digraph snakemake_dag {{ graph[bgcolor=white, margin=0]; node[shape=box, style=rounded, fontname=sans, \ fontsize=10, penwidth=2]; edge[penwidth=2, color=grey]; {items} }}\ """ ).format(items="\n".join(nodes + edges)) def filegraph_dot( self, node2rule=lambda node: node, node2style=lambda node: "rounded", node2label=lambda node: node, ): # NOTE: This is code from the rule_dot method. # This method could be split like there as well, however, # it cannot easily reuse the _dot method due to the different node type graph = defaultdict(set) for job in self.jobs: graph[job.rule].update(dep.rule for dep in self.dependencies[job]) # node ids ids = {node: i for i, node in enumerate(graph)} # Compute colors for rules def hsv_to_htmlhexrgb(h, s, v): """Convert hsv colors to hex-encoded rgb colors usable by html.""" import colorsys hex_r, hex_g, hex_b = (round(255 * x) for x in colorsys.hsv_to_rgb(h, s, v)) return "#{hex_r:0>2X}{hex_g:0>2X}{hex_b:0>2X}".format( hex_r=hex_r, hex_g=hex_g, hex_b=hex_b ) huefactor = 2 / (3 * len(self.rules)) rulecolor = { rule: hsv_to_htmlhexrgb(i * huefactor, 0.6, 0.85) for i, rule in enumerate(self.rules) } def resolve_input_functions(input_files): """Iterate over all input files and replace input functions with a fixed string. """ files = [] for f in input_files: if callable(f): files.append("") # NOTE: This is a workaround. It would be more informative # to show the code of the input function here (if it is # short enough). This cannot be easily done with the inspect # module, since the line numbers in the Snakefile do not # behave as expected. One (complicated) solution for this # would be to find the Snakefile and directly extract the # code of the function. else: files.append(repr(f).strip("'")) return files def html_node(node_id, node, color): """Assemble a html style node for graphviz""" input_files = resolve_input_functions(node._input) output_files = [repr(f).strip("'") for f in node._output] input_header = ( '↪ input' if input_files else "" ) output_header = ( 'output →' if output_files else "" ) html_node = [ '{node_id} [ shape=none, margin=0, label=<'.format( node_id=node_id, color=color ), "", "
", ''.format( input_header=input_header ), ] for filename in sorted(input_files): # Escape html relevant chars like '<' and '>' in filenames # These can be added by input functions etc. and cannot be # displayed in graphviz HTML nodes. in_file = html.escape(filename) html_node.extend( [ "", ''.format( in_file=in_file ), "", ] ) html_node.append("
") html_node.append( ''.format( output_header=output_header ) ) for filename in sorted(output_files): out_file = html.escape(filename) html_node.extend( [ "", '' "".format(out_file=out_file), ] ) html_node.append("
", '{node.name}'.format(node=node), "
{input_header}
{in_file}
{output_header}
{out_file}
>]") return "\n".join(html_node) nodes = [ html_node(ids[node], node, rulecolor[node2rule(node)]) for node in graph ] # calculate edges edge_markup = "\t{} -> {}".format edges = [ edge_markup(ids[dep], ids[node], ids[dep], ids[node]) for node, deps in graph.items() for dep in deps ] return textwrap.dedent( """\ digraph snakemake_dag {{ graph[bgcolor=white, margin=0]; node[shape=box, style=rounded, fontname=sans, \ fontsize=10, penwidth=2]; edge[penwidth=2, color=grey]; {items} }}\ """ ).format(items="\n".join(nodes + edges)) def summary(self, detailed=False): if detailed: yield "output_file\tdate\trule\tversion\tlog-file(s)\tinput-file(s)\tshellcmd\tstatus\tplan" else: yield "output_file\tdate\trule\tversion\tlog-file(s)\tstatus\tplan" for job in self.jobs: output = job.rule.output if self.dynamic(job) else job.expanded_output for f in output: rule = self.workflow.persistence.rule(f) rule = "-" if rule is None else rule version = self.workflow.persistence.version(f) version = "-" if version is None else str(version) date = time.ctime(f.mtime) if f.exists else "-" pending = "update pending" if self.reason(job) else "no update" log = self.workflow.persistence.log(f) log = "-" if log is None else ",".join(log) input = self.workflow.persistence.input(f) input = "-" if input is None else ",".join(input) shellcmd = self.workflow.persistence.shellcmd(f) shellcmd = "-" if shellcmd is None else shellcmd # remove new line characters, leading and trailing whitespace shellcmd = shellcmd.strip().replace("\n", "; ") status = "ok" if not f.exists: status = "missing" elif self.reason(job).updated_input: status = "updated input files" elif self.workflow.persistence.version_changed(job, file=f): status = "version changed to {}".format(job.rule.version) elif self.workflow.persistence.code_changed(job, file=f): status = "rule implementation changed" elif self.workflow.persistence.input_changed(job, file=f): status = "set of input files changed" elif self.workflow.persistence.params_changed(job, file=f): status = "params changed" if detailed: yield "\t".join( (f, date, rule, version, log, input, shellcmd, status, pending) ) else: yield "\t".join((f, date, rule, version, log, status, pending)) def archive(self, path): """Archives workflow such that it can be re-run on a different system. Archiving includes git versioned files (i.e. Snakefiles, config files, ...), ancestral input files and conda environments. """ if path.endswith(".tar"): mode = "x" elif path.endswith("tar.bz2"): mode = "x:bz2" elif path.endswith("tar.xz"): mode = "x:xz" elif path.endswith("tar.gz"): mode = "x:gz" else: raise WorkflowError( "Unsupported archive format " "(supported: .tar, .tar.gz, .tar.bz2, .tar.xz)" ) if os.path.exists(path): raise WorkflowError("Archive already exists:\n" + path) self.create_conda_envs(forceall=True) try: workdir = Path(os.path.abspath(os.getcwd())) with tarfile.open(path, mode=mode, dereference=True) as archive: archived = set() def add(path): if workdir not in Path(os.path.abspath(path)).parents: logger.warning( "Path {} cannot be archived: " "not within working directory.".format(path) ) else: f = os.path.relpath(path) if f not in archived: archive.add(f) archived.add(f) logger.info("archived " + f) logger.info( "Archiving snakefiles, scripts and files under " "version control..." ) for f in self.workflow.get_sources(): add(f) logger.info("Archiving external input files...") for job in self.jobs: # input files for f in job.input: if not any( f in files for files in self.dependencies[job].values() ): # this is an input file that is not created by any job add(f) logger.info("Archiving conda environments...") envs = set() for job in self.jobs: if job.conda_env_file: env_archive = job.archive_conda_env() envs.add(env_archive) for env in envs: add(env) except (Exception, BaseException) as e: os.remove(path) raise e def clean(self, only_temp=False, dryrun=False): """Removes files generated by the workflow. """ for job in self.jobs: for f in job.output: if not only_temp or is_flagged(f, "temp"): # The reason for the second check is that dangling # symlinks fail f.exists. if f.exists or os.path.islink(f): if f.protected: logger.error("Skipping write-protected file {}.".format(f)) else: msg = "Deleting {}" if not dryrun else "Would delete {}" logger.info(msg.format(f)) if not dryrun: # Remove non-empty dirs if flagged as temp() f.remove(remove_non_empty_dir=only_temp) def list_untracked(self): """List files in the workdir that are not in the dag. """ used_files = set() files_in_cwd = set() for job in self.jobs: used_files.update( os.path.relpath(file) for file in chain(job.local_input, job.local_output, job.log) ) for root, dirs, files in os.walk(os.getcwd()): # Ignore hidden files and don't traverse into hidden dirs files_in_cwd.update( [ os.path.relpath(os.path.join(root, f)) for f in files if not f[0] == "." ] ) dirs[:] = [d for d in dirs if not d[0] == "."] for f in sorted(list(files_in_cwd - used_files)): logger.info(f) def d3dag(self, max_jobs=10000): def node(job): jobid = self.jobid(job) return { "id": jobid, "value": { "jobid": jobid, "label": job.rule.name, "rule": job.rule.name, }, } def edge(a, b): return {"u": self.jobid(a), "v": self.jobid(b)} jobs = list(self.jobs) if len(jobs) > max_jobs: logger.info( "Job-DAG is too large for visualization (>{} jobs).".format(max_jobs) ) else: logger.d3dag( nodes=[node(job) for job in jobs], edges=[ edge(dep, job) for job in jobs for dep in self.dependencies[job] if self.needrun(dep) ], ) def stats(self): rules = Counter() rules.update(job.rule for job in self.needrun_jobs) rules.update(job.rule for job in self.finished_jobs) yield "Job counts:" yield "\tcount\tjobs" for rule, count in sorted(rules.most_common(), key=lambda item: item[0].name): yield "\t{}\t{}".format(count, rule) yield "\t{}".format(len(self)) def __str__(self): return self.dot() def __len__(self): return self._len snakemake-5.10.0/snakemake/decorators.py000066400000000000000000000007461361131222100202110ustar00rootroot00000000000000__author__ = "Christopher Tomkins-Tinch" __copyright__ = "Copyright 2015, Christopher Tomkins-Tinch" __email__ = "tomkinsc@broadinstitute.org" __license__ = "MIT" import functools import inspect def dec_all_methods(decorator, prefix="test_"): def dec_class(cls): for name, m in inspect.getmembers(cls, inspect.isfunction): if prefix == None or name.startswith(prefix): setattr(cls, name, decorator(m)) return cls return dec_class snakemake-5.10.0/snakemake/deployment/000077500000000000000000000000001361131222100176435ustar00rootroot00000000000000snakemake-5.10.0/snakemake/deployment/__init__.py000066400000000000000000000000001361131222100217420ustar00rootroot00000000000000snakemake-5.10.0/snakemake/deployment/conda.py000066400000000000000000000372711361131222100213130ustar00rootroot00000000000000__author__ = "Johannes Köster" __copyright__ = "Copyright 2015-2019, Johannes Köster" __email__ = "johannes.koester@uni-due.de" __license__ = "MIT" import os import re import subprocess import tempfile from urllib.request import urlopen from urllib.parse import urlparse from urllib.error import URLError import hashlib import shutil from distutils.version import StrictVersion import json from glob import glob import tarfile import uuid from snakemake.exceptions import CreateCondaEnvironmentException, WorkflowError from snakemake.logging import logger from snakemake.common import strip_prefix from snakemake import utils from snakemake.deployment import singularity from snakemake.io import git_content def content(env_file): if env_file.startswith("git+file:"): return git_content(env_file).encode("utf-8") elif urlparse(env_file).scheme: try: return urlopen(env_file).read() except URLError as e: raise WorkflowError( "Failed to open environment file {}:".format(env_file), e ) else: if not os.path.exists(env_file): raise WorkflowError("Conda env file does not " "exist: {}".format(env_file)) with open(env_file, "rb") as f: return f.read() class Env: """Conda environment from a given specification file.""" def __init__(self, env_file, dag, singularity_img=None): self.file = env_file self._env_dir = dag.workflow.persistence.conda_env_path self._env_archive_dir = dag.workflow.persistence.conda_env_archive_path self._hash = None self._content_hash = None self._content = None self._path = None self._archive_file = None self._singularity_img = singularity_img @property def singularity_img_url(self): return self._singularity_img.url if self._singularity_img else None @property def content(self): if self._content is None: self._content = content(self.file) return self._content @property def hash(self): if self._hash is None: md5hash = hashlib.md5() # Include the absolute path of the target env dir into the hash. # By this, moving the working directory around automatically # invalidates all environments. This is necessary, because binaries # in conda environments can contain hardcoded absolute RPATHs. env_dir = os.path.realpath(self._env_dir) md5hash.update(env_dir.encode()) if self._singularity_img: md5hash.update(self._singularity_img.url.encode()) md5hash.update(self.content) self._hash = md5hash.hexdigest() return self._hash @property def content_hash(self): if self._content_hash is None: md5hash = hashlib.md5() md5hash.update(self.content) self._content_hash = md5hash.hexdigest() return self._content_hash @property def path(self): """Path to directory of the conda environment. First tries full hash, if it does not exist, (8-prefix) is used as default. """ hash = self.hash env_dir = self._env_dir for h in [hash, hash[:8]]: path = os.path.join(env_dir, h) if os.path.exists(path): return path return path @property def archive_file(self): """Path to archive of the conda environment, which may or may not exist.""" if self._archive_file is None: self._archive_file = os.path.join(self._env_archive_dir, self.content_hash) return self._archive_file def create_archive(self): """Create self-contained archive of environment.""" from snakemake.shell import shell try: import yaml except ImportError: raise WorkflowError( "Error importing PyYAML. " "Please install PyYAML to archive workflows." ) # importing requests locally because it interferes with instantiating conda environments import requests env_archive = self.archive_file if os.path.exists(env_archive): return env_archive try: # Download logger.info( "Downloading packages for conda environment {}...".format(self.file) ) os.makedirs(env_archive, exist_ok=True) try: out = shell.check_output( "conda list --explicit --prefix '{}'".format(self.path), stderr=subprocess.STDOUT, ) logger.debug(out.decode()) except subprocess.CalledProcessError as e: raise WorkflowError( "Error exporting conda packages:\n" + e.output.decode() ) with open(os.path.join(env_archive, "packages.txt"), "w") as pkg_list: for l in out.decode().split("\n"): if l and not l.startswith("#") and not l.startswith("@"): pkg_url = l logger.info(pkg_url) parsed = urlparse(pkg_url) pkg_name = os.path.basename(parsed.path) # write package name to list print(pkg_name, file=pkg_list) # download package pkg_path = os.path.join(env_archive, pkg_name) with open(pkg_path, "wb") as copy: r = requests.get(pkg_url) r.raise_for_status() copy.write(r.content) try: tarfile.open(pkg_path) except: raise WorkflowError( "Package is invalid tar archive: {}".format(pkg_url) ) except ( requests.exceptions.ChunkedEncodingError, requests.exceptions.HTTPError, ) as e: shutil.rmtree(env_archive) raise WorkflowError("Error downloading conda package {}.".format(pkg_url)) except (Exception, BaseException) as e: shutil.rmtree(env_archive) raise e return env_archive def create(self, dryrun=False): """ Create the conda enviroment.""" from snakemake.shell import shell # Read env file and create hash. env_file = self.file tmp_file = None url_scheme, *_ = urlparse(env_file) if (url_scheme and not url_scheme == "file") or ( not url_scheme and env_file.startswith("git+file:/") ): with tempfile.NamedTemporaryFile(delete=False, suffix=".yaml") as tmp: tmp.write(self.content) env_file = tmp.name tmp_file = tmp.name env_hash = self.hash env_path = self.path # Check for broken environment if os.path.exists( os.path.join(env_path, "env_setup_start") ) and not os.path.exists(os.path.join(env_path, "env_setup_done")): if dryrun: logger.info( "Incomplete Conda environment {} will be recreated.".format( utils.simplify_path(self.file) ) ) else: logger.info( "Removing incomplete Conda environment {}...".format( utils.simplify_path(self.file) ) ) shutil.rmtree(env_path, ignore_errors=True) # Create environment if not already present. if not os.path.exists(env_path): if dryrun: logger.info( "Conda environment {} will be created.".format( utils.simplify_path(self.file) ) ) return env_path conda = Conda(self._singularity_img) logger.info( "Creating conda environment {}...".format( utils.simplify_path(self.file) ) ) # Check if env archive exists. Use that if present. env_archive = self.archive_file try: # Touch "start" flag file os.makedirs(env_path, exist_ok=True) with open(os.path.join(env_path, "env_setup_start"), "a") as f: pass if os.path.exists(env_archive): logger.info("Installing archived conda packages.") pkg_list = os.path.join(env_archive, "packages.txt") if os.path.exists(pkg_list): # read pacakges in correct order # this is for newer env archives where the package list # was stored packages = [ os.path.join(env_archive, pkg.rstrip()) for pkg in open(pkg_list) ] else: # guess order packages = glob(os.path.join(env_archive, "*.tar.bz2")) # install packages manually from env archive cmd = " ".join( ["conda", "create", "--copy", "--prefix '{}'".format(env_path)] + packages ) if self._singularity_img: cmd = singularity.shellcmd( self._singularity_img.path, cmd, envvars=self.get_singularity_envvars(), ) out = shell.check_output(cmd, stderr=subprocess.STDOUT) else: # Copy env file to env_path (because they can be on # different volumes and singularity should only mount one). # In addition, this allows to immediately see what an # environment in .snakemake/conda contains. target_env_file = env_path + ".yaml" shutil.copy(env_file, target_env_file) logger.info("Downloading and installing remote packages.") cmd = " ".join( [ "conda", "env", "create", "--file '{}'".format(target_env_file), "--prefix '{}'".format(env_path), ] ) if self._singularity_img: cmd = singularity.shellcmd( self._singularity_img.path, cmd, envvars=self.get_singularity_envvars(), ) out = shell.check_output(cmd, stderr=subprocess.STDOUT) # Touch "done" flag file with open(os.path.join(env_path, "env_setup_done"), "a") as f: pass logger.debug(out.decode()) logger.info( "Environment for {} created (location: {})".format( os.path.relpath(env_file), os.path.relpath(env_path) ) ) except subprocess.CalledProcessError as e: # remove potential partially installed environment shutil.rmtree(env_path, ignore_errors=True) raise CreateCondaEnvironmentException( "Could not create conda environment from {}:\n".format(env_file) + e.output.decode() ) if tmp_file: # temporary file was created os.remove(tmp_file) return env_path @classmethod def get_singularity_envvars(self): return {"CONDA_PKGS_DIRS": "/tmp/conda/{}".format(uuid.uuid4())} def __hash__(self): # this hash is only for object comparison, not for env paths return hash(self.file) def __eq__(self, other): if isinstance(other, Env): return self.file == other.file return False class Conda: instances = dict() def __new__(cls, singularity_img=None): if singularity_img not in cls.instances: inst = super().__new__(cls) inst.__init__(singularity_img=singularity_img) cls.instances[singularity_img] = inst return inst else: return cls.instances[singularity_img] def __init__(self, singularity_img=None): from snakemake.shell import shell from snakemake.deployment import singularity if isinstance(singularity_img, singularity.Image): singularity_img = singularity_img.path self.singularity_img = singularity_img self._check() self.info = json.loads(shell.check_output(self._get_cmd("conda info --json"))) def _get_cmd(self, cmd): if self.singularity_img: return singularity.shellcmd(self.singularity_img, cmd) return cmd def _check(self): from snakemake.shell import shell try: # Use type here since conda now is a function. # type allows to check for both functions and regular commands. shell.check_output(self._get_cmd("type conda"), stderr=subprocess.STDOUT) except subprocess.CalledProcessError as e: if self.singularity_img: raise CreateCondaEnvironmentException( "The 'conda' command is not " "available inside " "your singularity container " "image. Snakemake mounts " "your conda installation " "into singularity. " "Sometimes, this can fail " "because of shell restrictions. " "It has been tested to work " "with docker://ubuntu, but " "it e.g. fails with " "docker://bash " ) else: raise CreateCondaEnvironmentException( "The 'conda' command is not " "available in the " "shell {} that will be " "used by Snakemake. You have " "to ensure that it is in your " "PATH, e.g., first activating " "the conda base environment " "with `conda activate base`.".format(shell.get_executable()) ) try: version = shell.check_output( self._get_cmd("conda --version"), stderr=subprocess.STDOUT ).decode() version = version.split()[1] if StrictVersion(version) < StrictVersion("4.2"): raise CreateCondaEnvironmentException( "Conda must be version 4.2 or later, found version {}.".format( version ) ) except subprocess.CalledProcessError as e: raise CreateCondaEnvironmentException( "Unable to check conda version:\n" + e.output.decode() ) def prefix_path(self): return self.info["conda_prefix"] def bin_path(self): return os.path.join(self.prefix_path(), "bin") def shellcmd(self, env_path, cmd): from snakemake.shell import shell # get path to activate script activate = os.path.join(self.bin_path(), "activate") return "source {} '{}'; {}".format(activate, env_path, cmd) snakemake-5.10.0/snakemake/deployment/env_modules.py000066400000000000000000000011201361131222100225270ustar00rootroot00000000000000__author__ = "Johannes Köster" __copyright__ = "Copyright 2015-2019, Johannes Köster" __email__ = "johannes.koester@uni-due.de" __license__ = "MIT" class EnvModules: def __init__(self, *module_names): self.names = module_names def shellcmd(self, cmd): """Return shell command with given modules loaded.""" loads = " ".join(self._load_module(name) for name in self.names) return "{} {}".format(loads, cmd) def _load_module(self, name): return "module load {};".format(name) def __str__(self): return ", ".join(self.names) snakemake-5.10.0/snakemake/deployment/singularity.py000066400000000000000000000103471361131222100225740ustar00rootroot00000000000000__author__ = "Johannes Köster" __copyright__ = "Copyright 2015-2019, Johannes Köster" __email__ = "johannes.koester@uni-due.de" __license__ = "MIT" import subprocess import shutil import os from urllib.parse import urlparse import hashlib from distutils.version import LooseVersion import snakemake from snakemake.deployment.conda import Conda from snakemake.common import lazy_property, SNAKEMAKE_SEARCHPATH from snakemake.exceptions import WorkflowError from snakemake.logging import logger SNAKEMAKE_MOUNTPOINT = "/mnt/snakemake" class Image: def __init__(self, url, dag): if " " in url: raise WorkflowError( "Invalid singularity image URL containing " "whitespace." ) if not shutil.which("singularity"): raise WorkflowError( "The singularity command has to be " "available in order to use singularity " "integration." ) try: v = subprocess.check_output( ["singularity", "--version"], stderr=subprocess.PIPE ).decode() except subprocess.CalledProcessError as e: raise WorkflowError( "Failed to get singularity version:\n{}".format(e.stderr.decode()) ) v = v.rsplit(" ", 1)[-1] if v.startswith("v"): v = v[1:] if not LooseVersion(v) >= LooseVersion("2.4.1"): raise WorkflowError("Minimum singularity version is 2.4.1.") self.url = url self._img_dir = dag.workflow.persistence.singularity_img_path @property def is_local(self): scheme = urlparse(self.url).scheme return not scheme or scheme == "file" @lazy_property def hash(self): md5hash = hashlib.md5() md5hash.update(self.url.encode()) return md5hash.hexdigest() def pull(self, dryrun=False): if self.is_local: return if dryrun: logger.info("Singularity image {} will be pulled.".format(self.url)) return logger.debug("Singularity image location: {}".format(self.path)) if not os.path.exists(self.path): logger.info("Pulling singularity image {}.".format(self.url)) try: p = subprocess.check_output( [ "singularity", "pull", "--name", "{}.simg".format(self.hash), self.url, ], cwd=self._img_dir, stderr=subprocess.STDOUT, ) except subprocess.CalledProcessError as e: raise WorkflowError( "Failed to pull singularity image " "from {}:\n{}".format(self.url, e.stdout.decode()) ) @property def path(self): if self.is_local: return urlparse(self.url).path return os.path.join(self._img_dir, self.hash) + ".simg" def __hash__(self): return hash(self.hash) def __eq__(self, other): return self.url == other.url def shellcmd( img_path, cmd, args="", envvars=None, shell_executable=None, container_workdir=None ): """Execute shell command inside singularity container given optional args and environment variables to be passed.""" if envvars: envvars = " ".join( "SINGULARITYENV_{}={}".format(k, v) for k, v in envvars.items() ) else: envvars = "" if shell_executable is None: shell_executable = "sh" else: # Ensure to just use the name of the executable, not a path, # because we cannot be sure where it is located in the container. shell_executable = os.path.split(shell_executable)[-1] # mount host snakemake module into container args += " --bind {}:{}".format(SNAKEMAKE_SEARCHPATH, SNAKEMAKE_MOUNTPOINT) if container_workdir: args += " --pwd {}".format(container_workdir) cmd = "{} singularity exec --home {} {} {} {} -c '{}'".format( envvars, os.getcwd(), args, img_path, shell_executable, cmd.replace("'", r"'\''"), ) logger.debug(cmd) return cmd snakemake-5.10.0/snakemake/exceptions.py000066400000000000000000000362511361131222100202250ustar00rootroot00000000000000__author__ = "Johannes Köster" __copyright__ = "Copyright 2015-2019, Johannes Köster" __email__ = "koester@jimmy.harvard.edu" __license__ = "MIT" import os import traceback from tokenize import TokenError from snakemake.logging import logger def format_error(ex, lineno, linemaps=None, snakefile=None, show_traceback=False): if linemaps is None: linemaps = dict() msg = str(ex) if linemaps and snakefile and snakefile in linemaps: lineno = linemaps[snakefile][lineno] if isinstance(ex, SyntaxError): msg = ex.msg location = ( " in line {} of {}".format(lineno, snakefile) if lineno and snakefile else "" ) tb = "" if show_traceback: tb = "\n".join(format_traceback(cut_traceback(ex), linemaps=linemaps)) return "{}{}{}{}".format( ex.__class__.__name__, location, ":\n" + msg if msg else ".", "\n{}".format(tb) if show_traceback and tb else "", ) def get_exception_origin(ex, linemaps): for file, lineno, _, _ in reversed(traceback.extract_tb(ex.__traceback__)): if file in linemaps: return lineno, file def cut_traceback(ex): snakemake_path = os.path.dirname(__file__) for line in traceback.extract_tb(ex.__traceback__): dir = os.path.dirname(line[0]) if not dir: dir = "." if not os.path.isdir(dir) or not os.path.samefile(snakemake_path, dir): yield line def format_traceback(tb, linemaps): for file, lineno, function, code in tb: if file in linemaps: lineno = linemaps[file][lineno] if code is not None: yield ' File "{}", line {}, in {}'.format(file, lineno, function) def log_verbose_traceback(ex): tb = "Full " + "".join(traceback.format_exception(type(ex), ex, ex.__traceback__)) logger.debug(tb) def print_exception(ex, linemaps): """ Print an error message for a given exception. Arguments ex -- the exception linemaps -- a dict of a dict that maps for each snakefile the compiled lines to source code lines in the snakefile. """ log_verbose_traceback(ex) if isinstance(ex, SyntaxError) or isinstance(ex, IndentationError): logger.error( format_error( ex, ex.lineno, linemaps=linemaps, snakefile=ex.filename, show_traceback=True, ) ) return origin = get_exception_origin(ex, linemaps) if origin is not None: lineno, file = origin logger.error( format_error( ex, lineno, linemaps=linemaps, snakefile=file, show_traceback=True ) ) return elif isinstance(ex, TokenError): logger.error(format_error(ex, None, show_traceback=False)) elif isinstance(ex, MissingRuleException): logger.error( format_error( ex, None, linemaps=linemaps, snakefile=ex.filename, show_traceback=False ) ) elif isinstance(ex, RuleException): for e in ex._include + [ex]: if not e.omit: logger.error( format_error( e, e.lineno, linemaps=linemaps, snakefile=e.filename, show_traceback=True, ) ) elif isinstance(ex, WorkflowError): logger.error( format_error( ex, ex.lineno, linemaps=linemaps, snakefile=ex.snakefile, show_traceback=True, ) ) elif isinstance(ex, KeyboardInterrupt): logger.info("Cancelling snakemake on user request.") else: traceback.print_exception(type(ex), ex, ex.__traceback__) class WorkflowError(Exception): @staticmethod def format_arg(arg): if isinstance(arg, str): return arg else: return "{}: {}".format(arg.__class__.__name__, str(arg)) def __init__(self, *args, lineno=None, snakefile=None, rule=None): super().__init__("\n".join(self.format_arg(arg) for arg in args)) if rule is not None: self.lineno = rule.lineno self.snakefile = rule.snakefile else: self.lineno = lineno self.snakefile = snakefile self.rule = rule class WildcardError(WorkflowError): pass class RuleException(Exception): """ Base class for exception occuring within the execution or definition of rules. """ def __init__( self, message=None, include=None, lineno=None, snakefile=None, rule=None ): """ Creates a new instance of RuleException. Arguments message -- the exception message include -- iterable of other exceptions to be included lineno -- the line the exception originates snakefile -- the file the exception originates """ super(RuleException, self).__init__(message) self._include = set() if include: for ex in include: self._include.add(ex) self._include.update(ex._include) if rule is not None: if lineno is None: lineno = rule.lineno if snakefile is None: snakefile = rule.snakefile self._include = list(self._include) self.lineno = lineno self.filename = snakefile self.omit = not message @property def messages(self): return map(str, (ex for ex in self._include + [self] if not ex.omit)) class InputFunctionException(WorkflowError): def __init__(self, msg, wildcards=None, lineno=None, snakefile=None, rule=None): msg = ( self.format_arg(msg) + "\nWildcards:\n" + "\n".join( "{}={}".format(name, value) for name, value in wildcards.items() ) ) super().__init__(msg, lineno=lineno, snakefile=snakefile, rule=rule) class ChildIOException(WorkflowError): def __init__( self, parent=None, child=None, wildcards=None, lineno=None, snakefile=None, rule=None, ): msg = "File/directory is a child to another output:\n" + "{}\n{}".format( parent, child ) super().__init__(msg, lineno=lineno, snakefile=snakefile, rule=rule) class MissingOutputException(RuleException): pass class IOException(RuleException): def __init__(self, prefix, rule, files, include=None, lineno=None, snakefile=None): message = ( "{} for rule {}:\n{}".format(prefix, rule, "\n".join(files)) if files else "" ) super().__init__( message=message, include=include, lineno=lineno, snakefile=snakefile, rule=rule, ) class MissingInputException(IOException): def __init__(self, rule, files, include=None, lineno=None, snakefile=None): msg = "Missing input files" if any(map(lambda f: f.startswith("~"), files)): msg += ( "(Using '~' in your paths is not allowed as such platform " "specific syntax is not resolved by Snakemake. In general, " "try sticking to relative paths for everything inside the " "working directory.)" ) super().__init__(msg, rule, files, include, lineno=lineno, snakefile=snakefile) class PeriodicWildcardError(RuleException): pass class ProtectedOutputException(IOException): def __init__(self, rule, files, include=None, lineno=None, snakefile=None): super().__init__( "Write-protected output files", rule, files, include, lineno=lineno, snakefile=snakefile, ) class ImproperOutputException(IOException): def __init__(self, rule, files, include=None, lineno=None, snakefile=None): super().__init__( "Outputs of incorrect type (directories when expecting files or vice versa). " "Output directories must be flagged with directory().", rule, files, include, lineno=lineno, snakefile=snakefile, ) class UnexpectedOutputException(IOException): def __init__(self, rule, files, include=None, lineno=None, snakefile=None): super().__init__( "Unexpectedly present output files " "(accidentally created by other rule?)", rule, files, include, lineno=lineno, snakefile=snakefile, ) class ImproperShadowException(RuleException): def __init__(self, rule, lineno=None, snakefile=None): super().__init__( "Rule cannot shadow if using ThreadPoolExecutor", rule=rule, lineno=lineno, snakefile=snakefile, ) class AmbiguousRuleException(RuleException): def __init__(self, filename, job_a, job_b, lineno=None, snakefile=None): from snakemake import utils wildcards_a = utils.format("{}", job_a._format_wildcards) wildcards_b = utils.format("{}", job_b._format_wildcards) super().__init__( "Rules {job_a} and {job_b} are ambiguous for the file {f}.\n" "Consider starting rule output with a unique prefix, constrain " "your wildcards, or use the ruleorder directive.\n" "Wildcards:\n" "\t{job_a}: {wildcards_a}\n" "\t{job_b}: {wildcards_b}\n" "Expected input files:\n" "\t{job_a}: {job_a.input}\n" "\t{job_b}: {job_b.input}" "Expected output files:\n" "\t{job_a}: {job_a.output}\n" "\t{job_b}: {job_b.output}".format( job_a=job_a, job_b=job_b, f=filename, wildcards_a=wildcards_a, wildcards_b=wildcards_b, ), lineno=lineno, snakefile=snakefile, ) self.rule1, self.rule2 = job_a.rule, job_b.rule class CyclicGraphException(RuleException): def __init__(self, repeatedrule, file, rule=None): super().__init__( "Cyclic dependency on rule {}.".format(repeatedrule), rule=rule ) self.file = file class MissingRuleException(RuleException): def __init__(self, file, lineno=None, snakefile=None): super().__init__( "No rule to produce {} (if you use input functions make sure that they don't raise unexpected exceptions).".format( file ), lineno=lineno, snakefile=snakefile, ) class UnknownRuleException(RuleException): def __init__(self, name, prefix="", lineno=None, snakefile=None): msg = "There is no rule named {}.".format(name) if prefix: msg = "{} {}".format(prefix, msg) super().__init__(msg, lineno=lineno, snakefile=snakefile) class NoRulesException(RuleException): def __init__(self, lineno=None, snakefile=None): super().__init__( "There has to be at least one rule.", lineno=lineno, snakefile=snakefile ) class IncompleteFilesException(RuleException): def __init__(self, files): super().__init__( "The files below seem to be incomplete. " "If you are sure that certain files are not incomplete, " "mark them as complete with\n\n" " snakemake --cleanup-metadata \n\n" "To re-generate the files rerun your command with the " "--rerun-incomplete flag.\nIncomplete files:\n{}".format("\n".join(files)) ) class IOFileException(RuleException): def __init__(self, msg, lineno=None, snakefile=None): super().__init__(msg, lineno=lineno, snakefile=snakefile) class RemoteFileException(RuleException): def __init__(self, msg, lineno=None, snakefile=None): super().__init__(msg, lineno=lineno, snakefile=snakefile) class HTTPFileException(RuleException): def __init__(self, msg, lineno=None, snakefile=None): super().__init__(msg, lineno=lineno, snakefile=snakefile) class FTPFileException(RuleException): def __init__(self, msg, lineno=None, snakefile=None): super().__init__(msg, lineno=lineno, snakefile=snakefile) class S3FileException(RuleException): def __init__(self, msg, lineno=None, snakefile=None): super().__init__(msg, lineno=lineno, snakefile=snakefile) class AzureFileException(RuleException): def __init__(self, msg, lineno=None, snakefile=None): super().__init__(msg, lineno=lineno, snakefile=snakefile) class SFTPFileException(RuleException): def __init__(self, msg, lineno=None, snakefile=None): super().__init__(msg, lineno=lineno, snakefile=snakefile) class DropboxFileException(RuleException): def __init__(self, msg, lineno=None, snakefile=None): super().__init__(msg, lineno=lineno, snakefile=snakefile) class XRootDFileException(RuleException): def __init__(self, msg, lineno=None, snakefile=None): super().__init__(msg, lineno=lineno, snakefile=snakefile) class NCBIFileException(RuleException): def __init__(self, msg, lineno=None, snakefile=None): super().__init__(msg, lineno=lineno, snakefile=snakefile) class WebDAVFileException(RuleException): def __init__(self, msg, lineno=None, snakefile=None): super().__init__(msg, lineno=lineno, snakefile=snakefile) class ClusterJobException(RuleException): def __init__(self, job_info, jobid): super().__init__( "Error executing rule {} on cluster (jobid: {}, external: {}, jobscript: {}). " "For detailed error see the cluster log.".format( job_info.job.rule.name, jobid, job_info.jobid, job_info.jobscript ), lineno=job_info.job.rule.lineno, snakefile=job_info.job.rule.snakefile, ) class CreateRuleException(RuleException): pass class TerminatedException(Exception): pass class CreateCondaEnvironmentException(WorkflowError): pass class SpawnedJobError(Exception): pass class IncompleteCheckpointException(Exception): def __init__(self, rule, targetfile): super().__init__( "The requested checkpoint output is not yet created." "If you see this error, you have likely tried to use " "checkpoint output outside of an input function, or " "you have tried to call an input function directly " "via (). Please check the docs at " "https://snakemake.readthedocs.io/en/stable/" "snakefiles/rules.html#data-dependent-conditional-execution " "and note that the input function in the example rule " "'aggregate' is NOT called, but passed to the rule " "by name, such that Snakemake can call it internally " "once the checkpoint is finished." ) self.rule = rule from snakemake.io import checkpoint_target self.targetfile = checkpoint_target(targetfile) class CacheMissException(Exception): pass snakemake-5.10.0/snakemake/executors.py000066400000000000000000002230401361131222100200570ustar00rootroot00000000000000__author__ = "Johannes Köster" __copyright__ = "Copyright 2015-2019, Johannes Köster" __email__ = "koester@jimmy.harvard.edu" __license__ = "MIT" import os import sys import contextlib import time import datetime import json import textwrap import stat import shutil import shlex import threading import concurrent.futures import subprocess import signal from functools import partial from itertools import chain from collections import namedtuple from tempfile import mkdtemp from snakemake.io import _IOFile import random import base64 import uuid import re import math from snakemake.jobs import Job from snakemake.shell import shell from snakemake.logging import logger from snakemake.stats import Stats from snakemake.utils import format, Unformattable, makedirs from snakemake.io import get_wildcard_names, Wildcards from snakemake.exceptions import print_exception, get_exception_origin from snakemake.exceptions import format_error, RuleException, log_verbose_traceback from snakemake.exceptions import ( ProtectedOutputException, WorkflowError, ImproperShadowException, SpawnedJobError, CacheMissException, ) from snakemake.common import Mode, __version__, get_container_image, get_uuid def sleep(): # do not sleep on CI. In that case we just want to quickly test everything. if os.environ.get("CI") != "true": time.sleep(10) class AbstractExecutor: def __init__( self, workflow, dag, printreason=False, quiet=False, printshellcmds=False, printthreads=True, latency_wait=3, keepincomplete=False, ): self.workflow = workflow self.dag = dag self.quiet = quiet self.printreason = printreason self.printshellcmds = printshellcmds self.printthreads = printthreads self.latency_wait = latency_wait self.keepincomplete = keepincomplete def get_default_remote_provider_args(self): if self.workflow.default_remote_provider: return ( " --default-remote-provider {} " "--default-remote-prefix {} " ).format( self.workflow.default_remote_provider.__module__.split(".")[-1], self.workflow.default_remote_prefix, ) return "" def get_default_resources_args(self): if self.workflow.default_resources.args is not None: args = " --default-resources {} ".format( " ".join(map('"{}"'.format, self.workflow.default_resources.args)) ) return args return "" def run(self, job, callback=None, submit_callback=None, error_callback=None): self._run(job) callback(job) def shutdown(self): pass def cancel(self): pass def _run(self, job): job.check_protected_output() self.printjob(job) def rule_prefix(self, job): return "local " if job.is_local else "" def printjob(self, job): job.log_info(skip_dynamic=True) def print_job_error(self, job, msg=None, **kwargs): job.log_error(msg, **kwargs) def handle_job_success(self, job): pass def handle_job_error(self, job): pass class DryrunExecutor(AbstractExecutor): def printjob(self, job): super().printjob(job) if job.is_group(): for j in job.jobs: self.printcache(j) else: self.printcache(job) def printcache(self, job): if self.workflow.is_cached_rule(job.rule): if self.workflow.output_file_cache.exists(job): logger.info( "Output file {} will be obtained from cache.".format(job.output[0]) ) else: logger.info( "Output file {} will be written to cache.".format(job.output[0]) ) class RealExecutor(AbstractExecutor): def __init__( self, workflow, dag, printreason=False, quiet=False, printshellcmds=False, latency_wait=3, assume_shared_fs=True, keepincomplete=False, ): super().__init__( workflow, dag, printreason=printreason, quiet=quiet, printshellcmds=printshellcmds, latency_wait=latency_wait, keepincomplete=keepincomplete, ) self.assume_shared_fs = assume_shared_fs self.stats = Stats() self.snakefile = workflow.snakefile def register_job(self, job): job.register() def _run(self, job, callback=None, error_callback=None): super()._run(job) self.stats.report_job_start(job) try: self.register_job(job) except IOError as e: logger.info( "Failed to set marker file for job started ({}). " "Snakemake will work, but cannot ensure that output files " "are complete in case of a kill signal or power loss. " "Please ensure write permissions for the " "directory {}".format(e, self.workflow.persistence.path) ) def handle_job_success( self, job, upload_remote=True, handle_log=True, handle_touch=True, ignore_missing_output=False, ): job.postprocess( upload_remote=upload_remote, handle_log=handle_log, handle_touch=handle_touch, ignore_missing_output=ignore_missing_output, latency_wait=self.latency_wait, assume_shared_fs=self.assume_shared_fs, ) self.stats.report_job_end(job) def handle_job_error(self, job, upload_remote=True): job.postprocess( error=True, assume_shared_fs=self.assume_shared_fs, latency_wait=self.latency_wait, ) def format_job_pattern(self, pattern, job=None, **kwargs): overwrite_workdir = [] if self.workflow.overwrite_workdir: overwrite_workdir.extend(("--directory", self.workflow.overwrite_workdir)) overwrite_config = [] if self.workflow.overwrite_configfiles: # add each of the overwriting configfiles in the original order if self.workflow.overwrite_configfiles: overwrite_config.append("--configfiles") overwrite_config.extend(self.workflow.overwrite_configfiles) if self.workflow.config_args: overwrite_config.append("--config") overwrite_config.extend(self.workflow.config_args) printshellcmds = "" if self.workflow.printshellcmds: printshellcmds = "-p" if not job.is_branched and not job.is_updated: # Restrict considered rules. This does not work for updated jobs # because they need to be updated in the spawned process as well. rules = ["--allowed-rules"] rules.extend(job.rules) else: rules = [] target = kwargs.get("target", job.get_targets()) snakefile = kwargs.get("snakefile", self.snakefile) cores = kwargs.get("cores", self.cores) if "target" in kwargs: del kwargs["target"] if "snakefile" in kwargs: del kwargs["snakefile"] if "cores" in kwargs: del kwargs["cores"] return format( pattern, job=job, attempt=job.attempt, overwrite_workdir=overwrite_workdir, overwrite_config=overwrite_config, printshellcmds=printshellcmds, workflow=self.workflow, snakefile=snakefile, cores=cores, benchmark_repeats=job.benchmark_repeats if not job.is_group() else None, target=target, rules=rules, **kwargs ) class TouchExecutor(RealExecutor): def run(self, job, callback=None, submit_callback=None, error_callback=None): super()._run(job) try: # Touching of output files will be done by handle_job_success time.sleep(0.1) callback(job) except OSError as ex: print_exception(ex, self.workflow.linemaps) error_callback(job) def handle_job_success(self, job): super().handle_job_success(job, ignore_missing_output=True) _ProcessPoolExceptions = (KeyboardInterrupt,) try: from concurrent.futures.process import BrokenProcessPool _ProcessPoolExceptions = (KeyboardInterrupt, BrokenProcessPool) except ImportError: pass class CPUExecutor(RealExecutor): def __init__( self, workflow, dag, workers, printreason=False, quiet=False, printshellcmds=False, use_threads=False, latency_wait=3, cores=1, keepincomplete=False, ): super().__init__( workflow, dag, printreason=printreason, quiet=quiet, printshellcmds=printshellcmds, latency_wait=latency_wait, keepincomplete=keepincomplete, ) self.exec_job = "\\\n".join( ( "cd {workflow.workdir_init} && ", "{sys.executable} -m snakemake {target} --snakefile {snakefile} ", "--force -j{cores} --keep-target-files --keep-remote ", "--attempt {attempt} ", "--force-use-threads --wrapper-prefix {workflow.wrapper_prefix} ", "--latency-wait {latency_wait} ", self.get_default_remote_provider_args(), self.get_default_resources_args(), "{overwrite_workdir} {overwrite_config} {printshellcmds} {rules} ", "--notemp --quiet --no-hooks --nolock --mode {} ".format( Mode.subprocess ), ) ) if self.workflow.shadow_prefix: self.exec_job += " --shadow-prefix {} ".format(self.workflow.shadow_prefix) if self.workflow.use_conda: self.exec_job += " --use-conda " if self.workflow.conda_prefix: self.exec_job += " --conda-prefix {} ".format( self.workflow.conda_prefix ) if self.workflow.use_singularity: self.exec_job += " --use-singularity " if self.workflow.singularity_prefix: self.exec_job += " --singularity-prefix {} ".format( self.workflow.singularity_prefix ) if self.workflow.singularity_args: self.exec_job += ' --singularity-args "{}"'.format( self.workflow.singularity_args ) self.use_threads = use_threads self.cores = cores self.pool = concurrent.futures.ThreadPoolExecutor(max_workers=workers + 1) def run(self, job, callback=None, submit_callback=None, error_callback=None): super()._run(job) if job.is_group(): # the future waits for the entire group job future = self.pool.submit(self.run_group_job, job) else: future = self.run_single_job(job) future.add_done_callback(partial(self._callback, job, callback, error_callback)) def job_args_and_prepare(self, job): job.prepare() conda_env = job.conda_env_path singularity_img = job.singularity_img_path env_modules = job.env_modules benchmark = None benchmark_repeats = job.benchmark_repeats or 1 if job.benchmark is not None: benchmark = str(job.benchmark) return ( job.rule, job.input._plainstrings(), job.output._plainstrings(), job.params, job.wildcards, job.threads, job.resources, job.log._plainstrings(), benchmark, benchmark_repeats, conda_env, singularity_img, self.workflow.singularity_args, env_modules, self.workflow.use_singularity, self.workflow.linemaps, self.workflow.debug, self.workflow.cleanup_scripts, job.shadow_dir, job.jobid, ) def run_single_job(self, job): if self.use_threads or (not job.is_shadow and not job.is_run): future = self.pool.submit( self.cached_or_run, job, run_wrapper, *self.job_args_and_prepare(job) ) else: # run directive jobs are spawned into subprocesses future = self.pool.submit(self.cached_or_run, job, self.spawn_job, job) return future def run_group_job(self, job): """Run a pipe group job. This lets all items run simultaneously.""" # we only have to consider pipe groups because in local running mode, # these are the only groups that will occur futures = [self.run_single_job(j) for j in job] while True: k = 0 for f in futures: if f.done(): ex = f.exception() if ex is not None: # kill all shell commands of the other group jobs # there can be only shell commands because the # run directive is not allowed for pipe jobs for j in job: shell.kill(j.jobid) raise ex else: k += 1 if k == len(futures): return time.sleep(1) def spawn_job(self, job): exec_job = self.exec_job cmd = self.format_job_pattern( exec_job, job=job, _quote_all=True, latency_wait=self.latency_wait ) try: subprocess.check_call(cmd, shell=True) except subprocess.CalledProcessError as e: raise SpawnedJobError() def cached_or_run(self, job, run_func, *args): """ Either retrieve result from cache, or run job with given function. """ to_cache = self.workflow.is_cached_rule(job.rule) try: if to_cache: self.workflow.output_file_cache.fetch(job) return except CacheMissException: pass run_func(*args) if to_cache: self.workflow.output_file_cache.store(job) def shutdown(self): self.pool.shutdown() def cancel(self): self.pool.shutdown() def _callback(self, job, callback, error_callback, future): try: ex = future.exception() if ex is not None: raise ex callback(job) except _ProcessPoolExceptions: self.handle_job_error(job) # no error callback, just silently ignore the interrupt as the main scheduler is also killed except SpawnedJobError: # don't print error message, this is done by the spawned subprocess error_callback(job) except (Exception, BaseException) as ex: self.print_job_error(job) if not (job.is_group() or job.shellcmd) or self.workflow.verbose: print_exception(ex, self.workflow.linemaps) error_callback(job) def handle_job_success(self, job): super().handle_job_success(job) def handle_job_error(self, job): super().handle_job_error(job) if not self.keepincomplete: job.cleanup() self.workflow.persistence.cleanup(job) class ClusterExecutor(RealExecutor): default_jobscript = "jobscript.sh" def __init__( self, workflow, dag, cores, jobname="snakejob.{name}.{jobid}.sh", printreason=False, quiet=False, printshellcmds=False, latency_wait=3, cluster_config=None, local_input=None, restart_times=None, exec_job=None, assume_shared_fs=True, max_status_checks_per_second=1, disable_default_remote_provider_args=False, keepincomplete=False, ): from ratelimiter import RateLimiter local_input = local_input or [] super().__init__( workflow, dag, printreason=printreason, quiet=quiet, printshellcmds=printshellcmds, latency_wait=latency_wait, assume_shared_fs=assume_shared_fs, ) if not self.assume_shared_fs: # use relative path to Snakefile self.snakefile = os.path.relpath(workflow.snakefile) jobscript = workflow.jobscript if jobscript is None: jobscript = os.path.join(os.path.dirname(__file__), self.default_jobscript) try: with open(jobscript) as f: self.jobscript = f.read() except IOError as e: raise WorkflowError(e) if not "jobid" in get_wildcard_names(jobname): raise WorkflowError( 'Defined jobname ("{}") has to contain the wildcard {jobid}.' ) if exec_job is None: self.exec_job = "\\\n".join( ( "cd {workflow.workdir_init} && " if assume_shared_fs else "", "{sys.executable} " if assume_shared_fs else "python ", "-m snakemake {target} --snakefile {snakefile} ", "--force -j{cores} --keep-target-files --keep-remote ", "--wait-for-files {wait_for_files} --latency-wait {latency_wait} ", " --attempt {attempt} {use_threads} ", "--wrapper-prefix {workflow.wrapper_prefix} ", "{overwrite_workdir} {overwrite_config} {printshellcmds} {rules} " "--nocolor --notemp --no-hooks --nolock ", "--mode {} ".format(Mode.cluster), ) ) else: self.exec_job = exec_job if self.workflow.shadow_prefix: self.exec_job += " --shadow-prefix {} ".format(self.workflow.shadow_prefix) if self.workflow.use_conda: self.exec_job += " --use-conda " if self.workflow.conda_prefix: self.exec_job += " --conda-prefix {} ".format( self.workflow.conda_prefix ) if self.workflow.use_singularity: self.exec_job += " --use-singularity " if self.workflow.singularity_prefix: self.exec_job += " --singularity-prefix {} ".format( self.workflow.singularity_prefix ) if self.workflow.singularity_args: self.exec_job += ' --singularity-args "{}"'.format( self.workflow.singularity_args ) if not disable_default_remote_provider_args: self.exec_job += self.get_default_remote_provider_args() self.exec_job += self.get_default_resources_args() self.jobname = jobname self._tmpdir = None self.cores = cores if cores else "" self.cluster_config = cluster_config if cluster_config else dict() self.restart_times = restart_times self.active_jobs = list() self.lock = threading.Lock() self.wait = True self.wait_thread = threading.Thread(target=self._wait_for_jobs) self.wait_thread.daemon = True self.wait_thread.start() self.max_status_checks_per_second = max_status_checks_per_second self.status_rate_limiter = RateLimiter( max_calls=self.max_status_checks_per_second, period=1 ) def shutdown(self): with self.lock: self.wait = False self.wait_thread.join() if not self.workflow.immediate_submit: # Only delete tmpdir (containing jobscripts) if not using # immediate_submit. With immediate_submit, jobs can be scheduled # after this method is completed. Hence we have to keep the # directory. shutil.rmtree(self.tmpdir) def cancel(self): self.shutdown() def _run(self, job, callback=None, error_callback=None): if self.assume_shared_fs: job.remove_existing_output() job.download_remote_input() super()._run(job, callback=callback, error_callback=error_callback) @property def tmpdir(self): if self._tmpdir is None: self._tmpdir = mkdtemp(dir=".snakemake", prefix="tmp.") return os.path.abspath(self._tmpdir) def get_jobscript(self, job): f = job.format_wildcards(self.jobname, cluster=self.cluster_wildcards(job)) if os.path.sep in f: raise WorkflowError( "Path separator ({}) found in job name {}. " "This is not supported.".format(os.path.sep, f) ) return os.path.join(self.tmpdir, f) def format_job(self, pattern, job, **kwargs): wait_for_files = [] if self.assume_shared_fs: wait_for_files.append(self.tmpdir) wait_for_files.extend(job.get_wait_for_files()) format_p = partial( self.format_job_pattern, job=job, properties=job.properties(cluster=self.cluster_params(job)), latency_wait=self.latency_wait, wait_for_files=wait_for_files, **kwargs ) try: return format_p(pattern) except KeyError as e: raise WorkflowError( "Error formatting jobscript: {} not found\n" "Make sure that your custom jobscript is up to date.".format(e) ) def write_jobscript(self, job, jobscript, **kwargs): # only force threads if this is not a group job # otherwise we want proper process handling use_threads = "--force-use-threads" if not job.is_group() else "" exec_job = self.format_job( self.exec_job, job, _quote_all=True, use_threads=use_threads, **kwargs ) content = self.format_job(self.jobscript, job, exec_job=exec_job, **kwargs) logger.debug("Jobscript:\n{}".format(content)) with open(jobscript, "w") as f: print(content, file=f) os.chmod(jobscript, os.stat(jobscript).st_mode | stat.S_IXUSR) def cluster_params(self, job): """Return wildcards object for job from cluster_config.""" cluster = self.cluster_config.get("__default__", dict()).copy() cluster.update(self.cluster_config.get(job.name, dict())) # Format values with available parameters from the job. for key, value in list(cluster.items()): if isinstance(value, str): try: cluster[key] = job.format_wildcards(value) except NameError as e: if job.is_group(): msg = ( "Failed to format cluster config for group job. " "You have to ensure that your default entry " "does not contain any items that group jobs " "cannot provide, like {rule}, {wildcards}." ) else: msg = ( "Failed to format cluster config " "entry for job {}.".format(job.rule.name) ) raise WorkflowError(msg, e) return cluster def cluster_wildcards(self, job): return Wildcards(fromdict=self.cluster_params(job)) def handle_job_success(self, job): super().handle_job_success( job, upload_remote=False, handle_log=False, handle_touch=False ) def handle_job_error(self, job): # TODO what about removing empty remote dirs?? This cannot be decided # on the cluster node. super().handle_job_error(job, upload_remote=False) logger.debug("Cleanup job metadata.") # We have to remove metadata here as well. # It will be removed by the CPUExecutor in case of a shared FS, # but we might not see the removal due to filesystem latency. # By removing it again, we make sure that it is gone on the host FS. if not self.keepincomplete: self.workflow.persistence.cleanup(job) def print_cluster_job_error(self, job_info, jobid): job = job_info.job kind = ( "rule {}".format(job.rule.name) if not job.is_group() else "group job {}".format(job.groupid) ) logger.error( "Error executing {} on cluster (jobid: {}, external: " "{}, jobscript: {}). For error details see the cluster " "log and the log files of the involved rule(s).".format( kind, jobid, job_info.jobid, job_info.jobscript ) ) GenericClusterJob = namedtuple( "GenericClusterJob", "job jobid callback error_callback jobscript jobfinished jobfailed", ) class GenericClusterExecutor(ClusterExecutor): def __init__( self, workflow, dag, cores, submitcmd="qsub", statuscmd=None, cluster_config=None, jobname="snakejob.{rulename}.{jobid}.sh", printreason=False, quiet=False, printshellcmds=False, latency_wait=3, restart_times=0, assume_shared_fs=True, max_status_checks_per_second=1, keepincomplete=False, ): self.submitcmd = submitcmd if not assume_shared_fs and statuscmd is None: raise WorkflowError( "When no shared filesystem can be assumed, a " "status command must be given." ) self.statuscmd = statuscmd self.external_jobid = dict() super().__init__( workflow, dag, cores, jobname=jobname, printreason=printreason, quiet=quiet, printshellcmds=printshellcmds, latency_wait=latency_wait, cluster_config=cluster_config, restart_times=restart_times, assume_shared_fs=assume_shared_fs, max_status_checks_per_second=max_status_checks_per_second, ) if statuscmd: self.exec_job += " && exit 0 || exit 1" elif assume_shared_fs: # TODO wrap with watch and touch {jobrunning} # check modification date of {jobrunning} in the wait_for_job method self.exec_job += ( ' && touch "{jobfinished}" || (touch "{jobfailed}"; exit 1)' ) else: raise WorkflowError( "If no shared filesystem is used, you have to " "specify a cluster status command." ) def cancel(self): logger.info("Will exit after finishing currently running jobs.") self.shutdown() def register_job(self, job): # Do not register job here. # Instead do it manually once the jobid is known. pass def run(self, job, callback=None, submit_callback=None, error_callback=None): super()._run(job) workdir = os.getcwd() jobid = job.jobid jobscript = self.get_jobscript(job) jobfinished = os.path.join(self.tmpdir, "{}.jobfinished".format(jobid)) jobfailed = os.path.join(self.tmpdir, "{}.jobfailed".format(jobid)) self.write_jobscript( job, jobscript, jobfinished=jobfinished, jobfailed=jobfailed ) if self.statuscmd: ext_jobid = self.dag.incomplete_external_jobid(job) if ext_jobid: # Job is incomplete and still running. # We simply register it and wait for completion or failure. logger.info( "Resuming incomplete job {} with external jobid '{}'.".format( jobid, ext_jobid ) ) submit_callback(job) with self.lock: self.active_jobs.append( GenericClusterJob( job, ext_jobid, callback, error_callback, jobscript, jobfinished, jobfailed, ) ) return deps = " ".join( self.external_jobid[f] for f in job.input if f in self.external_jobid ) try: submitcmd = job.format_wildcards( self.submitcmd, dependencies=deps, cluster=self.cluster_wildcards(job) ) except AttributeError as e: raise WorkflowError(str(e), rule=job.rule if not job.is_group() else None) try: ext_jobid = ( subprocess.check_output( '{submitcmd} "{jobscript}"'.format( submitcmd=submitcmd, jobscript=jobscript ), shell=True, ) .decode() .split("\n") ) except subprocess.CalledProcessError as ex: logger.error( "Error submitting jobscript (exit code {}):\n{}".format( ex.returncode, ex.output.decode() ) ) error_callback(job) return if ext_jobid and ext_jobid[0]: ext_jobid = ext_jobid[0] self.external_jobid.update((f, ext_jobid) for f in job.output) logger.info( "Submitted {} {} with external jobid '{}'.".format( "group job" if job.is_group() else "job", jobid, ext_jobid ) ) self.workflow.persistence.started(job, external_jobid=ext_jobid) submit_callback(job) with self.lock: self.active_jobs.append( GenericClusterJob( job, ext_jobid, callback, error_callback, jobscript, jobfinished, jobfailed, ) ) def _wait_for_jobs(self): success = "success" failed = "failed" running = "running" if self.statuscmd is not None: def job_status(job): try: # this command shall return "success", "failed" or "running" return ( subprocess.check_output( "{statuscmd} {jobid}".format( jobid=job.jobid, statuscmd=self.statuscmd ), shell=True, ) .decode() .split("\n")[0] ) except subprocess.CalledProcessError as e: if e.returncode < 0: # Ignore SIGINT and all other issues due to signals # because it will be caused by hitting e.g. # Ctrl-C on the main process or sending killall to # snakemake. # Snakemake will handle the signal in # the master process. pass else: raise WorkflowError( "Failed to obtain job status. " "See above for error message." ) else: def job_status(job): if os.path.exists(active_job.jobfinished): os.remove(active_job.jobfinished) os.remove(active_job.jobscript) return success if os.path.exists(active_job.jobfailed): os.remove(active_job.jobfailed) os.remove(active_job.jobscript) return failed return running while True: with self.lock: if not self.wait: return active_jobs = self.active_jobs self.active_jobs = list() still_running = list() logger.debug("Checking status of {} jobs.".format(len(active_jobs))) for active_job in active_jobs: with self.status_rate_limiter: status = job_status(active_job) if status == success: active_job.callback(active_job.job) elif status == failed: self.print_job_error( active_job.job, cluster_jobid=active_job.jobid if active_job.jobid else "unknown", ) self.print_cluster_job_error( active_job, self.dag.jobid(active_job.job) ) active_job.error_callback(active_job.job) else: still_running.append(active_job) with self.lock: self.active_jobs.extend(still_running) sleep() SynchronousClusterJob = namedtuple( "SynchronousClusterJob", "job jobid callback error_callback jobscript process" ) class SynchronousClusterExecutor(ClusterExecutor): """ invocations like "qsub -sync y" (SGE) or "bsub -K" (LSF) are synchronous, blocking the foreground thread and returning the remote exit code at remote exit. """ def __init__( self, workflow, dag, cores, submitcmd="qsub", cluster_config=None, jobname="snakejob.{rulename}.{jobid}.sh", printreason=False, quiet=False, printshellcmds=False, latency_wait=3, restart_times=0, assume_shared_fs=True, keepincomplete=False, ): super().__init__( workflow, dag, cores, jobname=jobname, printreason=printreason, quiet=quiet, printshellcmds=printshellcmds, latency_wait=latency_wait, cluster_config=cluster_config, restart_times=restart_times, assume_shared_fs=assume_shared_fs, max_status_checks_per_second=10, ) self.submitcmd = submitcmd self.external_jobid = dict() def cancel(self): logger.info("Will exit after finishing currently running jobs.") self.shutdown() def run(self, job, callback=None, submit_callback=None, error_callback=None): super()._run(job) workdir = os.getcwd() jobid = job.jobid jobscript = self.get_jobscript(job) self.write_jobscript(job, jobscript) deps = " ".join( self.external_jobid[f] for f in job.input if f in self.external_jobid ) try: submitcmd = job.format_wildcards( self.submitcmd, dependencies=deps, cluster=self.cluster_wildcards(job) ) except AttributeError as e: raise WorkflowError(str(e), rule=job.rule if not job.is_group() else None) process = subprocess.Popen( '{submitcmd} "{jobscript}"'.format( submitcmd=submitcmd, jobscript=jobscript ), shell=True, ) submit_callback(job) with self.lock: self.active_jobs.append( SynchronousClusterJob( job, process.pid, callback, error_callback, jobscript, process ) ) def _wait_for_jobs(self): while True: with self.lock: if not self.wait: return active_jobs = self.active_jobs self.active_jobs = list() still_running = list() for active_job in active_jobs: with self.status_rate_limiter: exitcode = active_job.process.poll() if exitcode is None: # job not yet finished still_running.append(active_job) elif exitcode == 0: # job finished successfully os.remove(active_job.jobscript) active_job.callback(active_job.job) else: # job failed os.remove(active_job.jobscript) self.print_job_error(active_job.job) self.print_cluster_job_error( active_job, self.dag.jobid(active_job.job) ) active_job.error_callback(active_job.job) with self.lock: self.active_jobs.extend(still_running) sleep() DRMAAClusterJob = namedtuple( "DRMAAClusterJob", "job jobid callback error_callback jobscript" ) class DRMAAExecutor(ClusterExecutor): def __init__( self, workflow, dag, cores, jobname="snakejob.{rulename}.{jobid}.sh", printreason=False, quiet=False, printshellcmds=False, drmaa_args="", drmaa_log_dir=None, latency_wait=3, cluster_config=None, restart_times=0, assume_shared_fs=True, max_status_checks_per_second=1, keepincomplete=False, ): super().__init__( workflow, dag, cores, jobname=jobname, printreason=printreason, quiet=quiet, printshellcmds=printshellcmds, latency_wait=latency_wait, cluster_config=cluster_config, restart_times=restart_times, assume_shared_fs=assume_shared_fs, max_status_checks_per_second=max_status_checks_per_second, ) try: import drmaa except ImportError: raise WorkflowError( "Python support for DRMAA is not installed. " "Please install it, e.g. with easy_install3 --user drmaa" ) except RuntimeError as e: raise WorkflowError("Error loading drmaa support:\n{}".format(e)) self.session = drmaa.Session() self.drmaa_args = drmaa_args self.drmaa_log_dir = drmaa_log_dir self.session.initialize() self.submitted = list() def cancel(self): from drmaa.const import JobControlAction from drmaa.errors import InvalidJobException, InternalException for jobid in self.submitted: try: self.session.control(jobid, JobControlAction.TERMINATE) except (InvalidJobException, InternalException): # This is common - logging a warning would probably confuse the user. pass self.shutdown() def run(self, job, callback=None, submit_callback=None, error_callback=None): super()._run(job) jobscript = self.get_jobscript(job) self.write_jobscript(job, jobscript) try: drmaa_args = job.format_wildcards( self.drmaa_args, cluster=self.cluster_wildcards(job) ) except AttributeError as e: raise WorkflowError(str(e), rule=job.rule) import drmaa if self.drmaa_log_dir: makedirs(self.drmaa_log_dir) try: jt = self.session.createJobTemplate() jt.remoteCommand = jobscript jt.nativeSpecification = drmaa_args if self.drmaa_log_dir: jt.outputPath = ":" + self.drmaa_log_dir jt.errorPath = ":" + self.drmaa_log_dir jt.jobName = os.path.basename(jobscript) jobid = self.session.runJob(jt) except ( drmaa.DeniedByDrmException, drmaa.InternalException, drmaa.InvalidAttributeValueException, ) as e: print_exception( WorkflowError("DRMAA Error: {}".format(e)), self.workflow.linemaps ) error_callback(job) return logger.info( "Submitted DRMAA job {} with external jobid {}.".format(job.jobid, jobid) ) self.submitted.append(jobid) self.session.deleteJobTemplate(jt) submit_callback(job) with self.lock: self.active_jobs.append( DRMAAClusterJob(job, jobid, callback, error_callback, jobscript) ) def shutdown(self): super().shutdown() self.session.exit() def _wait_for_jobs(self): import drmaa while True: with self.lock: if not self.wait: return active_jobs = self.active_jobs self.active_jobs = list() still_running = list() for active_job in active_jobs: with self.status_rate_limiter: try: retval = self.session.wait( active_job.jobid, drmaa.Session.TIMEOUT_NO_WAIT ) except drmaa.ExitTimeoutException as e: # job still active still_running.append(active_job) continue except (drmaa.InternalException, Exception) as e: print_exception( WorkflowError("DRMAA Error: {}".format(e)), self.workflow.linemaps, ) os.remove(active_job.jobscript) active_job.error_callback(active_job.job) continue # job exited os.remove(active_job.jobscript) if ( not retval.wasAborted and retval.hasExited and retval.exitStatus == 0 ): active_job.callback(active_job.job) else: self.print_job_error(active_job.job) self.print_cluster_job_error( active_job, self.dag.jobid(active_job.job) ) active_job.error_callback(active_job.job) with self.lock: self.active_jobs.extend(still_running) sleep() @contextlib.contextmanager def change_working_directory(directory=None): """ Change working directory in execution context if provided. """ if directory: try: saved_directory = os.getcwd() logger.info("Changing to shadow directory: {}".format(directory)) os.chdir(directory) yield finally: os.chdir(saved_directory) else: yield KubernetesJob = namedtuple( "KubernetesJob", "job jobid callback error_callback kubejob jobscript" ) class KubernetesExecutor(ClusterExecutor): def __init__( self, workflow, dag, namespace, envvars, container_image=None, jobname="{rulename}.{jobid}", printreason=False, quiet=False, printshellcmds=False, latency_wait=3, cluster_config=None, local_input=None, restart_times=None, keepincomplete=False, ): exec_job = ( "cp -rf /source/. . && " "snakemake {target} --snakefile {snakefile} " "--force -j{cores} --keep-target-files --keep-remote " "--latency-wait 0 " " --attempt {attempt} {use_threads} " "--wrapper-prefix {workflow.wrapper_prefix} " "{overwrite_config} {printshellcmds} {rules} --nocolor " "--notemp --no-hooks --nolock " ) super().__init__( workflow, dag, None, jobname=jobname, printreason=printreason, quiet=quiet, printshellcmds=printshellcmds, latency_wait=latency_wait, cluster_config=cluster_config, local_input=local_input, restart_times=restart_times, exec_job=exec_job, assume_shared_fs=False, max_status_checks_per_second=10, ) # use relative path to Snakefile self.snakefile = os.path.relpath(workflow.snakefile) try: from kubernetes import config except ImportError: raise WorkflowError( "The Python 3 package 'kubernetes' " "must be installed to use Kubernetes" ) config.load_kube_config() import kubernetes.client self.kubeapi = kubernetes.client.CoreV1Api() self.batchapi = kubernetes.client.BatchV1Api() self.namespace = namespace self.envvars = envvars or [] self.secret_files = {} self.run_namespace = str(uuid.uuid4()) self.secret_envvars = {} self.register_secret() self.container_image = container_image or get_container_image() def register_secret(self): import kubernetes.client secret = kubernetes.client.V1Secret() secret.metadata = kubernetes.client.V1ObjectMeta() # create a random uuid secret.metadata.name = self.run_namespace secret.type = "Opaque" secret.data = {} for i, f in enumerate(self.workflow.get_sources()): if f.startswith(".."): logger.warning( "Ignoring source file {}. Only files relative " "to the working directory are allowed.".format(f) ) continue with open(f, "br") as content: key = "f{}".format(i) self.secret_files[key] = f secret.data[key] = base64.b64encode(content.read()).decode() for e in self.envvars: try: key = e.lower() secret.data[key] = base64.b64encode(os.environ[e].encode()).decode() self.secret_envvars[key] = e except KeyError: continue self.kubeapi.create_namespaced_secret(self.namespace, secret) def unregister_secret(self): import kubernetes.client self.kubeapi.delete_namespaced_secret( self.run_namespace, self.namespace, body=kubernetes.client.V1DeleteOptions() ) def shutdown(self): self.unregister_secret() super().shutdown() def cancel(self): import kubernetes.client body = kubernetes.client.V1DeleteOptions() with self.lock: for j in self.active_jobs: self.kubeapi.delete_namespaced_pod(j.jobid, self.namespace, body=body) self.shutdown() def run(self, job, callback=None, submit_callback=None, error_callback=None): import kubernetes.client super()._run(job) exec_job = self.format_job( self.exec_job, job, _quote_all=True, use_threads="--force-use-threads" if not job.is_group() else "", ) # Kubernetes silently does not submit a job if the name is too long # therefore, we ensure that it is not longer than snakejob+uuid. jobid = "snakejob-{}".format( get_uuid("{}-{}-{}".format(self.run_namespace, job.jobid, job.attempt)) ) body = kubernetes.client.V1Pod() body.metadata = kubernetes.client.V1ObjectMeta(labels={"app": "snakemake"}) body.metadata.name = jobid # container container = kubernetes.client.V1Container(name=jobid) container.image = self.container_image container.command = shlex.split("/bin/sh") container.args = ["-c", exec_job] container.working_dir = "/workdir" container.volume_mounts = [ kubernetes.client.V1VolumeMount(name="workdir", mount_path="/workdir") ] container.volume_mounts = [ kubernetes.client.V1VolumeMount(name="source", mount_path="/source") ] body.spec = kubernetes.client.V1PodSpec(containers=[container]) # fail on first error body.spec.restart_policy = "Never" # source files as a secret volume # we copy these files to the workdir before executing Snakemake too_large = [ path for path in self.secret_files.values() if os.path.getsize(path) > 1000000 ] if too_large: raise WorkflowError( "The following source files exceed the maximum " "file size (1MB) that can be passed from host to " "kubernetes. These are likely not source code " "files. Consider adding them to your " "remote storage instead or (if software) use " "Conda packages or container images:\n{}".format("\n".join(too_large)) ) secret_volume = kubernetes.client.V1Volume(name="source") secret_volume.secret = kubernetes.client.V1SecretVolumeSource() secret_volume.secret.secret_name = self.run_namespace secret_volume.secret.items = [ kubernetes.client.V1KeyToPath(key=key, path=path) for key, path in self.secret_files.items() ] # workdir as an emptyDir volume of undefined size workdir_volume = kubernetes.client.V1Volume(name="workdir") workdir_volume.empty_dir = kubernetes.client.V1EmptyDirVolumeSource() body.spec.volumes = [secret_volume, workdir_volume] # env vars container.env = [] for key, e in self.secret_envvars.items(): envvar = kubernetes.client.V1EnvVar(name=e) envvar.value_from = kubernetes.client.V1EnvVarSource() envvar.value_from.secret_key_ref = kubernetes.client.V1SecretKeySelector( key=key, name=self.run_namespace ) container.env.append(envvar) # request resources container.resources = kubernetes.client.V1ResourceRequirements() container.resources.requests = {} container.resources.requests["cpu"] = job.resources["_cores"] if "mem_mb" in job.resources.keys(): container.resources.requests["memory"] = "{}M".format( job.resources["mem_mb"] ) # capabilities if job.needs_singularity and self.workflow.use_singularity: # TODO this should work, but it doesn't currently because of # missing loop devices # singularity inside docker requires SYS_ADMIN capabilities # see https://groups.google.com/a/lbl.gov/forum/#!topic/singularity/e9mlDuzKowc # container.capabilities = kubernetes.client.V1Capabilities() # container.capabilities.add = ["SYS_ADMIN", # "DAC_OVERRIDE", # "SETUID", # "SETGID", # "SYS_CHROOT"] # Running in priviledged mode always works container.security_context = kubernetes.client.V1SecurityContext( privileged=True ) pod = self._kubernetes_retry( lambda: self.kubeapi.create_namespaced_pod(self.namespace, body) ) logger.info( "Get status with:\n" "kubectl describe pod {jobid}\n" "kubectl logs {jobid}".format(jobid=jobid) ) self.active_jobs.append( KubernetesJob(job, jobid, callback, error_callback, pod, None) ) def _kubernetes_retry(self, func): import kubernetes with self.lock: try: return func() except kubernetes.client.rest.ApiException as e: if e.status == 401: # Unauthorized. # Reload config in order to ensure token is # refreshed. Then try again. logger.info("trying to reauthenticate") kubernetes.config.load_kube_config() subprocess.run(["kubectl", "get", "nodes"]) self.kubeapi = kubernetes.client.CoreV1Api() self.batchapi = kubernetes.client.BatchV1Api() self.register_secret() try: return func() except kubernetes.client.rest.ApiException as e: # Both attempts failed, raise error. raise WorkflowError( e, "This is likely a bug in " "https://github.com/kubernetes-client/python.", ) # Handling timeout that may occur in case of GKE master upgrade except urllib3.exceptions.MaxRetryError as e: logger.info( "Request time out! " "check your connection to Kubernetes master" "Workflow will pause for 5 minutes to allow any update operations to complete" ) time.sleep(300) try: return func() except: # Still can't reach the server after 5 minutes raise WorkflowErroe( e, "Error 111 connection timeout, please check" " that the k8 cluster master is reachable!", ) def _wait_for_jobs(self): import kubernetes while True: with self.lock: if not self.wait: return active_jobs = self.active_jobs self.active_jobs = list() still_running = list() for j in active_jobs: with self.status_rate_limiter: logger.debug("Checking status for pod {}".format(j.jobid)) job_not_found = False try: res = self._kubernetes_retry( lambda: self.kubeapi.read_namespaced_pod_status( j.jobid, self.namespace ) ) except kubernetes.client.rest.ApiException as e: if e.status == 404: # Jobid not found # The job is likely already done and was deleted on # the server. j.callback(j.job) continue except WorkflowError as e: print_exception(e, self.workflow.linemaps) j.error_callback(j.job) continue if res is None: msg = ( "Unknown pod {jobid}. " "Has the pod been deleted " "manually?" ).format(jobid=j.jobid) self.print_job_error(j.job, msg=msg, jobid=j.jobid) j.error_callback(j.job) elif res.status.phase == "Failed": msg = ( "For details, please issue:\n" "kubectl describe pod {jobid}\n" "kubectl logs {jobid}" ).format(jobid=j.jobid) # failed self.print_job_error(j.job, msg=msg, jobid=j.jobid) j.error_callback(j.job) elif res.status.phase == "Succeeded": # finished j.callback(j.job) else: # still active still_running.append(j) with self.lock: self.active_jobs.extend(still_running) sleep() TibannaJob = namedtuple( "TibannaJob", "job jobname jobid exec_arn callback error_callback" ) class TibannaExecutor(ClusterExecutor): def __init__( self, workflow, dag, cores, tibanna_sfn, precommand="", container_image=None, printreason=False, quiet=False, printshellcmds=False, latency_wait=3, local_input=None, restart_times=None, exec_job=None, max_status_checks_per_second=1, keepincomplete=False, ): self.workflow_sources = [] for wfs in workflow.get_sources(): if os.path.isdir(wfs): for (dirpath, dirnames, filenames) in os.walk(wfs): self.workflow_sources.extend( [os.path.join(dirpath, f) for f in filenames] ) else: self.workflow_sources.append(os.path.abspath(wfs)) log = "sources=" for f in self.workflow_sources: log += f logger.debug(log) self.snakefile = workflow.snakefile self.tibanna_sfn = tibanna_sfn if precommand: self.precommand = precommand else: self.precommand = "" self.s3_bucket = workflow.default_remote_prefix.split("/")[0] self.s3_subdir = re.sub( "^{}/".format(self.s3_bucket), "", workflow.default_remote_prefix ) logger.debug("precommand= " + self.precommand) logger.debug("bucket=" + self.s3_bucket) logger.debug("subdir=" + self.s3_subdir) self.quiet = quiet exec_job = ( "snakemake {target} --snakefile {snakefile} " "--force -j{cores} --keep-target-files --keep-remote " "--latency-wait 0 " "--attempt 1 {use_threads} " "{overwrite_config} {rules} --nocolor " "--notemp --no-hooks --nolock " ) super().__init__( workflow, dag, cores, printreason=printreason, quiet=quiet, printshellcmds=printshellcmds, latency_wait=latency_wait, local_input=local_input, restart_times=restart_times, exec_job=exec_job, assume_shared_fs=False, max_status_checks_per_second=max_status_checks_per_second, disable_default_remote_provider_args=True, ) self.container_image = container_image or get_container_image() def shutdown(self): # perform additional steps on shutdown if necessary logger.debug("shutting down Tibanna executor") super().shutdown() def cancel(self): from tibanna.core import API for j in self.active_jobs: logger.info("killing job {}".format(j.jobname)) while True: try: res = API().kill(j.exec_arn) if not self.quiet: print(res) break except KeyboardInterrupt: pass self.shutdown() def split_filename(self, filename, checkdir=None): f = os.path.abspath(filename) if checkdir: checkdir = checkdir.rstrip("/") if f.startswith(checkdir): fname = re.sub("^{}/".format(checkdir), "", f) fdir = checkdir else: direrrmsg = ( "All source files including Snakefile, " + "conda env files, and rule script files " + "must be in the same working directory: {} vs {}" ) raise WorkflowError(direrrmsg.format(checkdir, f)) else: fdir, fname = os.path.split(f) return fname, fdir def remove_prefix(self, s): return re.sub("^{}/{}/".format(self.s3_bucket, self.s3_subdir), "", s) def handle_remote(self, target): if isinstance(target, _IOFile) and target.remote_object.provider.is_default: return self.remove_prefix(target) else: return target def add_command(self, job, tibanna_args, tibanna_config): # snakefile, with file name remapped snakefile_fname = tibanna_args.snakemake_main_filename # targets, with file name remapped targets = job.get_targets() if not isinstance(targets, list): targets = [targets] targets_default = " ".join([self.handle_remote(t) for t in targets]) # use_threads use_threads = "--force-use-threads" if not job.is_group() else "" # format command command = self.format_job_pattern( self.exec_job, job, target=targets_default, snakefile=snakefile_fname, use_threads=use_threads, cores=tibanna_config["cpu"], ) if self.precommand: command = self.precommand + "; " + command logger.debug("command = " + str(command)) tibanna_args.command = command def add_workflow_files(self, job, tibanna_args): snakefile_fname, snakemake_dir = self.split_filename(self.snakefile) snakemake_child_fnames = [] for src in self.workflow_sources: src_fname, _ = self.split_filename(src, snakemake_dir) if src_fname != snakefile_fname: # redundant snakemake_child_fnames.append(src_fname) # change path for config files self.workflow.overwrite_configfiles = [ self.split_filename(cf, snakemake_dir)[0] for cf in self.workflow.overwrite_configfiles ] tibanna_args.snakemake_directory_local = snakemake_dir tibanna_args.snakemake_main_filename = snakefile_fname tibanna_args.snakemake_child_filenames = list(set(snakemake_child_fnames)) def adjust_filepath(self, f): if not hasattr(f, "remote_object"): rel = self.remove_prefix(f) # log/benchmark elif ( hasattr(f.remote_object, "provider") and f.remote_object.provider.is_default ): rel = self.remove_prefix(f) else: rel = f return rel def make_tibanna_input(self, job): from tibanna import ec2_utils, core as tibanna_core # input & output # Local snakemake command here must be run with --default-remote-prefix # and --default-remote-provider (forced) but on VM these options will be removed. # The snakemake on the VM will consider these input and output as not remote. # They files are transferred to the container by Tibanna before running snakemake. # In short, the paths on VM must be consistent with what's in Snakefile. # but the actual location of the files is on the S3 bucket/prefix. # This mapping info must be passed to Tibanna. for i in job.input: logger.debug("job input " + str(i)) logger.debug("job input is remote= " + ("true" if i.is_remote else "false")) if hasattr(i.remote_object, "provider"): logger.debug( " is remote default= " + ("true" if i.remote_object.provider.is_default else "false") ) for o in job.expanded_output: logger.debug("job output " + str(o)) logger.debug( "job output is remote= " + ("true" if o.is_remote else "false") ) if hasattr(o.remote_object, "provider"): logger.debug( " is remote default= " + ("true" if o.remote_object.provider.is_default else "false") ) file_prefix = ( "file:///data1/snakemake" # working dir inside snakemake container on VM ) input_source = dict() for ip in job.input: ip_rel = self.adjust_filepath(ip) input_source[os.path.join(file_prefix, ip_rel)] = "s3://" + ip output_target = dict() output_all = [eo for eo in job.expanded_output] if job.log: output_all.append(str(job.log)) if hasattr(job, "benchmark") and job.benchmark: output_all.append(str(job.benchmark)) for op in output_all: op_rel = self.adjust_filepath(op) output_target[os.path.join(file_prefix, op_rel)] = "s3://" + op # mem & cpu mem = job.resources["mem_mb"] / 1024 if "mem_mb" in job.resources else 1 cpu = job.threads # jobid, grouping, run_name jobid = tibanna_core.create_jobid() if job.is_group(): run_name = "snakemake-job-%s-group-%s" % (str(jobid), str(job.groupid)) else: run_name = "snakemake-job-%s-rule-%s" % (str(jobid), str(job.rule)) # tibanna input tibanna_config = { "run_name": run_name, "mem": mem, "cpu": cpu, "ebs_size": math.ceil(job.resources["disk_mb"] / 1024), "log_bucket": self.s3_bucket, } tibanna_args = ec2_utils.Args( output_S3_bucket=self.s3_bucket, language="snakemake", container_image=self.container_image, input_files=input_source, output_target=output_target, ) self.add_workflow_files(job, tibanna_args) self.add_command(job, tibanna_args, tibanna_config) tibanna_input = { "jobid": jobid, "config": tibanna_config, "args": tibanna_args.as_dict(), } logger.debug(json.dumps(tibanna_input, indent=4)) return tibanna_input def run(self, job, callback=None, submit_callback=None, error_callback=None): logger.info("running job using Tibanna...") from tibanna.core import API super()._run(job) # submit job here, and obtain job ids from the backend tibanna_input = self.make_tibanna_input(job) jobid = tibanna_input["jobid"] exec_info = API().run_workflow( tibanna_input, sfn=self.tibanna_sfn, verbose=not self.quiet, jobid=jobid ) exec_arn = exec_info.get("_tibanna", {}).get("exec_arn", "") jobname = tibanna_input["config"]["run_name"] jobid = tibanna_input["jobid"] # register job as active, using your own namedtuple. # The namedtuple must at least contain the attributes # job, jobid, callback, error_callback. self.active_jobs.append( TibannaJob(job, jobname, jobid, exec_arn, callback, error_callback) ) def _wait_for_jobs(self): # busy wait on job completion # This is only needed if your backend does not allow to use callbacks # for obtaining job status. from tibanna.core import API while True: # always use self.lock to avoid race conditions with self.lock: if not self.wait: return active_jobs = self.active_jobs self.active_jobs = list() still_running = list() for j in active_jobs: # use self.status_rate_limiter to avoid too many API calls. with self.status_rate_limiter: if j.exec_arn: status = API().check_status(j.exec_arn) else: status = "FAILED_AT_SUBMISSION" if not self.quiet or status != "RUNNING": logger.debug("job %s: %s" % (j.jobname, status)) if status == "RUNNING": still_running.append(j) elif status == "SUCCEEDED": j.callback(j.job) else: j.error_callback(j.job) with self.lock: self.active_jobs.extend(still_running) sleep() def run_wrapper( job_rule, input, output, params, wildcards, threads, resources, log, benchmark, benchmark_repeats, conda_env, singularity_img, singularity_args, env_modules, use_singularity, linemaps, debug, cleanup_scripts, shadow_dir, jobid, ): """ Wrapper around the run method that handles exceptions and benchmarking. Arguments job_rule -- the ``job.rule`` member input -- list of input files output -- list of output files wildcards -- so far processed wildcards threads -- usable threads log -- list of log files shadow_dir -- optional shadow directory root """ # get shortcuts to job_rule members run = job_rule.run_func version = job_rule.version rule = job_rule.name is_shell = job_rule.shellcmd is not None if os.name == "posix" and debug: sys.stdin = open("/dev/stdin") if benchmark is not None: from snakemake.benchmark import ( BenchmarkRecord, benchmarked, write_benchmark_records, ) # Change workdir if shadow defined and not using singularity. # Otherwise, we do the change from inside the container. passed_shadow_dir = None if use_singularity and singularity_img: passed_shadow_dir = shadow_dir shadow_dir = None try: with change_working_directory(shadow_dir): if benchmark: bench_records = [] for bench_iteration in range(benchmark_repeats): # Determine whether to benchmark this process or do not # benchmarking at all. We benchmark this process unless the # execution is done through the ``shell:``, ``script:``, or # ``wrapper:`` stanza. is_sub = ( job_rule.shellcmd or job_rule.script or job_rule.wrapper or job_rule.cwl ) if is_sub: # The benchmarking through ``benchmarked()`` is started # in the execution of the shell fragment, script, wrapper # etc, as the child PID is available there. bench_record = BenchmarkRecord() run( input, output, params, wildcards, threads, resources, log, version, rule, conda_env, singularity_img, singularity_args, use_singularity, env_modules, bench_record, jobid, is_shell, bench_iteration, cleanup_scripts, passed_shadow_dir, ) else: # The benchmarking is started here as we have a run section # and the generated Python function is executed in this # process' thread. with benchmarked() as bench_record: run( input, output, params, wildcards, threads, resources, log, version, rule, conda_env, singularity_img, singularity_args, use_singularity, env_modules, bench_record, jobid, is_shell, bench_iteration, cleanup_scripts, passed_shadow_dir, ) # Store benchmark record for this iteration bench_records.append(bench_record) else: run( input, output, params, wildcards, threads, resources, log, version, rule, conda_env, singularity_img, singularity_args, use_singularity, env_modules, None, jobid, is_shell, None, cleanup_scripts, passed_shadow_dir, ) except (KeyboardInterrupt, SystemExit) as e: # Re-raise the keyboard interrupt in order to record an error in the # scheduler but ignore it raise e except (Exception, BaseException) as ex: log_verbose_traceback(ex) # this ensures that exception can be re-raised in the parent thread lineno, file = get_exception_origin(ex, linemaps) raise RuleException( format_error( ex, lineno, linemaps=linemaps, snakefile=file, show_traceback=True ) ) if benchmark is not None: try: write_benchmark_records(bench_records, benchmark) except (Exception, BaseException) as ex: raise WorkflowError(ex) snakemake-5.10.0/snakemake/gui.html000066400000000000000000000304711361131222100171420ustar00rootroot00000000000000 Snakemake

Resources

{% for resource in resources %}
{% endfor %}
snakemake-5.10.0/snakemake/gui.py000066400000000000000000000105021361131222100166170ustar00rootroot00000000000000__author__ = "Johannes Köster" __copyright__ = "Copyright 2015-2019, Johannes Köster" __email__ = "koester@jimmy.harvard.edu" __license__ = "MIT" import json import os import threading from flask import Flask, render_template, request from snakemake.common import __version__ LOCK = threading.Lock() app = Flask("snakemake", template_folder=os.path.dirname(__file__)) # app.debug=True app.extensions = { "dag": None, "run_snakemake": None, "progress": "", "log": [], "status": {"running": False}, "args": None, "targets": [], "rule_info": [], "resources": [], } def register(run_snakemake, args): app.extensions["run_snakemake"] = run_snakemake app.extensions["args"] = dict( targets=args.target, cluster=args.cluster, workdir=args.directory, touch=args.touch, forcetargets=args.force, forceall=args.forceall, forcerun=args.forcerun, prioritytargets=args.prioritize, stats=args.stats, keepgoing=args.keep_going, jobname=args.jobname, immediate_submit=args.immediate_submit, ignore_ambiguity=args.allow_ambiguity, lock=not args.nolock, force_incomplete=args.rerun_incomplete, ignore_incomplete=args.ignore_incomplete, jobscript=args.jobscript, notemp=args.notemp, latency_wait=args.latency_wait, ) target_rules = [] def log_handler(msg): if msg["level"] == "rule_info": target_rules.append(msg["name"]) run_snakemake(list_target_rules=True, log_handler=log_handler) for target in args.target: target_rules.remove(target) app.extensions["targets"] = args.target + target_rules resources = [] def log_handler(msg): if msg["level"] == "info": resources.append(msg["msg"]) run_snakemake(list_resources=True, log_handler=log_handler) app.extensions["resources"] = resources app.extensions["snakefilepath"] = os.path.abspath(args.snakefile) def run_snakemake(**kwargs): args = dict(app.extensions["args"]) args.update(kwargs) app.extensions["run_snakemake"](**args) @app.route("/") def index(): args = app.extensions["args"] return render_template( "gui.html", targets=app.extensions["targets"], cores_label="Nodes" if args["cluster"] else "Cores", resources=app.extensions["resources"], snakefilepath=app.extensions["snakefilepath"], version=__version__, node_width=15, node_padding=10, ) @app.route("/dag") def dag(): if app.extensions["dag"] is None: def record(msg): if msg["level"] == "d3dag": app.extensions["dag"] = msg elif msg["level"] in ("error", "info"): app.extensions["log"].append(msg) run_snakemake(printd3dag=True, log_handler=record) return json.dumps(app.extensions["dag"]) @app.route("/log/") def log(id): log = app.extensions["log"][id:] return json.dumps(log) @app.route("/progress") def progress(): return json.dumps(app.extensions["progress"]) def _run(dryrun=False): def log_handler(msg): level = msg["level"] if level == "progress": app.extensions["progress"] = msg elif level in ("info", "error", "job_info", "job_finished"): app.extensions["log"].append(msg) with LOCK: app.extensions["status"]["running"] = True run_snakemake(log_handler=log_handler, dryrun=dryrun) with LOCK: app.extensions["status"]["running"] = False return "" @app.route("/run") def run(): _run() @app.route("/dryrun") def dryrun(): _run(dryrun=True) @app.route("/status") def status(): with LOCK: return json.dumps(app.extensions["status"]) @app.route("/targets") def targets(): return json.dumps(app.extensions["targets"]) @app.route("/get_args") def get_args(): return json.dumps(app.extensions["args"]) @app.route("/set_args", methods=["POST"]) def set_args(): app.extensions["args"].update( {name: value for name, value in request.form.items() if not name.endswith("[]")} ) targets = request.form.getlist("targets[]") if targets != app.extensions["args"]["targets"]: app.extensions["dag"] = None app.extensions["args"]["targets"] = targets return "" snakemake-5.10.0/snakemake/io.py000077500000000000000000001261271361131222100164600ustar00rootroot00000000000000__author__ = "Johannes Köster" __copyright__ = "Copyright 2015-2019, Johannes Köster" __email__ = "koester@jimmy.harvard.edu" __license__ = "MIT" import collections import os import shutil from pathlib import Path import re import stat import time import datetime import json import copy import functools import subprocess as sp from itertools import product, chain from contextlib import contextmanager import string import collections from snakemake.exceptions import ( MissingOutputException, WorkflowError, WildcardError, RemoteFileException, ) from snakemake.logging import logger from inspect import isfunction, ismethod from snakemake.common import DYNAMIC_FILL def lutime(f, times): # In some cases, we have a platform where os.supports_follow_symlink includes stat() # but not utime(). This leads to an anomaly. In any case we never want to touch the # target of a link. if os.utime in os.supports_follow_symlinks: # ...utime is well behaved os.utime(f, times, follow_symlinks=False) elif not os.path.islink(f): # ...symlinks not an issue here os.utime(f, times) else: try: # try the system command if times: fmt_time = lambda sec: datetime.fromtimestamp(sec).strftime( "%Y%m%d%H%M.%S" ) atime, mtime = times sp.check_call(["touch", "-h", f, "-a", "-t", fmt_time(atime)]) sp.check_call(["touch", "-h", f, "-m", "-t", fmt_time(mtime)]) else: sp.check_call(["touch", "-h", f]) except sp.CalledProcessError: pass # ...problem system. Do nothing. logger.warning( "Unable to set utime on symlink {}. Your Python build does not support it.".format( f ) ) return None if os.chmod in os.supports_follow_symlinks: def lchmod(f, mode): os.chmod(f, mode, follow_symlinks=False) else: def lchmod(f, mode): os.chmod(f, mode) class IOCache: def __init__(self): self.mtime = dict() self.exists_local = dict() self.exists_remote = dict() self.size = dict() self.active = True def clear(self): self.mtime.clear() self.size.clear() self.exists_local.clear() self.exists_remote.clear() def deactivate(self): self.clear() self.active = False def IOFile(file, rule=None): assert rule is not None f = _IOFile(file) f.rule = rule return f class _IOFile(str): """ A file that is either input or output of a rule. """ __slots__ = ["_is_function", "_file", "rule", "_regex"] def __new__(cls, file): obj = str.__new__(cls, file) obj._is_function = isfunction(file) or ismethod(file) obj._is_function = obj._is_function or ( isinstance(file, AnnotatedString) and bool(file.callable) ) obj._file = file obj.rule = None obj._regex = None if obj.is_remote: obj.remote_object._iofile = obj return obj def iocache(func): @functools.wraps(func) def wrapper(self, *args, **kwargs): if self.rule.workflow.iocache.active: cache = getattr(self.rule.workflow.iocache, func.__name__) if self in cache: return cache[self] v = func(self, *args, **kwargs) cache[self] = v return v else: return func(self, *args, **kwargs) return wrapper def _refer_to_remote(func): """ A decorator so that if the file is remote and has a version of the same file-related function, call that version instead. """ @functools.wraps(func) def wrapper(self, *args, **kwargs): if self.is_remote: if hasattr(self.remote_object, func.__name__): return getattr(self.remote_object, func.__name__)(*args, **kwargs) return func(self, *args, **kwargs) return wrapper @contextmanager def open(self, mode="r", buffering=-1, encoding=None, errors=None, newline=None): """Open this file. If necessary, download it from remote first. This can (and should) be used in a `with`-statement. """ if not self.exists: raise WorkflowError( "File {} cannot be opened, since it does not exist.".format(self) ) if not self.exists_local and self.is_remote: self.download_from_remote() f = open(self) try: yield f finally: f.close() @property def is_remote(self): return is_flagged(self._file, "remote_object") @property def is_ancient(self): return is_flagged(self._file, "ancient") @property def is_directory(self): return is_flagged(self._file, "directory") @property def is_multiext(self): return is_flagged(self._file, "multiext") @property def multiext_prefix(self): return get_flag_value(self._file, "multiext") def update_remote_filepath(self): # if the file string is different in the iofile, update the remote object # (as in the case of wildcard expansion) remote_object = self.remote_object if remote_object._file != self._file: remote_object._iofile = self @property def should_keep_local(self): return self.remote_object.keep_local @property def should_stay_on_remote(self): return self.remote_object.stay_on_remote @property def remote_object(self): return get_flag_value(self._file, "remote_object") @property @_refer_to_remote def file(self): if not self._is_function: return self._file else: raise ValueError( "This IOFile is specified as a function and " "may not be used directly." ) def check(self): hint = ( "It can also lead to inconsistent results of the file-matching " "approach used by Snakemake." ) if self._file.startswith("./"): logger.warning( "Relative file path '{}' starts with './'. This is redundant " "and strongly discouraged. {} You can simply omit the './' " "for relative file paths.".format(self._file, hint) ) if self._file.startswith(" "): logger.warning( "File path '{}' starts with whitespace. " "This is likely unintended. {}".format(self._file, hint) ) if self._file.endswith(" "): logger.warning( "File path '{}' ends with whitespace. " "This is likely unintended. {}".format(self._file, hint) ) if "\n" in self._file: logger.warning( "File path '{}' contains line break. " "This is likely unintended. {}".format(self._file, hint) ) if _double_slash_regex.search(self._file) is not None and not self.is_remote: logger.warning( "File path {} contains double '{}'. " "This is likely unintended. {}".format(self._file, os.path.sep, hint) ) @property def exists(self): if self.is_remote: return self.exists_remote else: return self.exists_local def parents(self, omit=0): """Yield all parent paths, omitting the given number of ancestors.""" for p in list(Path(self.file).parents)[::-1][omit:]: p = IOFile(str(p), rule=self.rule) p.clone_flags(self) yield p @property @iocache def exists_local(self): if self.rule.workflow.iocache.active: # The idea is to first check existence of parent directories and # cache the results. # We omit the last ancestor, because this is always "." or "/" or a # drive letter. for p in self.parents(omit=1): try: if not p.exists_local: return False except: # In case of an error, we continue, because it can be that # we simply don't have the permissions to access a parent # directory. continue return os.path.exists(self.file) @property @iocache def exists_remote(self): if not self.is_remote: return False if ( self.rule.workflow.iocache.active and self.remote_object.provider.allows_directories ): # The idea is to first check existence of parent directories and # cache the results. # We omit the last 2 ancestors, because these are "." and the host # name of the remote location. for p in self.parents(omit=2): try: if not p.exists_remote: return False except: # In case of an error, we continue, because it can be that # we simply don't have the permissions to access a parent # directory in the remote. continue return self.remote_object.exists() @property def protected(self): """Returns True if the file is protected. Always False for symlinks.""" # symlinks are never regarded as protected return ( self.exists_local and not os.access(self.file, os.W_OK) and not os.path.islink(self.file) ) @property @iocache @_refer_to_remote def mtime(self): return self.mtime_local @property def mtime_local(self): # do not follow symlinks for modification time if os.path.isdir(self.file) and os.path.exists( os.path.join(self.file, ".snakemake_timestamp") ): return os.lstat(os.path.join(self.file, ".snakemake_timestamp")).st_mtime else: return os.lstat(self.file).st_mtime @property def flags(self): return getattr(self._file, "flags", {}) @property @iocache @_refer_to_remote def size(self): return self.size_local @property def size_local(self): # follow symlinks but throw error if invalid self.check_broken_symlink() return os.path.getsize(self.file) def check_broken_symlink(self): """ Raise WorkflowError if file is a broken symlink. """ if not self.exists_local and os.lstat(self.file): raise WorkflowError( "File {} seems to be a broken symlink.".format(self.file) ) @_refer_to_remote def is_newer(self, time): """ Returns true of the file is newer than time, or if it is a symlink that points to a file newer than time. """ if self.is_ancient: return False elif self.is_remote: # If file is remote but provider does not override the implementation this # is the best we can do. return self.mtime > time else: if os.path.isdir(self.file) and os.path.exists( os.path.join(self.file, ".snakemake_timestamp") ): st_mtime_file = os.path.join(self.file, ".snakemake_timestamp") else: st_mtime_file = self.file try: return os.stat(st_mtime_file).st_mtime > time or self.mtime > time except FileNotFoundError: raise WorkflowError( "File {} not found although it existed before. Is there another active process that might have deleted it?".format( self.file ) ) def download_from_remote(self): if self.is_remote and self.remote_object.exists(): if not self.should_stay_on_remote: logger.info("Downloading from remote: {}".format(self.file)) self.remote_object.download() logger.info("Finished download.") else: raise RemoteFileException( "The file to be downloaded does not seem to exist remotely." ) def upload_to_remote(self): if self.is_remote: logger.info("Uploading to remote: {}".format(self.file)) self.remote_object.upload() logger.info("Finished upload.") def prepare(self): path_until_wildcard = re.split(DYNAMIC_FILL, self.file)[0] dir = os.path.dirname(path_until_wildcard) if len(dir) > 0: try: os.makedirs(dir, exist_ok=True) except OSError as e: # ignore Errno 17 "File exists" (reason: multiprocessing) if e.errno != 17: raise e if is_flagged(self._file, "pipe"): os.mkfifo(self._file) def protect(self): mode = ( os.lstat(self.file).st_mode & ~stat.S_IWUSR & ~stat.S_IWGRP & ~stat.S_IWOTH ) if os.path.isdir(self.file): for root, dirs, files in os.walk(self.file): for d in dirs: lchmod(os.path.join(self.file, d), mode) for f in files: lchmod(os.path.join(self.file, f), mode) lchmod(self.file, mode) def remove(self, remove_non_empty_dir=False): if self.is_directory: remove(self, remove_non_empty_dir=True) else: remove(self, remove_non_empty_dir=remove_non_empty_dir) def touch(self, times=None): """ times must be 2-tuple: (atime, mtime) """ try: if self.is_directory: file = os.path.join(self.file, ".snakemake_timestamp") # Create the flag file if it doesn't exist if not os.path.exists(file): with open(file, "w") as f: pass lutime(file, times) else: lutime(self.file, times) except OSError as e: if e.errno == 2: raise MissingOutputException( "Output file {} of rule {} shall be touched but " "does not exist.".format(self.file, self.rule.name), lineno=self.rule.lineno, snakefile=self.rule.snakefile, ) else: raise e def touch_or_create(self): try: self.touch() except MissingOutputException: # first create directory if it does not yet exist dir = self.file if self.is_directory else os.path.dirname(self.file) if dir: os.makedirs(dir, exist_ok=True) # create empty file file = ( os.path.join(self.file, ".snakemake_timestamp") if self.is_directory else self.file ) with open(file, "w") as f: pass def apply_wildcards(self, wildcards, fill_missing=False, fail_dynamic=False): f = self._file if self._is_function: f = self._file(Namedlist(fromdict=wildcards)) # this bit ensures flags are transferred over to files after # wildcards are applied file_with_wildcards_applied = IOFile( apply_wildcards( f, wildcards, fill_missing=fill_missing, fail_dynamic=fail_dynamic, dynamic_fill=DYNAMIC_FILL, ), rule=self.rule, ) file_with_wildcards_applied.clone_flags(self) return file_with_wildcards_applied def get_wildcard_names(self): return get_wildcard_names(self.file) def contains_wildcard(self): return contains_wildcard(self.file) def regex(self): if self._regex is None: # compile a regular expression self._regex = re.compile(regex(self.file)) return self._regex def constant_prefix(self): first_wildcard = _wildcard_regex.search(self.file) if first_wildcard: return self.file[: first_wildcard.start()] return self.file def constant_suffix(self): m = None for m in _wildcard_regex.finditer(self.file): pass last_wildcard = m if last_wildcard: return self.file[last_wildcard.end() :] return self.file def match(self, target): return self.regex().match(target) or None def format_dynamic(self): return self.replace(DYNAMIC_FILL, "{*}") def clone_flags(self, other): if isinstance(self._file, str): self._file = AnnotatedString(self._file) if isinstance(other._file, AnnotatedString): self._file.flags = getattr(other._file, "flags", {}).copy() if "remote_object" in self._file.flags: self._file.flags["remote_object"] = copy.copy( self._file.flags["remote_object"] ) self.update_remote_filepath() def clone_remote_object(self, other): if ( isinstance(other._file, AnnotatedString) and "remote_object" in other._file.flags ): self._file.flags["remote_object"] = copy.copy( other._file.flags["remote_object"] ) self.update_remote_filepath() def set_flags(self, flags): if isinstance(self._file, str): self._file = AnnotatedString(self._file) self._file.flags = flags def __eq__(self, other): f = other._file if isinstance(other, _IOFile) else other return self._file == f def __hash__(self): return self._file.__hash__() _double_slash_regex = ( re.compile(r"([^:]//|^//)") if os.path.sep == "/" else re.compile(r"\\\\") ) _wildcard_regex = re.compile( r""" \{ (?=( # This lookahead assertion emulates an 'atomic group' # which is required for performance \s*(?P\w+) # wildcard name (\s*,\s* (?P # an optional constraint ([^{}]+ | \{\d+(,\d+)?\})* # allow curly braces to nest one level ) # ... as in '{w,a{3,5}}' )?\s* ))\1 \} """, re.VERBOSE, ) def wait_for_files( files, latency_wait=3, force_stay_on_remote=False, ignore_pipe=False ): """Wait for given files to be present in filesystem.""" files = list(files) def get_missing(): return [ f for f in files if not ( f.exists_remote if ( isinstance(f, _IOFile) and f.is_remote and (force_stay_on_remote or f.should_stay_on_remote) ) else os.path.exists(f) if not (is_flagged(f, "pipe") and ignore_pipe) else True ) ] missing = get_missing() if missing: logger.info( "Waiting at most {} seconds for missing files.".format(latency_wait) ) for _ in range(latency_wait): if not get_missing(): return time.sleep(1) raise IOError( "Missing files after {} seconds:\n{}".format( latency_wait, "\n".join(get_missing()) ) ) def get_wildcard_names(pattern): return set(match.group("name") for match in _wildcard_regex.finditer(pattern)) def contains_wildcard(path): return _wildcard_regex.search(path) is not None def contains_wildcard_constraints(pattern): return any(match.group("constraint") for match in _wildcard_regex.finditer(pattern)) def remove(file, remove_non_empty_dir=False): if file.is_remote and file.should_stay_on_remote: if file.exists_remote: file.remote_object.remove() elif os.path.isdir(file) and not os.path.islink(file): if remove_non_empty_dir: shutil.rmtree(file) else: try: os.removedirs(file) except OSError as e: # skip non empty directories if e.errno == 39: logger.info( "Skipped removing non-empty directory {}".format(e.filename) ) else: logger.warning(str(e)) # Remember that dangling symlinks fail the os.path.exists() test, but # we definitely still want to zap them. try/except is the safest way. # Also, we don't want to remove the null device if it is an output. elif os.devnull != str(file): try: os.remove(file) except FileNotFoundError: pass def regex(filepattern): f = [] last = 0 wildcards = set() for match in _wildcard_regex.finditer(filepattern): f.append(re.escape(filepattern[last : match.start()])) wildcard = match.group("name") if wildcard in wildcards: if match.group("constraint"): raise ValueError( "Constraint regex must be defined only in the first " "occurence of the wildcard in a string." ) f.append("(?P={})".format(wildcard)) else: wildcards.add(wildcard) f.append( "(?P<{}>{})".format( wildcard, match.group("constraint") if match.group("constraint") else ".+", ) ) last = match.end() f.append(re.escape(filepattern[last:])) f.append("$") # ensure that the match spans the whole file return "".join(f) def apply_wildcards( pattern, wildcards, fill_missing=False, fail_dynamic=False, dynamic_fill=None, keep_dynamic=False, ): def format_match(match): name = match.group("name") try: value = wildcards[name] if fail_dynamic and value == dynamic_fill: raise WildcardError(name) return str(value) # convert anything into a str except KeyError as ex: if keep_dynamic: return "{{{}}}".format(name) elif fill_missing: return dynamic_fill else: raise WildcardError(str(ex)) return re.sub(_wildcard_regex, format_match, pattern) def not_iterable(value): return ( isinstance(value, str) or isinstance(value, dict) or not isinstance(value, collections.abc.Iterable) ) def is_callable(value): return ( callable(value) or (isinstance(value, _IOFile) and value._is_function) or (isinstance(value, AnnotatedString) and value.callable is not None) ) class AnnotatedString(str): def __init__(self, value): self.flags = dict() self.callable = value if is_callable(value) else None def flag(value, flag_type, flag_value=True): if isinstance(value, AnnotatedString): value.flags[flag_type] = flag_value return value if not_iterable(value): value = AnnotatedString(value) value.flags[flag_type] = flag_value return value return [flag(v, flag_type, flag_value=flag_value) for v in value] def is_flagged(value, flag): if isinstance(value, AnnotatedString): return flag in value.flags and value.flags[flag] if isinstance(value, _IOFile): return flag in value.flags and value.flags[flag] return False def get_flag_value(value, flag_type): if isinstance(value, AnnotatedString) or isinstance(value, _IOFile): if flag_type in value.flags: return value.flags[flag_type] else: return None def ancient(value): """ A flag for an input file that shall be considered ancient; i.e. its timestamp shall have no effect on which jobs to run. """ return flag(value, "ancient") def directory(value): """ A flag to specify that an output is a directory, rather than a file or named pipe. """ if is_flagged(value, "pipe"): raise SyntaxError("Pipe and directory flags are mutually exclusive.") if is_flagged(value, "remote"): raise SyntaxError("Remote and directory flags are mutually exclusive.") if is_flagged(value, "dynamic"): raise SyntaxError("Dynamic and directory flags are mutually exclusive.") return flag(value, "directory") def temp(value): """ A flag for an input or output file that shall be removed after usage. """ if is_flagged(value, "protected"): raise SyntaxError("Protected and temporary flags are mutually exclusive.") if is_flagged(value, "remote"): raise SyntaxError("Remote and temporary flags are mutually exclusive.") return flag(value, "temp") def pipe(value): if is_flagged(value, "protected"): raise SyntaxError("Pipes may not be protected.") if is_flagged(value, "remote"): raise SyntaxError("Pipes may not be remote files.") return flag(value, "pipe") def temporary(value): """ An alias for temp. """ return temp(value) def protected(value): """ A flag for a file that shall be write protected after creation. """ if is_flagged(value, "temp"): raise SyntaxError("Protected and temporary flags are mutually exclusive.") if is_flagged(value, "remote"): raise SyntaxError("Remote and protected flags are mutually exclusive.") return flag(value, "protected") def dynamic(value): """ A flag for a file that shall be dynamic, i.e. the multiplicity (and wildcard values) will be expanded after a certain rule has been run """ logger.warning( "Dynamic output is deprecated in favor of checkpoints (see docs). " "It will be removed in Snakemake 6.0." ) annotated = flag(value, "dynamic", True) tocheck = [annotated] if not_iterable(annotated) else annotated for file in tocheck: matches = list(_wildcard_regex.finditer(file)) # if len(matches) != 1: # raise SyntaxError("Dynamic files need exactly one wildcard.") for match in matches: if match.group("constraint"): raise SyntaxError( "The wildcards in dynamic files cannot be constrained." ) return annotated def touch(value): return flag(value, "touch") def unpack(value): return flag(value, "unpack") def repeat(value, n_repeat): """Flag benchmark records with the number of repeats.""" return flag(value, "repeat", n_repeat) def checkpoint_target(value): return flag(value, "checkpoint_target") ReportObject = collections.namedtuple("ReportObject", ["caption", "category"]) def report(value, caption=None, category=None): """Flag output file as to be included into reports.""" return flag(value, "report", ReportObject(caption, category)) def local(value): """Mark a file as local file. This disables application of a default remote provider. """ if is_flagged(value, "remote"): raise SyntaxError("Remote and local flags are mutually exclusive.") return flag(value, "local") def expand(*args, **wildcards): """ Expand wildcards in given filepatterns. Arguments *args -- first arg: filepatterns as list or one single filepattern, second arg (optional): a function to combine wildcard values (itertools.product per default) **wildcards -- the wildcards as keyword arguments with their values as lists. If allow_missing=True is included wildcards in filepattern without values will stay unformatted. """ filepatterns = args[0] if len(args) == 1: combinator = product elif len(args) == 2: combinator = args[1] if isinstance(filepatterns, str): filepatterns = [filepatterns] def path_to_str(f): if isinstance(f, Path): return str(f) return f filepatterns = list(map(path_to_str, filepatterns)) if any(map(lambda f: getattr(f, "flags", {}), filepatterns)): raise WorkflowError( "Flags in file patterns given to expand() are invalid. " "Flags (e.g. temp(), directory()) have to be applied outside " "of expand (e.g. 'temp(expand(\"plots/{sample}.pdf\", sample=SAMPLES))')." ) # check if remove missing is provided format_dict = dict if "allow_missing" in wildcards and wildcards["allow_missing"] is True: class FormatDict(dict): def __missing__(self, key): return "{" + key + "}" format_dict = FormatDict # check that remove missing is not a wildcard in the filepatterns for filepattern in filepatterns: if "allow_missing" in re.findall(r"{([^}\.[!:]+)", filepattern): format_dict = dict break # remove unused wildcards to avoid duplicate filepatterns wildcards = { filepattern: { k: v for k, v in wildcards.items() if k in re.findall(r"{([^}\.[!:]+)", filepattern) } for filepattern in filepatterns } def flatten(wildcards): for wildcard, values in wildcards.items(): if isinstance(values, str) or not isinstance( values, collections.abc.Iterable ): values = [values] yield [(wildcard, value) for value in values] formatter = string.Formatter() try: return [ formatter.vformat(filepattern, (), comb) for filepattern in filepatterns for comb in map(format_dict, combinator(*flatten(wildcards[filepattern]))) ] except KeyError as e: raise WildcardError("No values given for wildcard {}.".format(e)) def multiext(prefix, *extensions): """Expand a given prefix with multiple extensions (e.g. .txt, .csv, ...).""" if any( ("/" in ext or "\\" in ext or not ext.startswith(".")) for ext in extensions ): raise WorkflowError( "Extensions for multiext may not contain path delimiters " "(/,\) and must start with '.' (e.g. .txt)." ) return [flag(prefix + ext, "multiext", flag_value=prefix) for ext in extensions] def limit(pattern, **wildcards): """ Limit wildcards to the given values. Arguments: **wildcards -- the wildcards as keyword arguments with their values as lists """ return pattern.format( **{ wildcard: "{{{},{}}}".format(wildcard, "|".join(values)) for wildcard, values in wildcards.items() } ) def glob_wildcards(pattern, files=None, followlinks=False): """ Glob the values of the wildcards by matching the given pattern to the filesystem. Returns a named tuple with a list of values for each wildcard. """ pattern = os.path.normpath(pattern) first_wildcard = re.search("{[^{]", pattern) dirname = ( os.path.dirname(pattern[: first_wildcard.start()]) if first_wildcard else os.path.dirname(pattern) ) if not dirname: dirname = "." names = [match.group("name") for match in _wildcard_regex.finditer(pattern)] Wildcards = collections.namedtuple("Wildcards", names) wildcards = Wildcards(*[list() for name in names]) pattern = re.compile(regex(pattern)) if files is None: files = ( os.path.normpath(os.path.join(dirpath, f)) for dirpath, dirnames, filenames in os.walk( dirname, followlinks=followlinks ) for f in chain(filenames, dirnames) ) for f in files: match = re.match(pattern, f) if match: for name, value in match.groupdict().items(): getattr(wildcards, name).append(value) return wildcards def update_wildcard_constraints( pattern, wildcard_constraints, global_wildcard_constraints ): """Update wildcard constraints Args: pattern (str): pattern on which to update constraints wildcard_constraints (dict): dictionary of wildcard:constraint key-value pairs global_wildcard_constraints (dict): dictionary of wildcard:constraint key-value pairs """ def replace_constraint(match): name = match.group("name") constraint = match.group("constraint") newconstraint = wildcard_constraints.get( name, global_wildcard_constraints.get(name) ) if name in examined_names: return match.group(0) examined_names.add(name) # Don't override if constraint already set if constraint is not None: return match.group(0) # Only update if a new constraint has actually been set elif newconstraint is not None: return "{{{},{}}}".format(name, newconstraint) else: return match.group(0) examined_names = set() updated = re.sub(_wildcard_regex, replace_constraint, pattern) # inherit flags if isinstance(pattern, AnnotatedString): updated = AnnotatedString(updated) updated.flags = dict(pattern.flags) return updated def split_git_path(path): file_sub = re.sub(r"^git\+file:/+", "/", path) (file_path, version) = file_sub.split("@") file_path = os.path.realpath(file_path) root_path = get_git_root(file_path) if file_path.startswith(root_path): file_path = file_path[len(root_path) :].lstrip("/") return (root_path, file_path, version) def get_git_root(path): """ Args: path: (str) Path a to a directory/file that is located inside the repo Returns: path to root folder for git repo """ import git try: git_repo = git.Repo(path, search_parent_directories=True) return git_repo.git.rev_parse("--show-toplevel") except git.exc.NoSuchPathError as e: tail, head = os.path.split(path) return get_git_root_parent_directory(tail, path) def get_git_root_parent_directory(path, input_path): """ This function will recursively go through parent directories until a git repository is found or until no parent directories are left, in which case a error will be raised. This is needed when providing a path to a file/folder that is located on a branch/tag no currently checked out. Args: path: (str) Path a to a directory that is located inside the repo input_path: (str) origin path, used when raising WorkflowError Returns: path to root folder for git repo """ import git try: git_repo = git.Repo(path, search_parent_directories=True) return git_repo.git.rev_parse("--show-toplevel") except git.exc.NoSuchPathError as e: tail, head = os.path.split(path) if tail is None: raise WorkflowError( "Neither provided git path ({}) ".format(input_path) + "or parent directories contain a valid git repo." ) else: return get_git_root_parent_directory(tail, input_path) def git_content(git_file): """ This function will extract a file from a git repository, one located on the filesystem. Expected format is git+file:///path/to/your/repo/path_to_file@@version Args: env_file (str): consist of path to repo, @, version and file information Ex: git+file:////home/smeds/snakemake-wrappers/bio/fastqc/wrapper.py@0.19.3 Returns: file content or None if the expected format isn't meet """ import git if git_file.startswith("git+file:"): (root_path, file_path, version) = split_git_path(git_file) return git.Repo(root_path).git.show("{}:{}".format(version, file_path)) else: raise WorkflowError( "Provided git path ({}) doesn't meet the " "expected format:".format(git_file) + ", expected format is " "git+file://PATH_TO_REPO/PATH_TO_FILE_INSIDE_REPO@VERSION" ) return None def strip_wildcard_constraints(pattern): """Return a string that does not contain any wildcard constraints.""" def strip_constraint(match): return "{{{}}}".format(match.group("name")) return _wildcard_regex.sub(strip_constraint, pattern) class Namedlist(list): """ A list that additionally provides functions to name items. Further, it is hashable, however the hash does not consider the item names. """ def __init__( self, toclone=None, fromdict=None, plainstr=False, strip_constraints=False, custom_map=None, ): """ Create the object. Arguments toclone -- another Namedlist that shall be cloned fromdict -- a dict that shall be converted to a Namedlist (keys become names) """ list.__init__(self) self._names = dict() if toclone: if custom_map is not None: self.extend(map(custom_map, toclone)) elif plainstr: self.extend(map(str, toclone)) elif strip_constraints: self.extend(map(strip_wildcard_constraints, toclone)) else: self.extend(toclone) if isinstance(toclone, Namedlist): self._take_names(toclone._get_names()) if fromdict: for key, item in fromdict.items(): self.append(item) self._add_name(key) def _add_name(self, name): """ Add a name to the last item. Arguments name -- a name """ self._set_name(name, len(self) - 1) def _set_name(self, name, index, end=None): """ Set the name of an item. Arguments name -- a name index -- the item index """ if name == "items" or name == "keys" or name == "get": raise AttributeError( "invalid name for input, output, wildcard, " "params or log: 'items', 'keys', and 'get' are reserved for internal use" ) self._names[name] = (index, end) if end is None: setattr(self, name, self[index]) else: setattr(self, name, Namedlist(toclone=self[index:end])) def _get_names(self): """ Get the defined names as (name, index) pairs. """ for name, index in self._names.items(): yield name, index def _take_names(self, names): """ Take over the given names. Arguments names -- the given names as (name, index) pairs """ for name, (i, j) in names: self._set_name(name, i, end=j) def items(self): for name in self._names: yield name, getattr(self, name) def _allitems(self): next = 0 for name, index in sorted( self._names.items(), key=lambda item: ( item[1][0], item[1][0] + 1 if item[1][1] is None else item[1][1], ), ): start, end = index if end is None: end = start + 1 if start > next: for item in self[next:start]: yield None, item yield name, getattr(self, name) next = end for item in self[next:]: yield None, item def _insert_items(self, index, items): self[index : index + 1] = items add = len(items) - 1 for name, (i, j) in self._names.items(): if i > index: self._names[name] = (i + add, None if j is None else j + add) elif i == index: self._set_name(name, i, end=i + len(items)) def keys(self): return self._names.keys() def _plainstrings(self): return self.__class__.__call__(toclone=self, plainstr=True) def _stripped_constraints(self): return self.__class__.__call__(toclone=self, strip_constraints=True) def _clone(self): return self.__class__.__call__(toclone=self) def get(self, key, default_value=None): return self.__dict__.get(key, default_value) def __getitem__(self, key): try: return super().__getitem__(key) except TypeError: pass return getattr(self, key) def __hash__(self): return hash(tuple(self)) def __str__(self): return " ".join(map(str, self)) class InputFiles(Namedlist): @property def size(self): return sum(f.size for f in self) class OutputFiles(Namedlist): pass class Wildcards(Namedlist): pass class Params(Namedlist): pass class Resources(Namedlist): pass class Log(Namedlist): pass def _load_configfile(configpath, filetype="Config"): "Tries to load a configfile first as JSON, then as YAML, into a dict." import yaml try: with open(configpath) as f: try: return json.load(f, object_pairs_hook=collections.OrderedDict) except ValueError: f.seek(0) # try again try: # From http://stackoverflow.com/a/21912744/84349 class OrderedLoader(yaml.Loader): pass def construct_mapping(loader, node): loader.flatten_mapping(node) return collections.OrderedDict(loader.construct_pairs(node)) OrderedLoader.add_constructor( yaml.resolver.BaseResolver.DEFAULT_MAPPING_TAG, construct_mapping ) return yaml.load(f, Loader=OrderedLoader) except yaml.YAMLError: raise WorkflowError( "Config file is not valid JSON or YAML. " "In case of YAML, make sure to not mix " "whitespace and tab indentation.".format(filetype) ) except FileNotFoundError: raise WorkflowError("{} file {} not found.".format(filetype, configpath)) def load_configfile(configpath): "Loads a JSON or YAML configfile as a dict, then checks that it's a dict." config = _load_configfile(configpath) if not isinstance(config, dict): raise WorkflowError( "Config file must be given as JSON or YAML " "with keys at top level." ) return config ##### Wildcard pumping detection ##### class PeriodicityDetector: def __init__(self, min_repeat=20, max_repeat=100): """ Args: max_repeat (int): The maximum length of the periodic substring. min_repeat (int): The minimum length of the periodic substring. """ self.regex = re.compile( "((?P.+)(?P=value){{{min_repeat},{max_repeat}}})$".format( min_repeat=min_repeat - 1, max_repeat=max_repeat - 1 ) ) def is_periodic(self, value): """Returns the periodic substring or None if not periodic.""" m = self.regex.search(value) # search for a periodic suffix. if m is not None: return m.group("value") snakemake-5.10.0/snakemake/jobs.py000066400000000000000000001316041361131222100167770ustar00rootroot00000000000000__author__ = "Johannes Köster" __copyright__ = "Copyright 2015-2019, Johannes Köster" __email__ = "koester@jimmy.harvard.edu" __license__ = "MIT" import hashlib import os import sys import base64 import tempfile import subprocess import json from collections import defaultdict from itertools import chain, filterfalse from functools import partial from operator import attrgetter from urllib.request import urlopen from urllib.parse import urlparse from snakemake.io import ( IOFile, Wildcards, Resources, _IOFile, is_flagged, get_flag_value, contains_wildcard, ) from snakemake.utils import format, listfiles from snakemake.exceptions import RuleException, ProtectedOutputException, WorkflowError from snakemake.exceptions import ( UnexpectedOutputException, CreateCondaEnvironmentException, ) from snakemake.logging import logger from snakemake.common import DYNAMIC_FILL, lazy_property, get_uuid from snakemake.deployment import conda from snakemake import wrapper def format_files(job, io, dynamicio): for f in io: if f in dynamicio: yield "{} (dynamic)".format(f.format_dynamic()) elif is_flagged(f, "pipe"): yield "{} (pipe)".format(f) elif is_flagged(f, "checkpoint_target"): yield "" else: yield f def jobfiles(jobs, type): return chain(*map(attrgetter(type), jobs)) class AbstractJob: def is_group(self): raise NotImplementedError() def log_info(self, skip_dynamic=False): raise NotImplementedError() def log_error(self, msg=None, **kwargs): raise NotImplementedError() def remove_existing_output(self): raise NotImplementedError() def download_remote_input(self): raise NotImplementedError() def properties(self, omit_resources=["_cores", "_nodes"], **aux_properties): raise NotImplementedError() class Job(AbstractJob): HIGHEST_PRIORITY = sys.maxsize __slots__ = [ "rule", "dag", "wildcards_dict", "wildcards", "_format_wildcards", "input", "dependencies", "output", "_params", "_log", "_benchmark", "_resources", "_conda_env_file", "_conda_env", "shadow_dir", "_inputsize", "dynamic_output", "dynamic_input", "temp_output", "protected_output", "touch_output", "subworkflow_input", "_hash", "_attempt", "_group", "targetfile", ] def __init__( self, rule, dag, wildcards_dict=None, format_wildcards=None, targetfile=None ): self.rule = rule self.dag = dag # the targetfile that led to the job # it is important to record this, since we need it to submit the # job on a cluster. In contrast, an arbitrary targetfile could # lead to a different composition of wildcard values (in case of # ambiguity in matching). self.targetfile = targetfile self.wildcards_dict = wildcards_dict self.wildcards = Wildcards(fromdict=self.wildcards_dict) self._format_wildcards = ( self.wildcards if format_wildcards is None else Wildcards(fromdict=format_wildcards) ) self.input, input_mapping, self.dependencies = self.rule.expand_input( self.wildcards_dict ) self.output, output_mapping = self.rule.expand_output(self.wildcards_dict) # other properties are lazy to be able to use additional parameters and check already existing files self._params = None self._log = None self._benchmark = None self._resources = None self._conda_env_file = None self._conda_env = None self._group = None self.shadow_dir = None self._inputsize = None self.is_updated = False self._attempt = self.dag.workflow.attempt # TODO get rid of these self.dynamic_output, self.dynamic_input = set(), set() self.temp_output, self.protected_output = set(), set() self.touch_output = set() self.subworkflow_input = dict() for f in self.output: f_ = output_mapping[f] if f_ in self.rule.dynamic_output: self.dynamic_output.add(f) if f_ in self.rule.temp_output: self.temp_output.add(f) if f_ in self.rule.protected_output: self.protected_output.add(f) if f_ in self.rule.touch_output: self.touch_output.add(f) for f in self.input: f_ = input_mapping[f] if f_ in self.rule.dynamic_input: self.dynamic_input.add(f) if f_ in self.rule.subworkflow_input: self.subworkflow_input[f] = self.rule.subworkflow_input[f_] elif "subworkflow" in f.flags: sub = f.flags["subworkflow"] if f in self.subworkflow_input: other = self.subworkflow_input[f] if sub != other: raise WorkflowError( "The input file {} is ambiguously " "associated with two subworkflows {} " "and {}.".format(f, sub, other), rule=self.rule, ) self.subworkflow_input[f] = sub self._hash = self.rule.__hash__() for wildcard_value in self.wildcards_dict.values(): self._hash ^= wildcard_value.__hash__() def updated(self): job = Job( self.rule, self.dag, wildcards_dict=self.wildcards_dict, targetfile=self.targetfile, ) job.is_updated = True return job def is_valid(self): """Check if job is valid""" # these properties have to work in dry-run as well. Hence we check them here: self.rule.expand_benchmark(self.wildcards_dict) self.rule.expand_log(self.wildcards_dict) def outputs_older_than_script_or_notebook(self): """return output that's older than script, i.e. script has changed""" path = self.rule.script or self.rule.notebook if not path: return assert os.path.exists(path) # to make sure lstat works script_mtime = os.lstat(path).st_mtime for f in self.expanded_output: if f.exists: if not f.is_newer(script_mtime): yield f @property def threads(self): return self.resources._cores @property def params(self): if self._params is None: self._params = self.rule.expand_params( self.wildcards_dict, self.input, self.output, self.resources ) return self._params @property def log(self): if self._log is None: self._log = self.rule.expand_log(self.wildcards_dict) return self._log @property def benchmark(self): if self._benchmark is None: self._benchmark = self.rule.expand_benchmark(self.wildcards_dict) return self._benchmark @property def benchmark_repeats(self): if self.benchmark is not None: return get_flag_value(self.benchmark, "repeat") or 1 @property def group(self): if self._group is None: self._group = self.rule.expand_group(self.wildcards_dict) return self._group @group.setter def group(self, group): self._group = group @property def attempt(self): return self._attempt @attempt.setter def attempt(self, attempt): # reset resources self._resources = None self._attempt = attempt @property def resources(self): if self._resources is None: self._resources = self.rule.expand_resources( self.wildcards_dict, self.input, self.attempt ) return self._resources @property def conda_env_file(self): if self._conda_env_file is None: expanded_env = self.rule.expand_conda_env(self.wildcards_dict) if expanded_env is not None: scheme, _, path, *_ = urlparse(expanded_env) # Normalize 'file:///my/path.yml' to '/my/path.yml' if scheme == "file" or not scheme: self._conda_env_file = path else: self._conda_env_file = expanded_env return self._conda_env_file @property def conda_env(self): if self.conda_env_file: if self._conda_env is None: self._conda_env = self.dag.conda_envs.get( (self.conda_env_file, self.singularity_img_url) ) return self._conda_env return None @property def conda_env_path(self): return self.conda_env.path if self.conda_env else None def archive_conda_env(self): """Archive a conda environment into a custom local channel.""" if self.conda_env_file: return self.conda_env.create_archive() return None @property def needs_singularity(self): return self.singularity_img is not None @property def singularity_img_url(self): return self.rule.singularity_img @property def singularity_img(self): if self.singularity_img_url: return self.dag.singularity_imgs[self.singularity_img_url] return None @property def env_modules(self): return self.rule.env_modules @property def singularity_img_path(self): return self.singularity_img.path if self.singularity_img else None @property def is_shadow(self): return self.rule.shadow_depth is not None @property def priority(self): return self.dag.priority(self) @property def b64id(self): return base64.b64encode( (self.rule.name + "".join(self.output)).encode("utf-8") ).decode("utf-8") @property def inputsize(self): """ Return the size of the input files. Input files need to be present. """ if self._inputsize is None: self._inputsize = sum(f.size for f in self.input) return self._inputsize @property def message(self): """ Return the message for this job. """ try: return ( self.format_wildcards(self.rule.message) if self.rule.message else None ) except AttributeError as ex: raise RuleException(str(ex), rule=self.rule) except KeyError as ex: raise RuleException( "Unknown variable in message " "of shell command: {}".format(str(ex)), rule=self.rule, ) @property def shellcmd(self): """ Return the shell command. """ try: return ( self.format_wildcards(self.rule.shellcmd) if self.rule.shellcmd else None ) except AttributeError as ex: raise RuleException(str(ex), rule=self.rule) except KeyError as ex: raise RuleException( "Unknown variable when printing " "shell command: {}".format(str(ex)), rule=self.rule, ) @property def is_shell(self): return self.rule.shellcmd is not None @property def is_norun(self): return self.rule.norun @property def is_script(self): return self.rule.script is not None @property def is_notebook(self): return self.rule.notebook is not None @property def is_wrapper(self): return self.rule.wrapper is not None @property def is_cwl(self): return self.rule.cwl is not None @property def is_run(self): return not ( self.is_shell or self.is_norun or self.is_script or self.is_wrapper or self.is_cwl ) @property def expanded_output(self): """ Iterate over output files while dynamic output is expanded. """ for f, f_ in zip(self.output, self.rule.output): if f in self.dynamic_output: expansion = self.expand_dynamic(f_) if not expansion: yield f_ for f, _ in expansion: file_to_yield = IOFile(f, self.rule) file_to_yield.clone_flags(f_) yield file_to_yield else: yield f def shadowed_path(self, f): """ Get the shadowed path of IOFile f. """ if not self.shadow_dir: return f f_ = IOFile(os.path.join(self.shadow_dir, f), self.rule) f_.clone_flags(f) return f_ @property def dynamic_wildcards(self): """ Return all wildcard values determined from dynamic output. """ combinations = set() for f, f_ in zip(self.output, self.rule.output): if f in self.dynamic_output: for f, w in self.expand_dynamic(f_): combinations.add(tuple(w.items())) wildcards = defaultdict(list) for combination in combinations: for name, value in combination: wildcards[name].append(value) return wildcards @property def missing_input(self): """ Return missing input files. """ # omit file if it comes from a subworkflow return set( f for f in self.input if not f.exists and not f in self.subworkflow_input ) @property def existing_remote_input(self): files = set() for f in self.input: if f.is_remote: if f.exists_remote: files.add(f) return files @property def existing_remote_output(self): files = set() for f in self.remote_output: if f.exists_remote: files.add(f) return files @property def missing_remote_input(self): return self.remote_input - self.existing_remote_input @property def missing_remote_output(self): return self.remote_output - self.existing_remote_output @property def output_mintime(self): """ Return oldest output file. """ existing = [f.mtime for f in self.expanded_output if f.exists] if self.benchmark and self.benchmark.exists: existing.append(self.benchmark.mtime) if existing: return min(existing) return None @property def output_mintime_local(self): existing = [f.mtime_local for f in self.expanded_output if f.exists] if self.benchmark and self.benchmark.exists: existing.append(self.benchmark.mtime_local) if existing: return min(existing) return None @property def input_maxtime(self): """ Return newest input file. """ existing = [f.mtime for f in self.input if f.exists] if existing: return max(existing) return None def missing_output(self, requested=None): """ Return missing output files. """ files = set() if self.benchmark and (requested is None or self.benchmark in requested): if not self.benchmark.exists: files.add(self.benchmark) for f, f_ in zip(self.output, self.rule.output): if requested is None or f in requested: if f in self.dynamic_output: if not self.expand_dynamic(f_): files.add("{} (dynamic)".format(f_)) elif not f.exists: files.add(f) for f in self.log: if requested and f in requested and not f.exists: files.add(f) return files @property def local_input(self): for f in self.input: if not f.is_remote: yield f @property def unique_input(self): seen = set() for element in filterfalse(seen.__contains__, self.input): seen.add(element) yield element @property def local_output(self): for f in self.output: if not f.is_remote: yield f @property def remote_input(self): for f in self.input: if f.is_remote: yield f @property def remote_output(self): for f in self.output: if f.is_remote: yield f @property def remote_input_newer_than_local(self): files = set() for f in self.remote_input: if (f.exists_remote and f.exists_local) and (f.mtime > f.mtime_local): files.add(f) return files @property def remote_input_older_than_local(self): files = set() for f in self.remote_input: if (f.exists_remote and f.exists_local) and (f.mtime < f.mtime_local): files.add(f) return files @property def remote_output_newer_than_local(self): files = set() for f in self.remote_output: if (f.exists_remote and f.exists_local) and (f.mtime > f.mtime_local): files.add(f) return files @property def remote_output_older_than_local(self): files = set() for f in self.remote_output: if (f.exists_remote and f.exists_local) and (f.mtime < f.mtime_local): files.add(f) return files @property def files_to_download(self): toDownload = set() for f in self.input: if f.is_remote: if (not f.exists_local and f.exists_remote) and ( not self.rule.norun or f.remote_object.keep_local ): toDownload.add(f) toDownload = toDownload | self.remote_input_newer_than_local return toDownload @property def files_to_upload(self): return self.missing_remote_input & self.remote_input_older_than_local @property def existing_output(self): return filter(lambda f: f.exists, self.expanded_output) def check_protected_output(self): protected = list(filter(lambda f: f.protected, self.expanded_output)) if protected: raise ProtectedOutputException(self.rule, protected) def remove_existing_output(self): """Clean up both dynamic and regular output before rules actually run """ if self.dynamic_output: for f, _ in chain(*map(self.expand_dynamic, self.rule.dynamic_output)): os.remove(f) for f, f_ in zip(self.output, self.rule.output): try: # remove_non_empty_dir only applies to directories which aren't # flagged with directory(). f.remove(remove_non_empty_dir=False) except FileNotFoundError: # No file == no problem pass for f in self.log: f.remove(remove_non_empty_dir=False) def download_remote_input(self): for f in self.files_to_download: f.download_from_remote() def prepare(self): """ Prepare execution of job. This includes creation of directories and deletion of previously created dynamic files. Creates a shadow directory for the job if specified. """ self.check_protected_output() unexpected_output = self.dag.reason(self).missing_output.intersection( self.existing_output ) if unexpected_output: logger.warning( "Warning: the following output files of rule {} were not " "present when the DAG was created:\n{}".format( self.rule, unexpected_output ) ) self.remove_existing_output() for f, f_ in zip(self.output, self.rule.output): f.prepare() self.download_remote_input() for f in self.log: f.prepare() if self.benchmark: self.benchmark.prepare() if not self.is_shadow: return # Create shadow directory structure self.shadow_dir = tempfile.mkdtemp( dir=self.rule.workflow.persistence.shadow_path ) cwd = os.getcwd() if self.rule.shadow_depth == "minimal": # Re-create the directory structure in the shadow directory for (f, d) in set( [ (item, os.path.dirname(item)) for sublist in [self.input, self.output, self.log] if sublist is not None for item in sublist ] ): if d and not os.path.isabs(d): rel_path = os.path.relpath(d) # Only create subdirectories if not rel_path.split(os.path.sep)[0] == "..": os.makedirs( os.path.join(self.shadow_dir, rel_path), exist_ok=True ) else: raise RuleException( "The following file name references a parent directory relative to your workdir.\n" 'This isn\'t supported for shadow: "minimal". Consider using an absolute path instead.\n{}'.format( f ), rule=self.rule, ) # Symlink the input files for rel_path in set( [os.path.relpath(f) for f in self.input if not os.path.isabs(f)] ): link = os.path.join(self.shadow_dir, rel_path) original = os.path.relpath(rel_path, os.path.dirname(link)) os.symlink(original, link) # Shallow simply symlink everything in the working directory. elif self.rule.shadow_depth == "shallow": for source in os.listdir(cwd): link = os.path.join(self.shadow_dir, source) os.symlink(os.path.abspath(source), link) elif self.rule.shadow_depth == "full": snakemake_dir = os.path.join(cwd, ".snakemake") for dirpath, dirnames, filenames in os.walk(cwd): # Must exclude .snakemake and its children to avoid infinite # loop of symlinks. if os.path.commonprefix([snakemake_dir, dirpath]) == snakemake_dir: continue for dirname in dirnames: if dirname == ".snakemake": continue relative_source = os.path.relpath(os.path.join(dirpath, dirname)) shadow = os.path.join(self.shadow_dir, relative_source) os.mkdir(shadow) for filename in filenames: source = os.path.join(dirpath, filename) relative_source = os.path.relpath(source) link = os.path.join(self.shadow_dir, relative_source) os.symlink(source, link) def close_remote(self): for f in self.input + self.output: if f.is_remote: f.remote_object.close() def cleanup(self): """ Cleanup output files. """ to_remove = [f for f in self.expanded_output if f.exists] to_remove.extend([f for f in self.remote_input if f.exists_local]) to_remove.extend( [ f for f in self.remote_output if ( f.exists_remote if (f.is_remote and f.should_stay_on_remote) else f.exists_local ) ] ) if to_remove: logger.info( "Removing output files of failed job {}" " since they might be corrupted:\n{}".format(self, ", ".join(to_remove)) ) for f in to_remove: f.remove() self.rmdir_empty_remote_dirs() @property def empty_remote_dirs(self): for f in set(self.output) | set(self.input): if f.is_remote and not f.should_stay_on_remote: if os.path.exists(os.path.dirname(f)) and not len( os.listdir(os.path.dirname(f)) ): yield os.path.dirname(f) def rmdir_empty_remote_dirs(self): for d in self.empty_remote_dirs: try: os.removedirs(d) except: pass # it's ok if we can't remove the leaf def format_wildcards(self, string, **variables): """ Format a string with variables from the job. """ _variables = dict() _variables.update(self.rule.workflow.globals) _variables.update( dict( input=self.input, output=self.output, params=self.params, wildcards=self._format_wildcards, threads=self.threads, resources=self.resources, log=self.log, jobid=self.jobid, version=self.rule.version, name=self.name, rule=self.rule.name, rulename=self.rule.name, bench_iteration=None, ) ) _variables.update(variables) try: return format(string, **_variables) except NameError as ex: raise RuleException("NameError: " + str(ex), rule=self.rule) except IndexError as ex: raise RuleException("IndexError: " + str(ex), rule=self.rule) def properties(self, omit_resources=["_cores", "_nodes"], **aux_properties): resources = { name: res for name, res in self.resources.items() if name not in omit_resources } params = {name: value for name, value in self.params.items()} properties = { "type": "single", "rule": self.rule.name, "local": self.is_local, "input": self.input, "output": self.output, "wildcards": self.wildcards_dict, "params": params, "log": self.log, "threads": self.threads, "resources": resources, "jobid": self.dag.jobid(self), } properties.update(aux_properties) try: return json.dumps(properties) except TypeError: del properties["params"] return json.dumps(properties) @property def is_local(self): return self.dag.workflow.is_local(self.rule) def __repr__(self): return self.rule.name def __eq__(self, other): if other is None: return False return ( self.rule == other.rule and (self.wildcards_dict == other.wildcards_dict) and (self.input == other.input) ) def __lt__(self, other): return self.rule.__lt__(other.rule) def __gt__(self, other): return self.rule.__gt__(other.rule) def __hash__(self): return self._hash def expand_dynamic(self, pattern): """ Expand dynamic files. """ return list( listfiles(pattern, restriction=self.wildcards, omit_value=DYNAMIC_FILL) ) def is_group(self): return False def log_info(self, skip_dynamic=False, indent=False, printshellcmd=True): # skip dynamic jobs that will be "executed" only in dryrun mode if skip_dynamic and self.dag.dynamic(self): return priority = self.priority logger.job_info( jobid=self.dag.jobid(self), msg=self.message, name=self.rule.name, local=self.dag.workflow.is_local(self.rule), input=list(format_files(self, self.input, self.dynamic_input)), output=list(format_files(self, self.output, self.dynamic_output)), log=list(self.log), benchmark=self.benchmark, wildcards=self.wildcards_dict, reason=str(self.dag.reason(self)), resources=self.resources, priority="highest" if priority == Job.HIGHEST_PRIORITY else priority, threads=self.threads, indent=indent, is_checkpoint=self.rule.is_checkpoint, printshellcmd=printshellcmd, ) logger.shellcmd(self.shellcmd, indent=indent) if self.dynamic_output: logger.info( "Subsequent jobs will be added dynamically " "depending on the output of this job", indent=True, ) def log_error(self, msg=None, indent=False, **kwargs): logger.job_error( name=self.rule.name, jobid=self.dag.jobid(self), output=list(format_files(self, self.output, self.dynamic_output)), log=list(self.log), conda_env=self.conda_env.path if self.conda_env else None, aux=kwargs, indent=indent, shellcmd=self.shellcmd, ) if msg is not None: logger.error(msg) def register(self): self.dag.workflow.persistence.started(self) def get_wait_for_files(self): wait_for_files = [] wait_for_files.extend(self.local_input) wait_for_files.extend( f for f in self.remote_input if not f.should_stay_on_remote ) if self.shadow_dir: wait_for_files.append(self.shadow_dir) if self.dag.workflow.use_conda and self.conda_env: wait_for_files.append(self.conda_env_path) return wait_for_files @property def jobid(self): return self.dag.jobid(self) def postprocess( self, upload_remote=True, handle_log=True, handle_touch=True, handle_temp=True, error=False, ignore_missing_output=False, assume_shared_fs=True, latency_wait=None, ): if assume_shared_fs: if not error and handle_touch: self.dag.handle_touch(self) if handle_log: self.dag.handle_log(self) if not error: self.dag.check_and_touch_output( self, wait=latency_wait, ignore_missing_output=ignore_missing_output ) self.dag.unshadow_output(self, only_log=error) if not error: self.dag.handle_remote(self, upload=upload_remote) self.dag.handle_protected(self) self.close_remote() else: if not error: self.dag.check_and_touch_output( self, wait=latency_wait, no_touch=True, force_stay_on_remote=True ) if not error: try: self.dag.workflow.persistence.finished(self) except IOError as e: logger.warning( "Error recording metadata for finished job " "({}). Please ensure write permissions for the " "directory {}".format(e, self.dag.workflow.persistence.path) ) if handle_temp: # temp handling has to happen after calling finished(), # because we need to access temp output files to record # start and end times. self.dag.handle_temp(self) @property def name(self): return self.rule.name @property def priority(self): return self.dag.priority(self) @property def products(self): products = list(self.output) if self.benchmark: products.append(self.benchmark) products.extend(self.log) return products def get_targets(self): return self.targetfile or [self.rule.name] @property def is_branched(self): return self.rule.is_branched @property def rules(self): return [self.rule.name] @property def restart_times(self): return self.rule.restart_times @property def is_checkpoint(self): return self.rule.is_checkpoint def __len__(self): return 1 class GroupJob(AbstractJob): __slots__ = [ "groupid", "jobs", "_resources", "_input", "_output", "_log", "_inputsize", "_all_products", "_attempt", "toposorted", ] def __init__(self, id, jobs): self.groupid = id self.jobs = frozenset(jobs) self.toposorted = None self._resources = None self._input = None self._output = None self._log = None self._inputsize = None self._all_products = None self._attempt = self.dag.workflow.attempt @property def dag(self): return next(iter(self.jobs)).dag def merge(self, other): assert other.groupid == self.groupid self.jobs = self.jobs | other.jobs def finalize(self): from toposort import toposort if self.toposorted is None: dag = { job: {dep for dep in self.dag.dependencies[job] if dep in self.jobs} for job in self.jobs } self.toposorted = list(toposort(dag)) @property def all_products(self): if self._all_products is None: self._all_products = set(f for job in self.jobs for f in job.products) return self._all_products def __iter__(self): if self.toposorted is None: yield from self.jobs else: yield from chain.from_iterable(self.toposorted) def __repr__(self): return "JobGroup({},{})".format(self.groupid, repr(self.jobs)) def __contains__(self, job): return job in self.jobs def is_group(self): return True @property def is_checkpoint(self): return any(job.is_checkpoint for job in self.jobs) @property def is_updated(self): return any(job.is_updated for job in self.jobs) def log_info(self, skip_dynamic=False): logger.group_info(groupid=self.groupid) for job in sorted(self.jobs, key=lambda j: j.rule.name): job.log_info(skip_dynamic, indent=True) def log_error(self, msg=None, **kwargs): logger.group_error(groupid=self.groupid) for job in self.jobs: job.log_error(msg=msg, indent=True, **kwargs) def register(self): for job in self.jobs: job.register() def remove_existing_output(self): for job in self.jobs: job.remove_existing_output() def download_remote_input(self): for job in self.jobs: job.download_remote_input() def get_wait_for_files(self): local_input = [ f for job in self.jobs for f in job.local_input if f not in self.all_products ] remote_input = [ f for job in self.jobs for f in job.remote_input if f not in self.all_products ] wait_for_files = [] wait_for_files.extend(local_input) wait_for_files.extend(f for f in remote_input if not f.should_stay_on_remote) for job in self.jobs: if job.shadow_dir: wait_for_files.append(job.shadow_dir) if self.dag.workflow.use_conda and job.conda_env: wait_for_files.append(job.conda_env_path) return wait_for_files @property def resources(self): if self._resources is None: self._resources = defaultdict(int) pipe_group = any( [any([is_flagged(o, "pipe") for o in job.output]) for job in self.jobs] ) # iterate over siblings that can be executed in parallel for siblings in self.toposorted: sibling_resources = defaultdict(int) for job in siblings: try: job_resources = job.resources except FileNotFoundError: # Skip job if resource evaluation leads to a file not found error. # This will be caused by an inner job, which needs files created by the same group. # All we can do is to ignore such jobs for now. continue for res, value in job_resources.items(): if res != "_nodes": sibling_resources[res] += value for res, value in sibling_resources.items(): if res != "_nodes": if self.dag.workflow.run_local or pipe_group: # in case of local execution, this must be a # group of jobs that are connected with pipes # and have to run simultaneously self._resources[res] += value else: # take the maximum with previous values self._resources[res] = max( self._resources.get(res, 0), value ) return Resources(fromdict=self._resources) @property def input(self): if self._input is None: self._input = [ f for job in self.jobs for f in job.input if f not in self.all_products ] return self._input @property def output(self): all_input = set(f for job in self.jobs for f in job.input) if self._output is None: self._output = [ f for job in self.jobs for f in job.output if f not in all_input ] return self._output @property def log(self): if self._log is None: self._log = [f for job in self.jobs for f in job.log] return self._log @property def products(self): all_input = set(f for job in self.jobs for f in job.input) return [f for job in self.jobs for f in job.products if f not in all_input] def properties(self, omit_resources=["_cores", "_nodes"], **aux_properties): resources = { name: res for name, res in self.resources.items() if name not in omit_resources } properties = { "type": "group", "groupid": self.groupid, "local": self.is_local, "input": self.input, "output": self.output, "threads": self.threads, "resources": resources, "jobid": self.jobid, } properties.update(aux_properties) return json.dumps(properties) @property def jobid(self): return str(get_uuid(",".join(str(job.jobid) for job in self.jobs))) def cleanup(self): for job in self.jobs: job.cleanup() def postprocess(self, error=False, **kwargs): for job in self.jobs: job.postprocess(handle_temp=False, error=error, **kwargs) # Handle temp after per-job postprocess. # This is necessary because group jobs are not topologically sorted, # and we might otherwise delete a temp input file before it has been # postprocessed by the outputting job in the same group. if not error: for job in self.jobs: self.dag.handle_temp(job) # remove all pipe outputs since all jobs of this group are done and the # pipes are no longer needed for job in self.jobs: for f in job.output: if is_flagged(f, "pipe"): f.remove() @property def name(self): return str(self.groupid) def check_protected_output(self): for job in self.jobs: job.check_protected_output() @property def dynamic_input(self): return [ f for job in self.jobs for f in job.dynamic_input if f not in self.all_products ] @property def inputsize(self): if self._inputsize is None: self._inputsize = sum(f.size for f in self.input) return self._inputsize @property def priority(self): return max(self.dag.priority(job) for job in self.jobs) @property def is_local(self): return all(job.is_local for job in self.jobs) def format_wildcards(self, string, **variables): """ Format a string with variables from the job. """ _variables = dict() _variables.update(self.dag.workflow.globals) _variables.update( dict( input=self.input, output=self.output, threads=self.threads, jobid=self.jobid, name=self.name, rule="GROUP", rulename="GROUP", resources=self.resources, ) ) _variables.update(variables) try: return format(string, **_variables) except NameError as ex: raise WorkflowError( "NameError with group job {}: {}".format(self.jobid, str(ex)) ) except IndexError as ex: raise WorkflowError( "IndexError with group job {}: {}".format(self.jobid, str(ex)) ) @property def threads(self): return self.resources["_cores"] def get_targets(self): # jobs without output are targeted by rule name targets = [job.rule.name for job in self.jobs if not job.products] targets.extend(self.products) return targets @property def attempt(self): return self._attempt @attempt.setter def attempt(self, attempt): # reset resources self._resources = None self._attempt = attempt @property def is_branched(self): return any(job.is_branched for job in self.jobs) @property def needs_singularity(self): return any(job.needs_singularity for job in self.jobs) @property def rules(self): return [job.rule.name for job in self.jobs] @property def expanded_output(self): """Yields the entire expanded output of all jobs""" for job in self.jobs: yield from job.expanded_output @property def restart_times(self): return max(job.restart_times for job in self.jobs) def __len__(self): return len(self.jobs) def __hash__(self): return hash(self.jobs) def __eq__(self, other): if other.is_group(): return self.jobs == other.jobs else: return False class Reason: __slots__ = [ "_updated_input", "_updated_input_run", "_missing_output", "_incomplete_output", "forced", "noio", "nooutput", "derived", ] def __init__(self): self._updated_input = None self._updated_input_run = None self._missing_output = None self._incomplete_output = None self.forced = False self.noio = False self.nooutput = False self.derived = True @lazy_property def updated_input(self): return set() @lazy_property def updated_input_run(self): return set() @lazy_property def missing_output(self): return set() @lazy_property def incomplete_output(self): return set() def __str__(self): s = list() if self.forced: s.append("Forced execution") else: if self.noio: s.append( "Rules with neither input nor " "output files are always executed." ) elif self.nooutput: s.append( "Rules with a run or shell declaration but no output " "are always executed." ) else: if self._missing_output: s.append( "Missing output files: {}".format( ", ".join(self.missing_output) ) ) if self._incomplete_output: s.append( "Incomplete output files: {}".format( ", ".join(self.incomplete_output) ) ) if self._updated_input: updated_input = self.updated_input - self.updated_input_run s.append("Updated input files: {}".format(", ".join(updated_input))) if self._updated_input_run: s.append( "Input files updated by another job: {}".format( ", ".join(self.updated_input_run) ) ) s = "; ".join(s) return s def __bool__(self): return bool( self.updated_input or self.missing_output or self.forced or self.updated_input_run or self.noio or self.nooutput ) snakemake-5.10.0/snakemake/jobscript.sh000066400000000000000000000000611361131222100200130ustar00rootroot00000000000000#!/bin/sh # properties = {properties} {exec_job} snakemake-5.10.0/snakemake/logging.py000066400000000000000000000376251361131222100175000ustar00rootroot00000000000000__author__ = "Johannes Köster" __copyright__ = "Copyright 2015-2019, Johannes Köster" __email__ = "koester@jimmy.harvard.edu" __license__ = "MIT" import logging as _logging import platform import time import datetime import sys import os import json import threading import tempfile from functools import partial import inspect from snakemake.common import DYNAMIC_FILL from snakemake.common import Mode class ColorizingStreamHandler(_logging.StreamHandler): BLACK, RED, GREEN, YELLOW, BLUE, MAGENTA, CYAN, WHITE = range(8) RESET_SEQ = "\033[0m" COLOR_SEQ = "\033[%dm" BOLD_SEQ = "\033[1m" colors = { "WARNING": YELLOW, "INFO": GREEN, "DEBUG": BLUE, "CRITICAL": RED, "ERROR": RED, } def __init__( self, nocolor=False, stream=sys.stderr, use_threads=False, mode=Mode.default ): super().__init__(stream=stream) self._output_lock = threading.Lock() self.nocolor = nocolor or not self.can_color_tty(mode) def can_color_tty(self, mode): if "TERM" in os.environ and os.environ["TERM"] == "dumb": return False if mode == Mode.subprocess: return True return self.is_tty and not platform.system() == "Windows" @property def is_tty(self): isatty = getattr(self.stream, "isatty", None) return isatty and isatty() def emit(self, record): with self._output_lock: try: self.format(record) # add the message to the record self.stream.write(self.decorate(record)) self.stream.write(getattr(self, "terminator", "\n")) self.flush() except BrokenPipeError as e: raise e except (KeyboardInterrupt, SystemExit): # ignore any exceptions in these cases as any relevant messages have been printed before pass except Exception as e: self.handleError(record) def decorate(self, record): message = record.message message = [message] if not self.nocolor and record.levelname in self.colors: message.insert(0, self.COLOR_SEQ % (30 + self.colors[record.levelname])) message.append(self.RESET_SEQ) return "".join(message) class SlackLogger: def __init__(self): from slacker import Slacker self.token = os.getenv("SLACK_TOKEN") if not self.token: print( "The use of slack logging requires the user to set a user specific slack legacy token to the SLACK_TOKEN environment variable. Set this variable by 'export SLACK_TOKEN=your_token'. To generate your token please visit https://api.slack.com/custom-integrations/legacy-tokens." ) exit(-1) self.slack = Slacker(self.token) # Check for success try: auth = self.slack.auth.test().body except Exception: print( "Slack connection failed. Please compare your provided slack token exported in the SLACK_TOKEN environment variable with your online token at https://api.slack.com/custom-integrations/legacy-tokens. A different token can be set up by 'export SLACK_TOKEN=your_token'." ) exit(-1) self.own_id = auth["user_id"] self.error_occured = False def log_handler(self, msg): if msg["level"] == "error" and not self.error_occured: self.slack.chat.post_message( self.own_id, text="At least one error occured.", username="snakemake" ) self.error_occured = True if msg["level"] == "progress" and msg["done"] == msg["total"]: # workflow finished self.slack.chat.post_message( self.own_id, text="Workflow complete.", username="snakemake" ) class Logger: def __init__(self): self.logger = _logging.getLogger(__name__) self.log_handler = [self.text_handler] self.stream_handler = None self.printshellcmds = False self.printreason = False self.debug_dag = False self.quiet = False self.logfile = None self.last_msg_was_job_info = False self.mode = Mode.default self.show_failed_logs = False self.logfile_handler = None def setup_logfile(self): if self.mode == Mode.default: os.makedirs(os.path.join(".snakemake", "log"), exist_ok=True) self.logfile = os.path.abspath( os.path.join( ".snakemake", "log", datetime.datetime.now().isoformat().replace(":", "") + ".snakemake.log", ) ) self.logfile_handler = _logging.FileHandler(self.logfile) self.logger.addHandler(self.logfile_handler) def cleanup(self): if self.mode == Mode.default and self.logfile_handler is not None: self.logger.removeHandler(self.logfile_handler) self.logfile_handler.close() self.log_handler = [self.text_handler] def get_logfile(self): if self.logfile is not None: self.logfile_handler.flush() return self.logfile def remove_logfile(self): if self.mode == Mode.default: self.logfile_handler.close() os.remove(self.logfile) def handler(self, msg): for handler in self.log_handler: handler(msg) def set_stream_handler(self, stream_handler): if self.stream_handler is not None: self.logger.removeHandler(self.stream_handler) self.stream_handler = stream_handler self.logger.addHandler(stream_handler) def set_level(self, level): self.logger.setLevel(level) def logfile_hint(self): if self.mode == Mode.default: logfile = self.get_logfile() self.info("Complete log: {}".format(logfile)) def location(self, msg): callerframerecord = inspect.stack()[1] frame = callerframerecord[0] info = inspect.getframeinfo(frame) self.debug( "{}: {info.filename}, {info.function}, {info.lineno}".format(msg, info=info) ) def info(self, msg, indent=False): self.handler(dict(level="info", msg=msg, indent=indent)) def warning(self, msg): self.handler(dict(level="warning", msg=msg)) def debug(self, msg): self.handler(dict(level="debug", msg=msg)) def error(self, msg): self.handler(dict(level="error", msg=msg)) def progress(self, done=None, total=None): self.handler(dict(level="progress", done=done, total=total)) def resources_info(self, msg): self.handler(dict(level="resources_info", msg=msg)) def run_info(self, msg): self.handler(dict(level="run_info", msg=msg)) def group_info(self, **msg): msg["level"] = "group_info" self.handler(msg) def job_info(self, **msg): msg["level"] = "job_info" self.handler(msg) def job_error(self, **msg): msg["level"] = "job_error" self.handler(msg) def group_error(self, **msg): msg["level"] = "group_error" self.handler(msg) def dag_debug(self, msg): self.handler(dict(level="dag_debug", **msg)) def shellcmd(self, msg, indent=False): if msg is not None: msg = dict(level="shellcmd", msg=msg) msg["indent"] = indent self.handler(msg) def job_finished(self, **msg): msg["level"] = "job_finished" self.handler(msg) def rule_info(self, **msg): msg["level"] = "rule_info" self.handler(msg) def d3dag(self, **msg): msg["level"] = "d3dag" self.handler(msg) def text_handler(self, msg): """The default snakemake log handler. Prints the output to the console. Args: msg (dict): the log message dictionary """ def job_info(msg): def format_item(item, omit=None, valueformat=str): value = msg[item] if value != omit: return " {}: {}".format(item, valueformat(value)) yield "{}{} {}:".format( "local" if msg["local"] else "", "checkpoint" if msg["is_checkpoint"] else "rule", msg["name"], ) for item in ["input", "output", "log"]: fmt = format_item(item, omit=[], valueformat=", ".join) if fmt != None: yield fmt singleitems = ["jobid", "benchmark"] if self.printreason: singleitems.append("reason") for item in singleitems: fmt = format_item(item, omit=None) if fmt != None: yield fmt wildcards = format_wildcards(msg["wildcards"]) if wildcards: yield " wildcards: " + wildcards for item, omit in zip("priority threads".split(), [0, 1]): fmt = format_item(item, omit=omit) if fmt != None: yield fmt resources = format_resources(msg["resources"]) if resources: yield " resources: " + resources def indent(item): if msg.get("indent"): return " " + item else: return item def timestamp(): self.logger.info(indent("[{}]".format(time.asctime()))) level = msg["level"] if level == "job_info" and not self.quiet: if not self.last_msg_was_job_info: self.logger.info("") timestamp() if msg["msg"] is not None: self.logger.info(indent("Job {}: {}".format(msg["jobid"], msg["msg"]))) if self.printreason: self.logger.info(indent("Reason: {}".format(msg["reason"]))) else: self.logger.info("\n".join(map(indent, job_info(msg)))) if msg["is_checkpoint"]: self.logger.warning( indent("Downstream jobs will be updated " "after completion.") ) self.logger.info("") self.last_msg_was_job_info = True elif level == "group_info" and not self.quiet: timestamp() if not self.last_msg_was_job_info: self.logger.info("") self.logger.info( "group job {} (jobs in lexicogr. order):".format(msg["groupid"]) ) elif level == "job_error": timestamp() self.logger.error(indent("Error in rule {}:".format(msg["name"]))) self.logger.error(indent(" jobid: {}".format(msg["jobid"]))) if msg["output"]: self.logger.error( indent(" output: {}".format(", ".join(msg["output"]))) ) if msg["log"]: self.logger.error( indent( " log: {} (check log file(s) for error message)".format( ", ".join(msg["log"]) ) ) ) if msg["conda_env"]: self.logger.error(indent(" conda-env: {}".format(msg["conda_env"]))) if msg["shellcmd"]: self.logger.error( indent( " shell:\n {}\n (one of the commands exited with non-zero exit code; note that snakemake uses bash strict mode!)".format( msg["shellcmd"] ) ) ) for item in msg["aux"].items(): self.logger.error(indent(" {}: {}".format(*item))) if self.show_failed_logs and msg["log"]: for f in msg["log"]: try: self.logger.error("Logfile {}:\n{}".format(f, open(f).read())) except FileNotFoundError: self.logger.error("Logfile {} not found.".format(f)) self.logger.error("") elif level == "group_error": timestamp() self.logger.error("Error in group job {}:".format(msg["groupid"])) else: if level == "info" and not self.quiet: self.logger.warning(msg["msg"]) if level == "warning": self.logger.warning(msg["msg"]) elif level == "error": self.logger.error(msg["msg"]) elif level == "debug": self.logger.debug(msg["msg"]) elif level == "resources_info" and not self.quiet: self.logger.warning(msg["msg"]) elif level == "run_info": self.logger.warning(msg["msg"]) elif level == "progress" and not self.quiet: done = msg["done"] total = msg["total"] p = done / total percent_fmt = ("{:.2%}" if p < 0.01 else "{:.0%}").format(p) self.logger.info( "{} of {} steps ({}) done".format(done, total, percent_fmt) ) elif level == "shellcmd": if self.printshellcmds: self.logger.warning(indent(msg["msg"])) elif level == "job_finished" and not self.quiet: timestamp() self.logger.info("Finished job {}.".format(msg["jobid"])) pass elif level == "rule_info": self.logger.info(msg["name"]) if msg["docstring"]: self.logger.info(" " + msg["docstring"]) elif level == "d3dag": print(json.dumps({"nodes": msg["nodes"], "links": msg["edges"]})) elif level == "dag_debug": if self.debug_dag: job = msg["job"] self.logger.warning( "{status} job {name}\n\twildcards: {wc}".format( status=msg["status"], name=job.rule.name, wc=format_wildcards(job.wildcards), ) ) self.last_msg_was_job_info = False def format_dict(dict_like, omit_keys=[], omit_values=[]): from snakemake.io import Namedlist if isinstance(dict_like, Namedlist): items = dict_like.items() elif isinstance(dict_like, dict): items = dict_like.items() else: raise ValueError( "bug: format_dict applied to something neither a dict nor a Namedlist" ) return ", ".join( "{}={}".format(name, str(value)) for name, value in items if name not in omit_keys and value not in omit_values ) format_resources = partial(format_dict, omit_keys={"_cores", "_nodes"}) format_wildcards = partial(format_dict, omit_values={DYNAMIC_FILL}) def format_resource_names(resources, omit_resources="_cores _nodes".split()): return ", ".join(name for name in resources if name not in omit_resources) logger = Logger() def setup_logger( handler=[], quiet=False, printshellcmds=False, printreason=False, debug_dag=False, nocolor=False, stdout=False, debug=False, use_threads=False, mode=Mode.default, show_failed_logs=False, ): logger.log_handler.extend(handler) # console output only if no custom logger was specified stream_handler = ColorizingStreamHandler( nocolor=nocolor, stream=sys.stdout if stdout else sys.stderr, use_threads=use_threads, mode=mode, ) logger.set_stream_handler(stream_handler) logger.set_level(_logging.DEBUG if debug else _logging.INFO) logger.quiet = quiet logger.printshellcmds = printshellcmds logger.printreason = printreason logger.debug_dag = debug_dag logger.mode = mode logger.show_failed_logs = show_failed_logs snakemake-5.10.0/snakemake/notebook.py000066400000000000000000000074411361131222100176630ustar00rootroot00000000000000import os from snakemake.exceptions import WorkflowError from snakemake.shell import shell from snakemake.script import get_source, ScriptBase, PythonScript, RScript class JupyterNotebook(ScriptBase): def write_script(self, preamble, fd): import nbformat nb = nbformat.reads(self.source, as_version=4) # nbformat.NO_CONVERT preamble_cell = nbformat.v4.new_code_cell(preamble) nb["cells"].insert(0, preamble_cell) fd.write(nbformat.writes(nb).encode()) def execute_script(self, fname): fname_out = self.log.get("notebook", None) if fname_out is None: output_parameter = "" else: fname_out = os.path.join(os.getcwd(), fname_out) output_parameter = "--output {fname_out:q}" cmd_tmp = "jupyter-nbconvert --execute {output_parameter} --to notebook --ExecutePreprocessor.timeout=-1 {{fname:q}}".format( output_parameter=output_parameter ) self._execute_cmd(cmd_tmp, fname_out=fname_out, fname=fname) class PythonJupyterNotebook(JupyterNotebook): def get_preamble(self): preamble_addendum = "import os; os.chdir('{cwd}');".format(cwd=os.getcwd()) return PythonScript.generate_preamble( self.path, self.source, self.basedir, self.input, self.output, self.params, self.wildcards, self.threads, self.resources, self.log, self.config, self.rulename, self.conda_env, self.singularity_img, self.singularity_args, self.env_modules, self.bench_record, self.jobid, self.bench_iteration, self.cleanup_scripts, self.shadow_dir, preamble_addendum=preamble_addendum, ) class RJupyterNotebook(JupyterNotebook): def get_preamble(self): preamble_addendum = "setwd('{cwd}');".format(cwd=os.getcwd()) return RScript.generate_preamble( self.path, self.source, self.basedir, self.input, self.output, self.params, self.wildcards, self.threads, self.resources, self.log, self.config, self.rulename, self.conda_env, self.singularity_img, self.singularity_args, self.env_modules, self.bench_record, self.jobid, self.bench_iteration, self.cleanup_scripts, self.shadow_dir, preamble_addendum=preamble_addendum, ) def notebook( path, basedir, input, output, params, wildcards, threads, resources, log, config, rulename, conda_env, singularity_img, singularity_args, env_modules, bench_record, jobid, bench_iteration, cleanup_scripts, shadow_dir, ): """ Load a script from the given basedir + path and execute it. """ path, source, language = get_source(path, basedir) ExecClass = { "jupyter_python": PythonJupyterNotebook, "jupyter_r": RJupyterNotebook, }.get(language, None) if ExecClass is None: raise ValueError("Unsupported notebook: Expecting Jupyter Notebook (.ipynb).") executor = ExecClass( path, source, basedir, input, output, params, wildcards, threads, resources, log, config, rulename, conda_env, singularity_img, singularity_args, env_modules, bench_record, jobid, bench_iteration, cleanup_scripts, shadow_dir, ) executor.evaluate() snakemake-5.10.0/snakemake/output_index.py000066400000000000000000000030761361131222100205720ustar00rootroot00000000000000__author__ = "Johannes Köster" __copyright__ = "Copyright 2018-2019, Johannes Köster" __email__ = "johannes.koester@protonmail.com" __license__ = "MIT" from itertools import chain from snakemake.io import _IOFile class OutputIndex: def __init__(self, rules): import datrie def prefixes(rule): return (str(o.constant_prefix()) for o in rule.products) def reverse_suffixes(rule): return (str(o.constant_suffix())[::-1] for o in rule.products) def calc_trie(subpatterns): t = datrie.Trie("".join(p for rule in rules for p in subpatterns(rule))) empty = list() for rule in rules: has_empty = False for p in subpatterns(rule): if not p: has_empty = True if p not in t: t[p] = [rule] else: t[p].append(rule) if has_empty: empty.append(rule) return t, empty self.prefix_trie, self.empty_prefix = calc_trie(prefixes) self.suffix_trie, self.empty_suffix = calc_trie(reverse_suffixes) def match(self, targetfile): def match_pattern(pattern, trie, empty): return chain(chain.from_iterable(trie.iter_prefix_values(pattern)), empty) f = str(targetfile) hits = set(match_pattern(f, self.prefix_trie, self.empty_prefix)) return hits.intersection( match_pattern(f[::-1], self.suffix_trie, self.empty_suffix) ) snakemake-5.10.0/snakemake/parser.py000066400000000000000000000534771361131222100173510ustar00rootroot00000000000000__author__ = "Johannes Köster" __copyright__ = "Copyright 2015-2019, Johannes Köster" __email__ = "koester@jimmy.harvard.edu" __license__ = "MIT" import tokenize import textwrap import os from urllib.error import HTTPError, URLError, ContentTooShortError import urllib.request from io import TextIOWrapper from snakemake.exceptions import WorkflowError dd = textwrap.dedent INDENT = "\t" def is_newline(token, newline_tokens=set((tokenize.NEWLINE, tokenize.NL))): return token.type in newline_tokens def is_indent(token): return token.type == tokenize.INDENT def is_dedent(token): return token.type == tokenize.DEDENT def is_op(token): return token.type == tokenize.OP def is_greater(token): return is_op(token) and token.string == ">" def is_comma(token): return is_op(token) and token.string == "," def is_name(token): return token.type == tokenize.NAME def is_colon(token): return is_op(token) and token.string == ":" def is_comment(token): return token.type == tokenize.COMMENT def is_string(token): return token.type == tokenize.STRING def is_eof(token): return token.type == tokenize.ENDMARKER def lineno(token): return token.start[0] class StopAutomaton(Exception): def __init__(self, token): self.token = token class TokenAutomaton: subautomata = dict() def __init__(self, snakefile, base_indent=0, dedent=0, root=True): self.root = root self.snakefile = snakefile self.state = None self.base_indent = base_indent self.line = 0 self.indent = 0 self.was_indented = False self.lasttoken = None self._dedent = dedent @property def dedent(self): return self._dedent @property def effective_indent(self): return self.base_indent + self.indent - self.dedent def indentation(self, token): if is_indent(token) or is_dedent(token): self.indent = token.end[1] - self.base_indent self.was_indented |= self.indent > 0 def consume(self): for token in self.snakefile: self.indentation(token) try: for t, orig in self.state(token): if self.lasttoken == "\n" and not t.isspace(): yield INDENT * self.effective_indent, orig yield t, orig self.lasttoken = t except tokenize.TokenError as e: self.error( str(e).split(",")[0].strip("()''"), token ) # TODO the inferred line number seems to be wrong sometimes def error(self, msg, token): raise SyntaxError(msg, (self.snakefile.path, lineno(token), None, None)) def subautomaton(self, automaton, *args, **kwargs): return self.subautomata[automaton]( self.snakefile, *args, base_indent=self.base_indent + self.indent, dedent=self.dedent, root=False, **kwargs ) class KeywordState(TokenAutomaton): prefix = "" def __init__(self, snakefile, base_indent=0, dedent=0, root=True): super().__init__(snakefile, base_indent=base_indent, dedent=dedent, root=root) self.line = 0 self.state = self.colon @property def keyword(self): return self.__class__.__name__.lower()[len(self.prefix) :] def end(self): yield ")" def decorate_end(self, token): for t in self.end(): yield t, token def colon(self, token): if is_colon(token): self.state = self.block for t in self.start(): yield t, token else: self.error("Colon expected after keyword {}.".format(self.keyword), token) def is_block_end(self, token): return (self.line and self.indent <= 0) or is_eof(token) def block(self, token): if self.lasttoken == "\n" and is_comment(token): # ignore lines containing only comments self.line -= 1 if self.is_block_end(token): for t, token_ in self.decorate_end(token): yield t, token_ yield "\n", token raise StopAutomaton(token) if is_newline(token): self.line += 1 yield token.string, token elif not (is_indent(token) or is_dedent(token)): if is_comment(token): yield token.string, token else: for t in self.block_content(token): yield t def yield_indent(self, token): return token.string, token def block_content(self, token): yield token.string, token class GlobalKeywordState(KeywordState): def start(self): yield "workflow.{keyword}(".format(keyword=self.keyword) class DecoratorKeywordState(KeywordState): decorator = None args = list() def start(self): yield "@workflow.{}".format(self.decorator) yield "\n" yield "def __{}({}):".format(self.decorator, ", ".join(self.args)) def end(self): yield "" class RuleKeywordState(KeywordState): def __init__(self, snakefile, base_indent=0, dedent=0, root=True, rulename=None): super().__init__(snakefile, base_indent=base_indent, dedent=dedent, root=root) self.rulename = rulename def start(self): yield "\n" yield "@workflow.{keyword}(".format(keyword=self.keyword) class SubworkflowKeywordState(KeywordState): prefix = "Subworkflow" def start(self): yield ", {keyword}=".format(keyword=self.keyword) def end(self): # no end needed return list() # Global keyword states class Include(GlobalKeywordState): pass class Workdir(GlobalKeywordState): pass class Configfile(GlobalKeywordState): pass class Report(GlobalKeywordState): pass class Ruleorder(GlobalKeywordState): def block_content(self, token): if is_greater(token): yield ",", token elif is_name(token): yield repr(token.string), token else: self.error( "Expected a descending order of rule names, " "e.g. rule1 > rule2 > rule3 ...", token, ) class GlobalWildcardConstraints(GlobalKeywordState): @property def keyword(self): return "global_wildcard_constraints" class GlobalSingularity(GlobalKeywordState): @property def keyword(self): return "global_singularity" # subworkflows class SubworkflowSnakefile(SubworkflowKeywordState): pass class SubworkflowWorkdir(SubworkflowKeywordState): pass class SubworkflowConfigfile(SubworkflowKeywordState): pass class Subworkflow(GlobalKeywordState): subautomata = dict( snakefile=SubworkflowSnakefile, workdir=SubworkflowWorkdir, configfile=SubworkflowConfigfile, ) def __init__(self, snakefile, base_indent=0, dedent=0, root=True): super().__init__(snakefile, base_indent=base_indent, dedent=dedent, root=root) self.state = self.name self.has_snakefile = False self.has_workdir = False self.has_name = False self.primary_token = None def end(self): if not (self.has_snakefile or self.has_workdir): self.error( "A subworkflow needs either a path to a Snakefile or to a workdir.", self.primary_token, ) yield ")" def name(self, token): if is_name(token): yield "workflow.subworkflow({name!r}".format(name=token.string), token self.has_name = True elif is_colon(token) and self.has_name: self.primary_token = token self.state = self.block else: self.error("Expected name after subworkflow keyword.", token) def block_content(self, token): if is_name(token): try: if token.string == "snakefile": self.has_snakefile = True if token.string == "workdir": self.has_workdir = True for t in self.subautomaton(token.string).consume(): yield t except KeyError: self.error( "Unexpected keyword {} in " "subworkflow definition".format(token.string), token, ) except StopAutomaton as e: self.indentation(e.token) for t in self.block(e.token): yield t elif is_comment(token): yield "\n", token yield token.string, token elif is_string(token): # ignore docstring pass else: self.error( "Expecting subworkflow keyword, comment or docstrings " "inside a subworkflow definition.", token, ) class Localrules(GlobalKeywordState): def block_content(self, token): if is_comma(token): yield ",", token elif is_name(token): yield repr(token.string), token else: self.error( "Expected a comma separated list of rules that shall " "not be executed by the cluster command.", token, ) # Rule keyword states class Input(RuleKeywordState): pass class Output(RuleKeywordState): pass class Params(RuleKeywordState): pass class Threads(RuleKeywordState): pass class Shadow(RuleKeywordState): pass class Resources(RuleKeywordState): pass class Priority(RuleKeywordState): pass class Version(RuleKeywordState): pass class Log(RuleKeywordState): pass class Message(RuleKeywordState): pass class Benchmark(RuleKeywordState): pass class Conda(RuleKeywordState): pass class Singularity(RuleKeywordState): pass class EnvModules(RuleKeywordState): pass class Group(RuleKeywordState): pass class WildcardConstraints(RuleKeywordState): @property def keyword(self): return "wildcard_constraints" class Run(RuleKeywordState): def __init__(self, snakefile, rulename, base_indent=0, dedent=0, root=True): super().__init__(snakefile, base_indent=base_indent, dedent=dedent, root=root) self.rulename = rulename self.content = 0 def start(self): yield "@workflow.run" yield "\n" yield ( "def __rule_{rulename}(input, output, params, wildcards, threads, " "resources, log, version, rule, conda_env, singularity_img, " "singularity_args, use_singularity, env_modules, bench_record, jobid, " "is_shell, bench_iteration, cleanup_scripts, shadow_dir):".format( rulename=self.rulename if self.rulename is not None else self.snakefile.rulecount ) ) def end(self): yield "" def block_content(self, token): self.content += 1 yield token.string, token def is_block_end(self, token): return (self.content and self.line and self.indent <= 0) or is_eof(token) class AbstractCmd(Run): overwrite_cmd = None start_func = None end_func = None def __init__(self, snakefile, rulename, base_indent=0, dedent=0, root=True): super().__init__( snakefile, rulename, base_indent=base_indent, dedent=dedent, root=root ) self.cmd = list() self.token = None if self.overwrite_cmd is not None: self.block_content = self.overwrite_block_content def is_block_end(self, token): return (self.line and self.indent <= 0) or is_eof(token) def start(self): if self.start_func is not None: yield self.start_func yield "(" def args(self): yield from [] def end(self): # the end is detected. So we can savely reset the indent to zero here self.indent = 0 yield "\n" yield ")" yield "\n" for t in super().start(): yield t yield "\n" yield INDENT * (self.effective_indent + 1) yield self.end_func yield "(" yield "\n".join(self.cmd) yield from self.args() yield "\n" yield ")" for t in super().end(): yield t def decorate_end(self, token): if self.token is None: # no block after shell keyword self.error( "Command must be given as string after the shell keyword.", token ) for t in self.end(): yield t, self.token def block_content(self, token): self.token = token self.cmd.append(token.string) yield token.string, token def overwrite_block_content(self, token): if self.token is None: self.token = token cmd = repr(self.overwrite_cmd) self.cmd.append(cmd) yield cmd, token class Shell(AbstractCmd): start_func = "@workflow.shellcmd" end_func = "shell" def args(self): yield ", bench_record=bench_record, bench_iteration=bench_iteration" class Script(AbstractCmd): start_func = "@workflow.script" end_func = "script" def args(self): # basedir yield ", {!r}".format(os.path.abspath(os.path.dirname(self.snakefile.path))) # other args yield ( ", input, output, params, wildcards, threads, resources, log, " "config, rule, conda_env, singularity_img, singularity_args, env_modules, " "bench_record, jobid, bench_iteration, cleanup_scripts, shadow_dir" ) class Notebook(Script): start_func = "@workflow.notebook" end_func = "notebook" class Wrapper(Script): start_func = "@workflow.wrapper" end_func = "wrapper" def args(self): yield ( ", input, output, params, wildcards, threads, resources, log, " "config, rule, conda_env, singularity_img, singularity_args, env_modules, " "bench_record, workflow.wrapper_prefix, jobid, bench_iteration, " "cleanup_scripts, shadow_dir" ) class CWL(Script): start_func = "@workflow.cwl" end_func = "cwl" def args(self): # basedir yield ", {!r}".format(os.path.abspath(os.path.dirname(self.snakefile.path))) # other args yield ( ", input, output, params, wildcards, threads, resources, log, " "config, rule, use_singularity, bench_record, jobid" ) class Rule(GlobalKeywordState): subautomata = dict( input=Input, output=Output, params=Params, threads=Threads, resources=Resources, priority=Priority, version=Version, log=Log, message=Message, benchmark=Benchmark, conda=Conda, singularity=Singularity, envmodules=EnvModules, wildcard_constraints=WildcardConstraints, shadow=Shadow, group=Group, run=Run, shell=Shell, script=Script, notebook=Notebook, wrapper=Wrapper, cwl=CWL, ) def __init__(self, snakefile, base_indent=0, dedent=0, root=True): super().__init__(snakefile, base_indent=base_indent, dedent=dedent, root=root) self.state = self.name self.lineno = None self.rulename = None self.run = False self.snakefile.rulecount += 1 def start(self, aux=""): yield ( "@workflow.rule(name={rulename!r}, lineno={lineno}, " "snakefile={snakefile!r}{aux})".format( rulename=self.rulename, lineno=self.lineno, snakefile=self.snakefile.path, aux=aux, ) ) def end(self): if not self.run: yield "@workflow.norun()" yield "\n" for t in self.subautomaton("run", rulename=self.rulename).start(): yield t # the end is detected. # So we can savely reset the indent to zero here self.indent = 0 yield "\n" yield INDENT * (self.effective_indent + 1) yield "pass" def name(self, token): if is_name(token): self.rulename = token.string elif is_colon(token): self.lineno = self.snakefile.lines + 1 self.state = self.block for t in self.start(): yield t, token else: self.error("Expected name or colon after rule keyword.", token) def block_content(self, token): if is_name(token): try: if ( token.string == "run" or token.string == "shell" or token.string == "script" or token.string == "wrapper" or token.string == "cwl" ): if self.run: raise self.error( "Multiple run or shell keywords in rule {}.".format( self.rulename ), token, ) self.run = True elif self.run: raise self.error( "No rule keywords allowed after " "run/shell/script/wrapper/cwl in " "rule {}.".format(self.rulename), token, ) for t in self.subautomaton( token.string, rulename=self.rulename ).consume(): yield t except KeyError: self.error( "Unexpected keyword {} in rule definition".format(token.string), token, ) except StopAutomaton as e: self.indentation(e.token) for t in self.block(e.token): yield t elif is_comment(token): yield "\n", token yield token.string, token elif is_string(token): yield "\n", token yield "@workflow.docstring({})".format(token.string), token else: self.error( "Expecting rule keyword, comment or docstrings " "inside a rule definition.", token, ) @property def dedent(self): return self.indent class Checkpoint(Rule): def start(self): yield from super().start(aux=", checkpoint=True") class OnSuccess(DecoratorKeywordState): decorator = "onsuccess" args = ["log"] class OnError(DecoratorKeywordState): decorator = "onerror" args = ["log"] class OnStart(DecoratorKeywordState): decorator = "onstart" args = ["log"] class Python(TokenAutomaton): subautomata = dict( include=Include, workdir=Workdir, configfile=Configfile, report=Report, ruleorder=Ruleorder, rule=Rule, checkpoint=Checkpoint, subworkflow=Subworkflow, localrules=Localrules, onsuccess=OnSuccess, onerror=OnError, onstart=OnStart, wildcard_constraints=GlobalWildcardConstraints, singularity=GlobalSingularity, ) def __init__(self, snakefile, base_indent=0, dedent=0, root=True): super().__init__(snakefile, base_indent=base_indent, dedent=dedent, root=root) self.state = self.python def python(self, token): if not (is_indent(token) or is_dedent(token)): if self.lasttoken is None or self.lasttoken.isspace(): try: for t in self.subautomaton(token.string).consume(): yield t except KeyError: yield token.string, token except StopAutomaton as e: self.indentation(e.token) for t in self.python(e.token): yield t else: yield token.string, token class Snakefile: def __init__(self, path, rulecount=0): self.path = path try: self.file = open(self.path, encoding="utf-8") except (FileNotFoundError, OSError) as e: try: self.file = TextIOWrapper( urllib.request.urlopen(self.path), encoding="utf-8" ) except (HTTPError, URLError, ContentTooShortError, ValueError): raise WorkflowError("Failed to open {}.".format(path)) self.tokens = tokenize.generate_tokens(self.file.readline) self.rulecount = rulecount self.lines = 0 def __next__(self): return next(self.tokens) def __iter__(self): return self def __enter__(self): return self def __exit__(self, *args): self.file.close() def format_tokens(tokens): t_ = None for t in tokens: if t_ and not t.isspace() and not t_.isspace(): yield " " yield t t_ = t def parse(path, overwrite_shellcmd=None, rulecount=0): Shell.overwrite_cmd = overwrite_shellcmd with Snakefile(path, rulecount=rulecount) as snakefile: automaton = Python(snakefile) linemap = dict() compilation = list() for t, orig_token in automaton.consume(): l = lineno(orig_token) linemap.update( dict( (i, l) for i in range( snakefile.lines + 1, snakefile.lines + t.count("\n") + 1 ) ) ) snakefile.lines += t.count("\n") compilation.append(t) compilation = "".join(format_tokens(compilation)) if linemap: last = max(linemap) linemap[last + 1] = linemap[last] return compilation, linemap, snakefile.rulecount snakemake-5.10.0/snakemake/persistence.py000077500000000000000000000315061361131222100203710ustar00rootroot00000000000000__author__ = "Johannes Köster" __copyright__ = "Copyright 2015-2019, Johannes Köster" __email__ = "koester@jimmy.harvard.edu" __license__ = "MIT" import os import shutil import signal import marshal import pickle import json import time from base64 import urlsafe_b64encode, b64encode from functools import lru_cache, partial from itertools import filterfalse, count from snakemake.logging import logger from snakemake.jobs import jobfiles from snakemake.utils import listfiles class Persistence: def __init__( self, nolock=False, dag=None, conda_prefix=None, singularity_prefix=None, shadow_prefix=None, warn_only=False, ): self.path = os.path.abspath(".snakemake") if not os.path.exists(self.path): os.mkdir(self.path) self._lockdir = os.path.join(self.path, "locks") if not os.path.exists(self._lockdir): os.mkdir(self._lockdir) self.dag = dag self._lockfile = dict() self._metadata_path = os.path.join(self.path, "metadata") self.conda_env_archive_path = os.path.join(self.path, "conda-archive") self.benchmark_path = os.path.join(self.path, "benchmarks") if conda_prefix is None: self.conda_env_path = os.path.join(self.path, "conda") else: self.conda_env_path = os.path.abspath(os.path.expanduser(conda_prefix)) if singularity_prefix is None: self.singularity_img_path = os.path.join(self.path, "singularity") else: self.singularity_img_path = os.path.abspath( os.path.expanduser(singularity_prefix) ) if shadow_prefix is None: self.shadow_path = os.path.join(self.path, "shadow") else: self.shadow_path = os.path.join(shadow_prefix, "shadow") for d in ( self._metadata_path, self.shadow_path, self.conda_env_archive_path, self.conda_env_path, self.singularity_img_path, ): os.makedirs(d, exist_ok=True) if nolock: self.lock = self.noop self.unlock = self.noop if warn_only: self.lock = self.lock_warn_only self.unlock = self.noop self._read_record = self._read_record_cached @property def files(self): if self._files is None: self._files = set(self.dag.output_files) return self._files @property def locked(self): inputfiles = set(self.all_inputfiles()) outputfiles = set(self.all_outputfiles()) if os.path.exists(self._lockdir): for lockfile in self._locks("input"): with open(lockfile) as lock: for f in lock: f = f.strip() if f in outputfiles: return True for lockfile in self._locks("output"): with open(lockfile) as lock: for f in lock: f = f.strip() if f in outputfiles or f in inputfiles: return True return False def lock_warn_only(self): if self.locked: logger.info( "Error: Directory cannot be locked. This usually " "means that another Snakemake instance is running on this directory. " "Another possibility is that a previous run exited unexpectedly." ) def lock(self): if self.locked: raise IOError("Another snakemake process " "has locked this directory.") self._lock(self.all_inputfiles(), "input") self._lock(self.all_outputfiles(), "output") def unlock(self, *args): logger.debug("unlocking") for lockfile in self._lockfile.values(): try: logger.debug("removing lock") os.remove(lockfile) except OSError as e: if e.errno != 2: # missing file raise e logger.debug("removed all locks") def cleanup_locks(self): shutil.rmtree(self._lockdir) def cleanup_metadata(self, path): self._delete_record(self._metadata_path, path) def cleanup_shadow(self): if os.path.exists(self.shadow_path): shutil.rmtree(self.shadow_path) os.mkdir(self.shadow_path) def cleanup_conda(self): # cleanup envs in_use = set(env.hash[:8] for env in self.dag.conda_envs.values()) for d in os.listdir(self.conda_env_path): if len(d) >= 8 and d[:8] not in in_use: if os.path.isdir(os.path.join(self.conda_env_path, d)): shutil.rmtree(os.path.join(self.conda_env_path, d)) else: os.remove(os.path.join(self.conda_env_path, d)) # cleanup env archives in_use = set(env.content_hash for env in self.dag.conda_envs.values()) for d in os.listdir(self.conda_env_archive_path): if d not in in_use: shutil.rmtree(os.path.join(self.conda_env_archive_path, d)) def started(self, job, external_jobid=None): for f in job.output: self._record( self._metadata_path, {"incomplete": True, "external_jobid": external_jobid}, f, ) def finished(self, job): version = str(job.rule.version) if job.rule.version is not None else None code = self._code(job.rule) input = self._input(job) log = self._log(job) params = self._params(job) shellcmd = job.shellcmd conda_env = self._conda_env(job) fallback_time = time.time() for f in job.expanded_output: rec_path = self._record_path(self._metadata_path, f) starttime = os.path.getmtime(rec_path) if os.path.exists(rec_path) else None endtime = f.mtime if os.path.exists(f) else fallback_time self._record( self._metadata_path, { "version": version, "code": code, "rule": job.rule.name, "input": input, "log": log, "params": params, "shellcmd": shellcmd, "incomplete": False, "starttime": starttime, "endtime": endtime, "job_hash": hash(job), "conda_env": conda_env, "singularity_img_url": job.singularity_img_url, }, f, ) def cleanup(self, job): for f in job.expanded_output: self._delete_record(self._metadata_path, f) def incomplete(self, job): def marked_incomplete(f): return self._read_record(self._metadata_path, f).get("incomplete", False) return any(map(lambda f: f.exists and marked_incomplete(f), job.output)) def external_jobids(self, job): return list( set( self._read_record(self._metadata_path, f).get("external_jobid", None) for f in job.output ) ) def metadata(self, path): return self._read_record(self._metadata_path, path) def version(self, path): return self.metadata(path).get("version") def rule(self, path): return self.metadata(path).get("rule") def input(self, path): return self.metadata(path).get("input") def log(self, path): return self.metadata(path).get("log") def shellcmd(self, path): return self.metadata(path).get("shellcmd") def params(self, path): return self.metadata(path).get("params") def code(self, path): return self.metadata(path).get("code") def version_changed(self, job, file=None): """Yields output files with changed versions of bool if file given.""" return _bool_or_gen(self._version_changed, job, file=file) def code_changed(self, job, file=None): """Yields output files with changed code of bool if file given.""" return _bool_or_gen(self._code_changed, job, file=file) def input_changed(self, job, file=None): """Yields output files with changed input of bool if file given.""" return _bool_or_gen(self._input_changed, job, file=file) def params_changed(self, job, file=None): """Yields output files with changed params of bool if file given.""" return _bool_or_gen(self._params_changed, job, file=file) def _version_changed(self, job, file=None): assert file is not None return self.version(file) != job.rule.version def _code_changed(self, job, file=None): assert file is not None return self.code(file) != self._code(job.rule) def _input_changed(self, job, file=None): assert file is not None return self.input(file) != self._input(job) def _params_changed(self, job, file=None): assert file is not None return self.params(file) != self._params(job) def noop(self, *args): pass def _b64id(self, s): return urlsafe_b64encode(str(s).encode()).decode() @lru_cache() def _code(self, rule): code = rule.run_func.__code__ return b64encode(pickle_code(code)).decode() @lru_cache() def _conda_env(self, job): if job.conda_env: return b64encode(job.conda_env.content).decode() @lru_cache() def _input(self, job): return sorted(job.input) @lru_cache() def _log(self, job): return sorted(job.log) @lru_cache() def _params(self, job): return sorted(map(repr, job.params)) @lru_cache() def _output(self, job): return sorted(job.output) def _record(self, subject, json_value, id): recpath = self._record_path(subject, id) os.makedirs(os.path.dirname(recpath), exist_ok=True) with open(recpath, "w") as f: json.dump(json_value, f) def _delete_record(self, subject, id): try: recpath = self._record_path(subject, id) os.remove(recpath) recdirs = os.path.relpath(os.path.dirname(recpath), start=subject) if recdirs != ".": os.removedirs(recdirs) except OSError as e: if e.errno != 2: # not missing raise e @lru_cache() def _read_record_cached(self, subject, id): return self._read_record_uncached(subject, id) def _read_record_uncached(self, subject, id): if not self._exists_record(subject, id): return dict() with open(self._record_path(subject, id), "r") as f: return json.load(f) def _exists_record(self, subject, id): return os.path.exists(self._record_path(subject, id)) def _locks(self, type): return ( f for f, _ in listfiles( os.path.join(self._lockdir, "{{n,[0-9]+}}.{}.lock".format(type)) ) if not os.path.isdir(f) ) def _lock(self, files, type): for i in count(0): lockfile = os.path.join(self._lockdir, "{}.{}.lock".format(i, type)) if not os.path.exists(lockfile): self._lockfile[type] = lockfile with open(lockfile, "w") as lock: print(*files, sep="\n", file=lock) return def _record_path(self, subject, id): max_len = ( os.pathconf(subject, "PC_NAME_MAX") if os.name == "posix" else 255 ) # maximum NTFS and FAT32 filename length if max_len == 0: max_len = 255 b64id = self._b64id(id) # split into chunks of proper length b64id = [b64id[i : i + max_len - 1] for i in range(0, len(b64id), max_len - 1)] # prepend dirs with @ (does not occur in b64) to avoid conflict with b64-named files in the same dir b64id = ["@" + s for s in b64id[:-1]] + [b64id[-1]] path = os.path.join(subject, *b64id) return path def all_outputfiles(self): # we only look at output files that will be updated return jobfiles(self.dag.needrun_jobs, "output") def all_inputfiles(self): # we consider all input files, also of not running jobs return jobfiles(self.dag.jobs, "input") def deactivate_cache(self): self._read_record_cached.cache_clear() self._read_record = self._read_record_uncached def _bool_or_gen(func, job, file=None): if file is None: return (f for f in job.expanded_output if func(job, file=f)) else: return func(job, file=file) def pickle_code(code): consts = [ (pickle_code(const) if type(const) == type(code) else const) for const in code.co_consts ] return pickle.dumps((code.co_code, code.co_varnames, consts, code.co_names)) snakemake-5.10.0/snakemake/remote/000077500000000000000000000000001361131222100167565ustar00rootroot00000000000000snakemake-5.10.0/snakemake/remote/AzureStorage.py000066400000000000000000000315201361131222100217440ustar00rootroot00000000000000__author__ = "Sebastian Kurscheid" __copyright__ = "Copyright 2019, Sebastian Kurscheid" __email__ = "sebastian.kurscheid@anu.edu.au" __license__ = "MIT" # built-ins import os import re import math import functools import concurrent.futures # snakemake specific from snakemake.common import lazy_property # module specific from snakemake.exceptions import WorkflowError, AzureFileException from snakemake.remote import AbstractRemoteObject, AbstractRemoteProvider # service provider support try: from azure.storage.common.cloudstorageaccount import ( CloudStorageAccount as AzureStorageAccount, ) except ImportError as e: raise WorkflowError( "The Python 3 packages 'azure-storage' and 'azure-storage-common' " "need to be installed to use Azure Storage remote() file functionality. %s" % e.msg ) class RemoteProvider(AbstractRemoteProvider): supports_default = True def __init__( self, *args, keep_local=False, stay_on_remote=False, is_default=False, **kwargs ): super(RemoteProvider, self).__init__( *args, keep_local=keep_local, stay_on_remote=stay_on_remote, is_default=is_default, **kwargs ) self._as = AzureStorageHelper(*args, **kwargs) def remote_interface(self): return self._as @property def default_protocol(self): """The protocol that is prepended to the path when no protocol is specified.""" return "ab://" @property def available_protocols(self): """List of valid protocols for this remote provider.""" return ["ab://"] class RemoteObject(AbstractRemoteObject): def __init__(self, *args, keep_local=False, provider=None, **kwargs): super(RemoteObject, self).__init__( *args, keep_local=keep_local, provider=provider, **kwargs ) if provider: self._as = provider.remote_interface() else: self._as = AzureStorageHelper(*args, **kwargs) # === Implementations of abstract class members === def exists(self): if self._matched_as_path: return self._as.exists_in_container(self.container_name, self.blob_name) else: raise AzureFileException( "The file cannot be parsed as an Azure Blob path in form 'container/blob': %s" % self.local_file() ) def mtime(self): if self.exists(): t = self._as.blob_last_modified(self.container_name, self.blob_name) return t else: raise AzureFileException( "The file does not seem to exist remotely: %s" % self.local_file() ) def size(self): if self.exists(): return self._as.blob_size(self.container_name, self.blob_name) else: return self._iofile.size_local def download(self): if self.exists(): os.makedirs(os.path.dirname(self.local_file()), exist_ok=True) self._as.download_from_azure_storage( self.container_name, self.blob_name, destination_path=self.local_file() ) os.sync() return self.local_file() return None def upload(self): self._as.upload_to_azure_storage( container_name=self.container_name, blob_name=self.blob_name, file_path=self.local_file(), ) @property def list(self): return self._as.list_blobs(self.container_name) # # === Related methods === @property def _matched_as_path(self): return re.search( "(?P[^/]*)/(?P.*)", self.local_file() ) def as_create_stub(self): if self._matched_as_path: if not self.exists: self._as.download_from_azure_storage( self.container_name, self.blob_name, self.file, create_stub_only=True, ) else: raise AzureFileException( "The file to be downloaded cannot be parsed as an Azure Storage path in form 'container/blob': %s" % self.local_file() ) @property def container_name(self): if len(self._matched_as_path.groups()) == 2: return self._matched_as_path.group("container_name") return None @property def name(self): return self.blob_name @property def blob_name(self): if len(self._matched_as_path.groups()) == 2: return self._matched_as_path.group("blob_name") # Actual Azure specific functions, adapted from S3.py class AzureStorageHelper(object): def __init__(self, *args, **kwargs): if "stay_on_remote" in kwargs: del kwargs["stay_on_remote"] self.azure = AzureStorageAccount(**kwargs).create_block_blob_service() def container_exists(self, container_name): try: self.azure.exists(container_name=container_name) return True except: return False def upload_to_azure_storage( self, container_name, file_path, blob_name=None, use_relative_path_for_blob_name=True, relative_start_dir=None, extra_args=None, ): """ Upload a file to Azure Storage This function uploads a file to an Azure Storage Container as a blob. Args: container_name: the name of the Azure container to use file_path: The path to the file to upload. blob_name: The name to set for the blob on Azure. If not specified, this will default to the name of the file. Returns: The blob_name of the file on Azure if written, None otherwise """ file_path = os.path.realpath(os.path.expanduser(file_path)) assert container_name, "container_name must be specified" assert os.path.exists(file_path), ( "The file path specified does not exist: %s" % file_path ) assert os.path.isfile(file_path), ( "The file path specified does not appear to be a file: %s" % file_path ) if not self.azure.exists(container_name): self.azure.create_container(container_name=container_name) if not blob_name: if use_relative_path_for_blob_name: if relative_start_dir: path_blob_name = os.path.relpath(file_path, relative_start_dir) else: path_blob_name = os.path.relpath(file_path) else: path_blob_name = os.path.basename(file_path) blob_name = path_blob_name b = self.azure try: b.create_blob_from_path( container_name, file_path=file_path, blob_name=blob_name ) return b.get_blob_properties(container_name, blob_name=blob_name).name except: raise WorkflowError("Error in creating blob. %s" % e.msg) # return None def download_from_azure_storage( self, container_name, blob_name, destination_path=None, expandBlobNameIntoDirs=True, make_dest_dirs=True, create_stub_only=False, ): """ Download a file from Azure Storage This function downloads an object from a specified Azure Storage container. Args: container_name: the name of the Azure Storage container to use (container name only) destination_path: If specified, the file will be saved to this path, otherwise cwd. expandBlobNameIntoDirs: Since Azure blob names can include slashes, if this is True (defult) then Azure blob names with slashes are expanded into directories on the receiving end. If it is False, the blob name is passed to os.path.basename() to get the substring following the last slash. make_dest_dirs: If this is True (default) and the destination path includes directories that do not exist, they will be created. Returns: The destination path of the downloaded file on the receiving end, or None if the destination_path could not be downloaded """ assert container_name, "container_name must be specified" assert blob_name, "blob_name must be specified" if destination_path: destination_path = os.path.realpath(os.path.expanduser(destination_path)) else: if expandBlobNameIntoDirs: destination_path = os.path.join(os.getcwd(), blob_name) else: destination_path = os.path.join( os.getcwd(), os.path.basename(blob_name) ) # if the destination path does not exist if make_dest_dirs: os.makedirs(os.path.dirname(destination_path), exist_ok=True) b = self.azure try: if not create_stub_only: b.get_blob_to_path( container_name=container_name, blob_name=blob_name, file_path=destination_path, ) else: # just create an empty file with the right timestamps with open(destination_path, "wb") as fp: os.utime( fp.name, (k.last_modified.timestamp(), k.last_modified.timestamp()), ) return destination_path except: return None def delete_from_container(self, container_name, blob_name): """ Delete a file from Azure Storage container This function deletes an object from a specified Azure Storage container. Args: container_name: the name of the Azure Storage container to use (container name only, not endpoint) blob_name: the name of the blob to delete from the container Returns: nothing """ assert container_name, "container_name must be specified" assert blob_name, "blob_name must be specified" b = self.azure b.delete_blob(container_name, blob_name) def exists_in_container(self, container_name, blob_name): """ Returns whether the blob exists in the container Args: container_name: the name of the Azure Storage container (container name only, not endpoint) blob_name: the blob_name of the object to delete from the container Returns: True | False """ assert container_name, "container_name must be specified" assert blob_name, "blob_name must be specified" try: return self.azure.exists(container_name, blob_name) except: return None def blob_size(self, container_name, blob_name): """ Returns the size of a blob Args: container_name: the name of the Azure Storage container (container name only, not endpoint) blob_name: the blob_name of the object to delete from the container Returns: Size in kb """ assert container_name, "container_name must be specified" assert blob_name, "blob_name must be specified" try: b = self.azure.get_blob_properties(container_name, blob_name) return b.properties.content_length // 1024 except: print("blob or container do not exist") return None def blob_last_modified(self, container_name, blob_name): """ Returns a timestamp of a blob Args: container_name: the name of the Azure Storage container (container name only, not endpoint) blob_name: the blob_name of the object to delete from the container Returns: timestamp """ assert container_name, "container_name must be specified" assert blob_name, "blob_name must be specified" try: b = self.azure.get_blob_properties(container_name, blob_name) return b.properties.last_modified.timestamp() except: print("blob or container do not exist") return None def list_blobs(self, container_name): """ Returns a list of blobs from the container Args: container_name: the name of the Azure Storage container (container name only, not endpoint) Returns: list of blobs """ assert container_name, "container_name must be specified" try: b = self.azure.list_blobs(container_name) return [o.name for o in b] except: print("Did you provide a valid container_name?") return None snakemake-5.10.0/snakemake/remote/EGA.py000066400000000000000000000162241361131222100177310ustar00rootroot00000000000000__author__ = "Johannes Köster" __copyright__ = "Copyright 2018-2019, Johannes Köster" __email__ = "johannes.koester@tu-dortmund.de" __license__ = "MIT" import os import json import time import uuid from collections import namedtuple import hashlib import requests from requests.auth import HTTPBasicAuth from snakemake.remote import AbstractRemoteObject, AbstractRemoteProvider from snakemake.exceptions import WorkflowError from snakemake.common import lazy_property EGAFileInfo = namedtuple("EGAFileInfo", ["size", "status", "id", "checksum"]) EGAFile = namedtuple("EGAFile", ["dataset", "path"]) class RemoteProvider(AbstractRemoteProvider): def __init__( self, *args, keep_local=False, stay_on_remote=False, is_default=False, retry=5, **kwargs ): super().__init__( *args, keep_local=keep_local, stay_on_remote=stay_on_remote, is_default=is_default, **kwargs ) self.retry = retry self._token = None self._expires = None self._file_cache = dict() def _login(self): if self._expires is not None and self._expires > time.time(): # token is still valid return # token will expire in 10 minutes # (we stop using it 10 seconds earlier to be sure) self._expires = time.time() + 10 * 60 * 60 - 10 data = { "grant_type": "password", "client_id": self._client_id(), "scope": "openid", "client_secret": self._client_secret(), "username": self._username(), "password": self._password(), } for i in range(3): try: r = requests.post( "https://ega.ebi.ac.uk:8443/ega-openid-connect-server/token", headers={"Content-Type": "application/x-www-form-urlencoded"}, data=data, ) except requests.exceptions.ConnectionError as e: time.sleep(5) if i == 2: raise WorkflowError("Error contacting EGA.", e) if r.status_code != 200: raise WorkflowError("Login to EGA failed with:\n{}".format(r.text)) r = r.json() # store session token try: self._token = r["access_token"] except KeyError: raise WorkflowError("Login to EGA failed:\n{}".format(r)) def _expire_token(self): self._expires = None @property def token(self): self._login() return self._token def api_request( self, url_suffix, url_prefix="https://ega.ebi.ac.uk:8051/elixir/", json=True, post=False, **params ): """Make an API request. Args: url_suffix (str): Part of REST API URL right of https://ega.ebi.ac.uk:8051/elixir/ params (dict): Parameters to pass, except session """ url = url_prefix + url_suffix headers = ( {"Accept": "application/json"} if json else {"Accept": "application/octet-stream"} ) headers["Authorization"] = "Bearer {}".format(self.token) for i in range(3): try: if post: r = requests.post( url, stream=not json, data=params, params={"session": self.token}, headers=headers, ) else: params = dict(params) params["session"] = self.token r = requests.get( url, stream=not json, params=params, headers=headers ) except requests.exceptions.ConnectionError as e: time.sleep(5) if i == 2: raise WorkflowError("Error contacting EGA.", e) if r.status_code != 200: raise WorkflowError( "Access to EGA API endpoint {} failed " "with:\n{}".format(url, r.text) ) if json: msg = r.json() return msg else: return r def get_files(self, dataset): if dataset not in self._file_cache: files = self.api_request( "data/metadata/datasets/{dataset}/files".format(dataset=dataset) ) self._file_cache[dataset] = { os.path.basename(f["fileName"])[:-4]: EGAFileInfo( int(f["fileSize"]), f["fileStatus"], f["fileId"], f["checksum"] ) for f in files } return self._file_cache[dataset] @property def default_protocol(self): return "ega://" @property def available_protocols(self): return ["ega://"] @classmethod def _username(cls): return self._credentials("EGA_USERNAME") @classmethod def _password(cls): return self._credentials("EGA_PASSWORD") @classmethod def _client_id(cls): return self._credentials("EGA_CLIENT_ID") @classmethod def _client_secret(cls): return self._credentials("EGA_CLIENT_SECRET") @classmethod def _credentials(cls, name): try: return os.environ[name] except KeyError: raise WorkflowError( "$EGA_USERNAME, $EGA_PASSWORD, $EGA_CLIENT_ID, " "$EGA_CLIENT_SECRET must be given " "as environment variables." ) class RemoteObject(AbstractRemoteObject): # === Implementations of abstract class members === def _stats(self): return self.provider.get_files(self.parts.dataset)[self.parts.path] def exists(self): return self.parts.path in self.provider.get_files(self.parts.dataset) def size(self): return self._stats().size def mtime(self): # There is no mtime info provided by EGA # Hence, the files are always considered to be "ancient". return 0 def download(self): stats = self._stats() r = self.provider.api_request( "data/files/{}?destinationFormat=plain".format(stats.id), json=False ) local_md5 = hashlib.md5() # download file in chunks and calculate md5 on the fly os.makedirs(os.path.dirname(self.local_file()), exist_ok=True) with open(self.local_file(), "wb") as f: for chunk in r.iter_content(chunk_size=1024 * 1024 * 10): local_md5.update(chunk) f.write(chunk) local_md5 = local_md5.hexdigest() if local_md5 != stats.checksum: raise WorkflowError( "File checksums do not match for: {}".format(self.remote_file()) ) @lazy_property def parts(self): parts = self.local_file().split("/") if parts[0] != "ega": raise WorkflowError( "Invalid EGA remote file name. Must be 'ega//'" ) _, dataset, path = self.local_file().split("/", 2) return EGAFile(dataset, path) snakemake-5.10.0/snakemake/remote/FTP.py000066400000000000000000000215161361131222100177660ustar00rootroot00000000000000__author__ = "Christopher Tomkins-Tinch" __copyright__ = "Copyright 2015, Christopher Tomkins-Tinch" __email__ = "tomkinsc@broadinstitute.org" __license__ = "MIT" import os import re import ftplib import collections from itertools import chain from contextlib import contextmanager # module-specific from snakemake.remote import AbstractRemoteProvider, DomainObject from snakemake.exceptions import FTPFileException, WorkflowError try: # third-party modules import ftputil import ftputil.session except ImportError as e: raise WorkflowError( "The Python 3 package 'ftputil' " + "must be installed to use SFTP remote() file functionality. %s" % e.msg ) class RemoteProvider(AbstractRemoteProvider): supports_default = True allows_directories = True def __init__( self, *args, keep_local=False, stay_on_remote=False, is_default=False, immediate_close=False, **kwargs ): super(RemoteProvider, self).__init__( *args, keep_local=keep_local, stay_on_remote=stay_on_remote, is_default=is_default, **kwargs ) self.immediate_close = immediate_close @property def default_protocol(self): """The protocol that is prepended to the path when no protocol is specified.""" return "ftp://" @property def available_protocols(self): """List of valid protocols for this remote provider.""" return ["ftp://", "ftps://"] def remote( self, value, *args, encrypt_data_channel=None, immediate_close=None, **kwargs ): if isinstance(value, str): values = [value] elif isinstance(value, collections.abc.Iterable): values = value else: raise TypeError( "Invalid type ({}) passed to remote: {}".format(type(value), value) ) for i, file in enumerate(values): match = re.match("^(ftps?)://.+", file) if match: (protocol,) = match.groups() if protocol == "ftps" and encrypt_data_channel: raise SyntaxError( "encrypt_data_channel=False cannot be used with a ftps:// url" ) if protocol == "ftp" and encrypt_data_channel not in [None, False]: raise SyntaxError( "encrypt_data_channel=Trie cannot be used with a ftp:// url" ) else: if encrypt_data_channel: values[i] = "ftps://" + file else: values[i] = "ftp://" + file should_close = immediate_close if immediate_close else self.immediate_close values = [ super(RemoteProvider, self).remote( value, *args, encrypt_data_channel=encrypt_data_channel, immediate_close=should_close, **kwargs ) for value in values ] if len(values) == 1: return values[0] else: return values class RemoteObject(DomainObject): """ This is a class to interact with an FTP server. """ def __init__( self, *args, keep_local=False, provider=None, encrypt_data_channel=False, immediate_close=False, **kwargs ): super(RemoteObject, self).__init__( *args, keep_local=keep_local, provider=provider, **kwargs ) self.encrypt_data_channel = encrypt_data_channel self.immediate_close = immediate_close def close(self): if ( hasattr(self, "conn") and isinstance(self.conn, ftputil.FTPHost) and not self.immediate_close ): try: self.conn.keep_alive() self.conn.close() except: pass # === Implementations of abstract class members === @contextmanager # makes this a context manager. after 'yield' is __exit__() def ftpc(self): if ( not hasattr(self, "conn") or (hasattr(self, "conn") and not isinstance(self.conn, ftputil.FTPHost)) ) or self.immediate_close: # if args have been provided to remote(), use them over those given to RemoteProvider() args_to_use = self.provider.args if len(self.args): args_to_use = self.args # use kwargs passed in to remote() to override those given to the RemoteProvider() # default to the host and port given as part of the file, falling back to one specified # as a kwarg to remote() or the RemoteProvider (overriding the latter with the former if both) kwargs_to_use = {} kwargs_to_use["host"] = self.host kwargs_to_use["username"] = None kwargs_to_use["password"] = None kwargs_to_use["port"] = int(self.port) if self.port else 21 kwargs_to_use["encrypt_data_channel"] = self.encrypt_data_channel for k, v in self.provider.kwargs.items(): kwargs_to_use[k] = v for k, v in self.kwargs.items(): kwargs_to_use[k] = v ftp_base_class = ( ftplib.FTP_TLS if kwargs_to_use["encrypt_data_channel"] else ftplib.FTP ) ftp_session_factory = ftputil.session.session_factory( base_class=ftp_base_class, port=kwargs_to_use["port"], encrypt_data_channel=kwargs_to_use["encrypt_data_channel"], debug_level=None, ) conn = ftputil.FTPHost( kwargs_to_use["host"], kwargs_to_use["username"], kwargs_to_use["password"], session_factory=ftp_session_factory, ) if self.immediate_close: yield conn else: self.conn = conn yield self.conn elif not self.immediate_close: yield self.conn # after returning from the context manager, close the connection if the scope is local if self.immediate_close: try: conn.keep_alive() conn.close() except: pass def exists(self): if self._matched_address: with self.ftpc() as ftpc: return ftpc.path.exists(self.remote_path) return False else: raise FTPFileException( "The file cannot be parsed as an FTP path in form 'host:port/abs/path/to/file': %s" % self.local_file() ) def mtime(self): if self.exists(): with self.ftpc() as ftpc: try: # requires write access ftpc.synchronize_times() except: pass return ftpc.path.getmtime(self.remote_path) else: raise FTPFileException( "The file does not seem to exist remotely: %s" % self.local_file() ) def size(self): if self.exists(): with self.ftpc() as ftpc: return ftpc.path.getsize(self.remote_path) else: return self._iofile.size_local def download(self, make_dest_dirs=True): with self.ftpc() as ftpc: if self.exists(): # if the destination path does not exist if make_dest_dirs: os.makedirs(os.path.dirname(self.local_path), exist_ok=True) try: # requires write access ftpc.synchronize_times() except: pass ftpc.download(source=self.remote_path, target=self.local_path) os.sync() # ensure flush to disk else: raise FTPFileException( "The file does not seem to exist remotely: %s" % self.local_file() ) def upload(self): with self.ftpc() as ftpc: ftpc.synchronize_times() ftpc.upload(source=self.local_path, target=self.remote_path) @property def list(self): file_list = [] first_wildcard = self._iofile.constant_prefix() dirname = first_wildcard.replace(self.path_prefix, "") with self.ftpc() as ftpc: file_list = [ (os.path.join(dirpath, f) if dirpath != "." else f) for dirpath, dirnames, filenames in ftpc.walk(dirname) for f in chain(filenames, dirnames) ] file_list = [ file_path[1:] if file_path[0] == "/" else file_path for file_path in file_list ] return file_list snakemake-5.10.0/snakemake/remote/GS.py000066400000000000000000000106171361131222100176460ustar00rootroot00000000000000__author__ = "Johannes Köster" __copyright__ = "Copyright 2017-2019, Johannes Köster" __email__ = "johannes.koester@tu-dortmund.de" __license__ = "MIT" import os import re from snakemake.remote import AbstractRemoteObject, AbstractRemoteProvider from snakemake.exceptions import WorkflowError from snakemake.common import lazy_property try: import google.cloud from google.cloud import storage except ImportError as e: raise WorkflowError( "The Python 3 package 'google-cloud-sdk' " "needs to be installed to use GS remote() file functionality. %s" % e.msg ) class RemoteProvider(AbstractRemoteProvider): supports_default = True def __init__( self, *args, keep_local=False, stay_on_remote=False, is_default=False, **kwargs ): super(RemoteProvider, self).__init__( *args, keep_local=keep_local, stay_on_remote=stay_on_remote, is_default=is_default, **kwargs ) self.client = storage.Client(*args, **kwargs) def remote_interface(self): return self.client @property def default_protocol(self): """The protocol that is prepended to the path when no protocol is specified.""" return "gs://" @property def available_protocols(self): """List of valid protocols for this remote provider.""" return ["gs://"] class RemoteObject(AbstractRemoteObject): def __init__( self, *args, keep_local=False, provider=None, user_project=None, **kwargs ): super(RemoteObject, self).__init__( *args, keep_local=keep_local, provider=provider, **kwargs ) if provider: self.client = provider.remote_interface() else: self.client = storage.Client(*args, **kwargs) # keep user_project available for when bucket is initialized self._user_project = user_project self._key = None self._bucket_name = None self._bucket = None self._blob = None # === Implementations of abstract class members === def exists(self): return self.blob.exists() def mtime(self): if self.exists(): self.update_blob() t = self.blob.updated return t.timestamp() else: raise WorkflowError( "The file does not seem to exist remotely: %s" % self.local_file() ) def size(self): if self.exists(): self.update_blob() return self.blob.size // 1024 else: return self._iofile.size_local def download(self): if self.exists(): os.makedirs(os.path.dirname(self.local_file()), exist_ok=True) self.blob.download_to_filename(self.local_file()) os.sync() return self.local_file() return None def upload(self): try: if not self.bucket.exists(): self.bucket.create() self.update_blob() self.blob.upload_from_filename(self.local_file()) except google.cloud.exceptions.Forbidden as e: raise WorkflowError( e, "When running locally, make sure that you are authenticated " "via gcloud (see Snakemake documentation). When running in a " "kubernetes cluster, make sure that storage-rw is added to " "--scopes (see Snakemake documentation).", ) @property def name(self): return self.key @property def list(self): return [k.name for k in self.bucket.list_blobs()] # ========= Helpers =============== def update_blob(self): self._blob = self.bucket.get_blob(self.key) @lazy_property def bucket(self): return self.client.bucket(self.bucket_name, user_project=self._user_project) @lazy_property def blob(self): return self.bucket.blob(self.key) @lazy_property def bucket_name(self): return self.parse().group("bucket") @lazy_property def key(self): return self.parse().group("key") def parse(self): m = re.search("(?P[^/]*)/(?P.*)", self.local_file()) if len(m.groups()) != 2: raise WorkflowError( "GS remote file {} does not have the form " "/.".format(self.local_file()) ) return m snakemake-5.10.0/snakemake/remote/HTTP.py000066400000000000000000000230631361131222100201130ustar00rootroot00000000000000__author__ = "Christopher Tomkins-Tinch" __copyright__ = "Copyright 2015, Christopher Tomkins-Tinch" __email__ = "tomkinsc@broadinstitute.org" __license__ = "MIT" import os import re import collections import shutil import email.utils from contextlib import contextmanager # module-specific from snakemake.remote import AbstractRemoteProvider, DomainObject from snakemake.exceptions import HTTPFileException, WorkflowError from snakemake.logging import logger try: # third-party modules import requests except ImportError as e: raise WorkflowError( "The Python 3 package 'requests' " + "must be installed to use HTTP(S) remote() file functionality. %s" % e.msg ) class RemoteProvider(AbstractRemoteProvider): def __init__( self, *args, keep_local=False, stay_on_remote=False, is_default=False, **kwargs ): super(RemoteProvider, self).__init__( *args, keep_local=keep_local, stay_on_remote=stay_on_remote, is_default=is_default, **kwargs ) @property def default_protocol(self): """The protocol that is prepended to the path when no protocol is specified.""" return "https://" @property def available_protocols(self): """List of valid protocols for this remote provider.""" return ["http://", "https://"] def remote(self, value, *args, insecure=None, **kwargs): if isinstance(value, str): values = [value] elif isinstance(value, collections.abc.Iterable): values = value else: raise TypeError( "Invalid type ({}) passed to remote: {}".format(type(value), value) ) for i, file in enumerate(values): match = re.match("^(https?)://.+", file) if match: (protocol,) = match.groups() if protocol == "https" and insecure: raise SyntaxError( "insecure=True cannot be used with a https:// url" ) if protocol == "http" and insecure not in [None, False]: raise SyntaxError( "insecure=False cannot be used with a http:// url" ) else: if insecure: values[i] = "http://" + file else: values[i] = "https://" + file return super(RemoteProvider, self).remote(values, *args, **kwargs) class RemoteObject(DomainObject): """ This is a class to interact with an HTTP server. """ def __init__( self, *args, keep_local=False, provider=None, additional_request_string="", allow_redirects=True, **kwargs ): super(RemoteObject, self).__init__( *args, keep_local=keep_local, provider=provider, allow_redirects=allow_redirects, **kwargs ) self.additional_request_string = additional_request_string # === Implementations of abstract class members === @contextmanager # makes this a context manager. after 'yield' is __exit__() def httpr(self, verb="GET", stream=False): # if args have been provided to remote(), use them over those given to RemoteProvider() args_to_use = self.provider.args if len(self.args): args_to_use = self.args # use kwargs passed in to remote() to override those given to the RemoteProvider() # default to the host and port given as part of the file, falling back to one specified # as a kwarg to remote() or the RemoteProvider (overriding the latter with the former if both) kwargs_to_use = {} kwargs_to_use["username"] = None kwargs_to_use["password"] = None kwargs_to_use["auth"] = None for k, v in self.provider.kwargs.items(): kwargs_to_use[k] = v for k, v in self.kwargs.items(): kwargs_to_use[k] = v # Check that in case authentication kwargs are provided, they are either ("username", "password") combination # or "auth", but not both. if ( kwargs_to_use["username"] and kwargs_to_use["password"] and kwargs_to_use["auth"] ): raise TypeError( "Authentication accepts either username and password or requests.auth object" ) # If "username" and "password" kwargs are provided, use those to construct a tuple for "auth". Neither # requests.head() nor requests.get() accept them as-is. if kwargs_to_use["username"] and kwargs_to_use["password"]: kwargs_to_use["auth"] = ( kwargs_to_use["username"], kwargs_to_use["password"], ) # Delete "username" and "password" from kwargs del kwargs_to_use["username"] del kwargs_to_use["password"] url = self.remote_file() + self.additional_request_string if verb.upper() == "GET": r = requests.get(url, *args_to_use, stream=stream, **kwargs_to_use) if verb.upper() == "HEAD": r = requests.head(url, *args_to_use, **kwargs_to_use) yield r r.close() def exists(self): if self._matched_address: with self.httpr(verb="HEAD") as httpr: # if a file redirect was found if httpr.status_code in range(300, 308): raise HTTPFileException( "The file specified appears to have been moved (HTTP %s), check the URL or try adding 'allow_redirects=True' to the remote() file object: %s" % (httpr.status_code, httpr.url) ) return httpr.status_code == requests.codes.ok return False else: raise HTTPFileException( "The file cannot be parsed as an HTTP path in form 'host:port/abs/path/to/file': %s" % self.local_file() ) def mtime(self): if self.exists(): with self.httpr(verb="HEAD") as httpr: file_mtime = self.get_header_item(httpr, "last-modified", default=None) logger.debug("HTTP last-modified: {}".format(file_mtime)) epochTime = 0 if file_mtime is not None: modified_tuple = email.utils.parsedate_tz(file_mtime) if modified_tuple is None: logger.debug( "HTTP last-modified not in RFC2822 format: `{}`".format( file_mtime ) ) else: epochTime = email.utils.mktime_tz(modified_tuple) return epochTime else: raise HTTPFileException( "The file does not seem to exist remotely: %s" % self.remote_file() ) def size(self): if self.exists(): with self.httpr(verb="HEAD") as httpr: content_size = int( self.get_header_item(httpr, "content-size", default=0) ) return content_size else: return self._iofile.size_local def download(self, make_dest_dirs=True): with self.httpr(stream=True) as httpr: if self.exists(): # Find out if the source file is gzip compressed in order to keep # compression intact after the download. # Per default requests decompresses .gz files. # More detials can be found here: https://stackoverflow.com/questions/25749345/how-to-download-gz-files-with-requests-in-python-without-decoding-it?noredirect=1&lq=1 # Since data transferred with HTTP compression need to be decompressed automatically # check the header and decode if the content is encoded. if ( not self.name.endswith(".gz") and httpr.headers.get("Content-Encoding") == "gzip" ): # Decode non-gzipped sourcefiles automatically. # This is needed to decompress uncompressed files that are compressed # for the transfer by HTTP compression. httpr.raw.decode_content = True # if the destination path does not exist if make_dest_dirs: os.makedirs(os.path.dirname(self.local_path), exist_ok=True) with open(self.local_path, "wb") as f: shutil.copyfileobj(httpr.raw, f) os.sync() # ensure flush to disk else: raise HTTPFileException( "The file does not seem to exist remotely: %s" % self.remote_file() ) def upload(self): raise HTTPFileException( "Upload is not permitted for the HTTP remote provider. Is an output set to HTTP.remote()?" ) def get_header_item(self, httpr, header_name, default): """ Since HTTP header capitalization may differ, this returns a header value regardless of case """ header_value = default for k, v in httpr.headers.items(): if k.lower() == header_name: header_value = v return header_value @property def list(self): raise HTTPFileException( "The HTTP Remote Provider does not currently support list-based operations like glob_wildcards()." ) snakemake-5.10.0/snakemake/remote/NCBI.py000066400000000000000000000704201361131222100200460ustar00rootroot00000000000000__author__ = "Christopher Tomkins-Tinch" __copyright__ = "Copyright 2017, Christopher Tomkins-Tinch" __email__ = "tomkinsc@broadinstitute.org" __license__ = "MIT" # built-ins import time import os import re import json import logging import xml.etree.ElementTree as ET # module-specific from snakemake.remote import AbstractRemoteObject, AbstractRemoteProvider from snakemake.exceptions import WorkflowError, NCBIFileException from snakemake.logging import logger try: # third-party modules from Bio import Entrez except ImportError as e: raise WorkflowError( "The Python package 'biopython' needs to be installed to use NCBI Entrez remote() file functionality. %s" % e.msg ) class RemoteProvider(AbstractRemoteProvider): def __init__( self, *args, keep_local=False, stay_on_remote=False, is_default=False, email=None, **kwargs ): super(RemoteProvider, self).__init__( *args, keep_local=keep_local, stay_on_remote=stay_on_remote, is_default=is_default, email=email, **kwargs ) self._ncbi = NCBIHelper(*args, email=email, **kwargs) def remote_interface(self): return self._ncbi @property def default_protocol(self): """The protocol that is prepended to the path when no protocol is specified.""" return "ncbi://" @property def available_protocols(self): """List of valid protocols for this remote provider.""" return ["ncbi://"] def search( self, query, *args, db="nuccore", idtype="acc", retmode="json", **kwargs ): return list( self._ncbi.search( query, *args, db=db, idtype=idtype, retmode=retmode, **kwargs ) ) class RemoteObject(AbstractRemoteObject): """ This is a class to interact with NCBI / GenBank. """ def __init__( self, *args, keep_local=False, stay_on_remote=False, provider=None, email=None, db=None, rettype=None, retmode=None, **kwargs ): super(RemoteObject, self).__init__( *args, keep_local=keep_local, stay_on_remote=stay_on_remote, provider=provider, email=email, db=db, rettype=rettype, retmode=retmode, **kwargs ) if provider: self._ncbi = provider.remote_interface() else: self._ncbi = NCBIHelper(*args, email=email, **kwargs) if db and not self._ncbi.is_valid_db(db): raise NCBIFileException( "DB specified is not valid. Options include: {dbs}".format( dbs=", ".join(self._ncbi.valid_dbs) ) ) else: self.db = db self.rettype = rettype self.retmode = retmode self.kwargs = kwargs # === Implementations of abstract class members === def exists(self): if not self.retmode or not self.rettype: likely_request_options = self._ncbi.guess_db_options_for_extension( self.file_ext, db=self.db, rettype=self.rettype, retmode=self.retmode ) self.db = likely_request_options["db"] self.retmode = likely_request_options["retmode"] self.rettype = likely_request_options["rettype"] return self._ncbi.exists(self.accession, db=self.db) def mtime(self): if self.exists(): return self._ncbi.mtime(self.accession, db=self.db) else: raise NCBIFileException( "The record does not seem to exist remotely: %s" % self.accession ) def size(self): if self.exists(): return self._ncbi.size(self.accession, db=self.db) else: return self._iofile.size_local def download(self): if self.exists(): self._ncbi.fetch_from_ncbi( [self.accession], os.path.dirname(self.accession), rettype=self.rettype, retmode=self.retmode, file_ext=self.file_ext, db=self.db, **self.kwargs ) else: raise NCBIFileException( "The record does not seem to exist remotely: %s" % self.accession ) def upload(self): raise NCBIFileException( "Upload is not permitted for the NCBI remote provider. Is an output set to NCBI.RemoteProvider.remote()?" ) @property def list(self): raise NCBIFileException( "The NCBI Remote Provider does not currently support list-based operations like glob_wildcards()." ) @property def accession(self): accession, version, file_ext = self._ncbi.parse_accession_str(self.local_file()) return accession + "." + version @property def file_ext(self): accession, version, file_ext = self._ncbi.parse_accession_str(self.local_file()) return file_ext @property def version(self): accession, version, file_ext = self._ncbi.parse_accession_str(self.local_file()) return version class NCBIHelper(object): def __init__(self, *args, email=None, **kwargs): if not email: raise NCBIFileException( "An e-mail address must be provided to either the remote file or the RemoteProvider() as email=. The NCBI requires e-mail addresses for queries." ) self.email = email self.entrez = Entrez self.entrez.email = self.email self.entrez.tool = "Snakemake" # valid NCBI Entrez efetch options # via https://www.ncbi.nlm.nih.gov/books/NBK25499/table/chapter4.T._valid_values_of__retmode_and/?report=objectonly self.efetch_options = { "bioproject": [{"rettype": "xml", "retmode": "xml", "ext": "xml"}], "biosample": [ {"rettype": "full", "retmode": "xml", "ext": "xml"}, {"rettype": "full", "retmode": "text", "ext": "txt"}, ], "biosystems": [{"rettype": "xml", "retmode": "xml", "ext": "xml"}], "gds": [{"rettype": "summary", "retmode": "text", "ext": "txt"}], "gene": [ {"rettype": "null", "retmode": "asn.1", "ext": "asn1"}, {"rettype": "null", "retmode": "xml", "ext": "xml"}, {"rettype": "gene_table", "retmode": "text", "ext": "gene_table"}, ], "homologene": [ {"rettype": "null", "retmode": "asn.1", "ext": "asn1"}, {"rettype": "null", "retmode": "xml", "ext": "xml"}, { "rettype": "alignmentscores", "retmode": "text", "ext": "alignmentscores", }, {"rettype": "fasta", "retmode": "text", "ext": "fasta"}, {"rettype": "homologene", "retmode": "text", "ext": "homologene"}, ], "mesh": [{"rettype": "full", "retmode": "text", "ext": "txt"}], "nlmcatalog": [ {"rettype": "null", "retmode": "text", "ext": "txt"}, {"rettype": "null", "retmode": "xml", "ext": "xml"}, ], "nuccore": [ {"rettype": "null", "retmode": "text", "ext": "txt"}, {"rettype": "null", "retmode": "asn.1", "ext": "asn1"}, {"rettype": "native", "retmode": "xml", "ext": "xml"}, {"rettype": "acc", "retmode": "text", "ext": "acc"}, {"rettype": "fasta", "retmode": "text", "ext": "fasta"}, {"rettype": "fasta", "retmode": "xml", "ext": "fasta.xml"}, {"rettype": "seqid", "retmode": "text", "ext": "seqid"}, {"rettype": "gb", "retmode": "text", "ext": "gb"}, {"rettype": "gb", "retmode": "xml", "ext": "gb.xml"}, {"rettype": "gbc", "retmode": "xml", "ext": "gbc"}, {"rettype": "ft", "retmode": "text", "ext": "ft"}, {"rettype": "gbwithparts", "retmode": "text", "ext": "gbwithparts"}, {"rettype": "fasta_cds_na", "retmode": "text", "ext": "fasta_cds_na"}, {"rettype": "fasta_cds_aa", "retmode": "text", "ext": "fasta_cds_aa"}, ], "nucest": [ {"rettype": "null", "retmode": "text", "ext": "txt"}, {"rettype": "null", "retmode": "asn.1", "ext": "asn1"}, {"rettype": "native", "retmode": "xml", "ext": "xml"}, {"rettype": "acc", "retmode": "text", "ext": "acc"}, {"rettype": "fasta", "retmode": "text", "ext": "fasta"}, {"rettype": "fasta", "retmode": "xml", "ext": "fasta.xml"}, {"rettype": "seqid", "retmode": "text", "ext": "seqid"}, {"rettype": "gb", "retmode": "text", "ext": "gb"}, {"rettype": "gb", "retmode": "xml", "ext": "gb.xml"}, {"rettype": "gbc", "retmode": "xml", "ext": "gbc"}, {"rettype": "est", "retmode": "text", "ext": "est"}, ], "nucgss": [ {"rettype": "null", "retmode": "text", "ext": "txt"}, {"rettype": "null", "retmode": "asn.1", "ext": "asn1"}, {"rettype": "native", "retmode": "xml", "ext": "xml"}, {"rettype": "acc", "retmode": "text", "ext": "acc"}, {"rettype": "fasta", "retmode": "text", "ext": "fasta"}, {"rettype": "fasta", "retmode": "xml", "ext": "fasta.xml"}, {"rettype": "seqid", "retmode": "text", "ext": "seqid"}, {"rettype": "gb", "retmode": "text", "ext": "gb"}, {"rettype": "gb", "retmode": "xml", "ext": "gb.xml"}, {"rettype": "gbc", "retmode": "xml", "ext": "gbc"}, {"rettype": "gss", "retmode": "text", "ext": "gss"}, ], "protein": [ {"rettype": "null", "retmode": "text", "ext": "txt"}, {"rettype": "null", "retmode": "asn.1", "ext": "asn1"}, {"rettype": "native", "retmode": "xml", "ext": "xml"}, {"rettype": "acc", "retmode": "text", "ext": "acc"}, {"rettype": "fasta", "retmode": "text", "ext": "fasta"}, {"rettype": "fasta", "retmode": "xml", "ext": "fasta.xml"}, {"rettype": "seqid", "retmode": "text", "ext": "seqid"}, {"rettype": "ft", "retmode": "text", "ext": "ft"}, {"rettype": "gp", "retmode": "text", "ext": "gp"}, {"rettype": "gp", "retmode": "xml", "ext": "gp.xml"}, {"rettype": "gpc", "retmode": "xml", "ext": "gpc"}, {"rettype": "ipg", "retmode": "xml", "ext": "xml"}, ], "popset": [ {"rettype": "null", "retmode": "text", "ext": "txt"}, {"rettype": "null", "retmode": "asn.1", "ext": "asn1"}, {"rettype": "native", "retmode": "xml", "ext": "xml"}, {"rettype": "acc", "retmode": "text", "ext": "acc"}, {"rettype": "fasta", "retmode": "text", "ext": "fasta"}, {"rettype": "fasta", "retmode": "xml", "ext": "fasta.xml"}, {"rettype": "seqid", "retmode": "text", "ext": "seqid"}, {"rettype": "gb", "retmode": "text", "ext": "gb"}, {"rettype": "gb", "retmode": "xml", "ext": "gb.xml"}, {"rettype": "gbc", "retmode": "xml", "ext": "gbc"}, ], "pmc": [ {"rettype": "null", "retmode": "xml", "ext": "xml"}, {"rettype": "medline", "retmode": "text", "ext": "medline"}, ], "pubmed": [ {"rettype": "null", "retmode": "asn.1", "ext": "asn1"}, {"rettype": "null", "retmode": "xml", "ext": "xml"}, {"rettype": "medline", "retmode": "text", "ext": "medline"}, {"rettype": "uilist", "retmode": "text", "ext": "uilist"}, {"rettype": "abstract", "retmode": "text", "ext": "abstract"}, ], "sequences": [ {"rettype": "null", "retmode": "text", "ext": "txt"}, {"rettype": "acc", "retmode": "text", "ext": "acc"}, {"rettype": "fasta", "retmode": "text", "ext": "fasta"}, {"rettype": "seqid", "retmode": "text", "ext": "seqid"}, ], "snp": [ {"rettype": "null", "retmode": "asn.1", "ext": "asn1"}, {"rettype": "null", "retmode": "xml", "ext": "xml"}, {"rettype": "flt", "retmode": "text", "ext": "flt"}, {"rettype": "fasta", "retmode": "text", "ext": "fasta"}, {"rettype": "rsr", "retmode": "text", "ext": "rsr"}, {"rettype": "ssexemplar", "retmode": "text", "ext": "ssexemplar"}, {"rettype": "chr", "retmode": "text", "ext": "chr"}, {"rettype": "docset", "retmode": "text", "ext": "docset"}, {"rettype": "uilist", "retmode": "text", "ext": "uilist"}, {"rettype": "uilist", "retmode": "xml", "ext": "uilist.xml"}, ], "sra": [{"rettype": "full", "retmode": "xml", "ext": "xml"}], "taxonomy": [ {"rettype": "null", "retmode": "xml", "ext": "xml"}, {"rettype": "uilist", "retmode": "text", "ext": "uilist"}, {"rettype": "uilist", "retmode": "xml", "ext": "uilist.xml"}, ], } @property def valid_extensions(self): extensions = set() for db, db_options in self.efetch_options.items(): for options in db_options: extensions |= set([options["ext"]]) return list(extensions) def dbs_for_options(self, file_ext, rettype=None, retmode=None): possible_dbs = set() for db, db_options in self.efetch_options.items(): for option_dict in db_options: if option_dict["ext"] == file_ext: if retmode and option_dict["retmode"] != retmode: continue if rettype and option_dict["rettype"] != rettype: continue possible_dbs |= set([db]) break return possible_dbs def options_for_db_and_extension(self, db, file_ext, rettype=None, retmode=None): possible_options = [] assert file_ext, "file_ext must be defined" if not self.is_valid_db(db): raise NCBIFileException( "DB specified is not valid. Options include: {dbs}".format( dbs=", ".join(self.valid_dbs) ) ) db_options = self.efetch_options[db] for opt in db_options: if file_ext == opt["ext"]: if retmode and opt["retmode"] != retmode: continue if rettype and opt["rettype"] != rettype: continue possible_options.append(opt) return possible_options def guess_db_options_for_extension( self, file_ext, db=None, rettype=None, retmode=None ): if db and rettype and retmode: if self.is_valid_db_request(db, rettype, retmode): request_options = {} request_options["db"] = db request_options["rettype"] = rettype request_options["retmode"] = retmode request_options["ext"] = file_ext return request_options possible_dbs = [db] if db else self.dbs_for_options(file_ext, rettype, retmode) if len(possible_dbs) > 1: raise NCBIFileException( 'Ambigious db for file extension specified: "{}"; possible databases include: {}'.format( file_ext, ", ".join(list(possible_dbs)) ) ) elif len(possible_dbs) == 1: likely_db = possible_dbs.pop() likely_options = self.options_for_db_and_extension( likely_db, file_ext, rettype, retmode ) if len(likely_options) == 1: request_options = {} request_options["db"] = likely_db request_options["rettype"] = likely_options[0]["rettype"] request_options["retmode"] = likely_options[0]["retmode"] request_options["ext"] = likely_options[0]["ext"] return request_options elif len(likely_options) > 1: raise NCBIFileException( "Please clarify the rettype and retmode. Multiple request types are possible for the file extension ({}) specified: {}".format( file_ext, likely_options ) ) else: raise NCBIFileException( "No request options found. Please check the file extension ({}), db ({}), rettype ({}), and retmode ({}) specified.".format( file_ext, db, rettype, retmode ) ) def is_valid_db_request(self, db, rettype, retmode): if not self.is_valid_db(db): raise NCBIFileException( "DB specified is not valid. Options include: {dbs}".format( dbs=", ".join(self.valid_dbs) ) ) db_options = self.efetch_options[db] for opt in db_options: if opt["rettype"] == rettype and opt["retmode"] == retmode: return True return False @property def valid_dbs(self): return self.efetch_options.keys() def is_valid_db(self, db): return db in self.valid_dbs def parse_accession_str(self, id_str): """ This tries to match an NCBI accession as defined here: http://www.ncbi.nlm.nih.gov/Sequin/acc.html """ m = re.search( r"(?P(?:[a-zA-Z]{1,6}|NW_|NC_|NM_|NR_)\d{1,10})(?:\.(?P\d+))?(?:\.(?P\S+))?.*", id_str, ) accession, version, file_ext = ("", "", "") if m: accession = m.group("accession") version = m.group("version") file_ext = m.group("file_ext") assert ( file_ext ), "file_ext must be defined: {}.{}.. Possible values include: {}".format( accession, version, ", ".join(list(self.valid_extensions)) ) assert version, "version must be defined: {}..{}".format( accession, file_ext ) return accession, version, file_ext @staticmethod def _seq_chunks(seq, n): # http://stackoverflow.com/a/312464/190597 (Ned Batchelder) """ Yield successive n-sized chunks from seq.""" for i in range(0, len(seq), n): yield seq[i : i + n] def _esummary_and_parse( self, accession, xpath_selector, db="nuccore", return_type=int, raise_on_failure=True, retmode="xml", **kwargs ): result = self.entrez.esummary(db=db, id=accession, **kwargs) root = ET.fromstring(result.read()) nodes = root.findall(xpath_selector) retval = 0 if len(nodes): retval = return_type(nodes[0].text) else: if raise_on_failure: raise NCBIFileException("The esummary query failed.") return retval def exists(self, accession, db="nuccore"): result = self.entrez.esearch(db=db, term=accession, rettype="count") root = ET.fromstring(result.read()) nodes = root.findall(".//Count") count = 0 if len(nodes): count = int(nodes[0].text) else: raise NCBIFileException("The esummary query failed.") if count == 1: return True else: logger.warning( 'The accession specified, "{acc}", could not be found in the database "{db}".\nConsider if you may need to specify a different database via "db=".'.format( acc=accession, db=db ) ) return False def size(self, accession, db="nuccore"): return self._esummary_and_parse(accession, ".//*[@Name='Length']", db=db) def mtime(self, accession, db="nuccore"): update_date = self._esummary_and_parse( accession, ".//Item[@Name='UpdateDate']", db=db, return_type=str ) pattern = "%Y/%m/%d" epoch_update_date = int(time.mktime(time.strptime(update_date, pattern))) return epoch_update_date def fetch_from_ncbi( self, accession_list, destination_dir, force_overwrite=False, rettype="fasta", retmode="text", file_ext=None, combined_file_prefix=None, remove_separate_files=False, chunk_size=1, db="nuccore", **kwargs ): """ This function downloads and saves files from NCBI. Adapted in part from the BSD-licensed code here: https://github.com/broadinstitute/viral-ngs/blob/master/util/genbank.py """ max_chunk_size = 500 # Conform to NCBI retreival guidelines by chunking into 500-accession chunks if # >500 accessions are specified and chunk_size is set to 1 # Also clamp chunk size to 500 if the user specified a larger value. if chunk_size > max_chunk_size or ( len(accession_list) > max_chunk_size and chunk_size == 1 ): chunk_size = max_chunk_size outEx = {"fasta": "fasta", "ft": "tbl", "gb": "gbk"} output_directory = os.path.abspath(os.path.expanduser(destination_dir)) if not os.path.exists(output_directory): os.makedirs(output_directory) output_extension = str(file_ext) # ensure the extension starts with a ".", also allowing for passed-in # extensions that already have it if output_extension[:1] != ".": output_extension = "." + output_extension logger.info( "Fetching {} entries from NCBI: {}\n".format( str(len(accession_list)), ", ".join(accession_list[:10]) ) ) output_files = [] for chunk_num, chunk in enumerate(self._seq_chunks(accession_list, chunk_size)): # sleep to throttle requests to 2 per second per NCBI guidelines: # https://www.ncbi.nlm.nih.gov/books/NBK25497/#chapter2.Usage_Guidelines_and_Requiremen time.sleep(0.5) acc_string = ",".join(chunk) # if the filename would be longer than Linux allows, simply say "chunk-chunk_num" if len(acc_string) + len(output_extension) <= 254: output_file_path = os.path.join( output_directory, acc_string + output_extension ) else: output_file_path = os.path.join( output_directory, "chunk-{}".format(chunk_num) + output_extension ) if not force_overwrite: logger.info("not overwriting, checking for existence") assert not os.path.exists(output_file_path), ( """File %s already exists. Consider removing this file or specifying a different output directory. The files for the accessions specified can be overwritten if you add force_overwrite flag. Processing aborted.""" % output_file_path ) try_count = 1 while True: try: logger.info( "Fetching file {}: {}, try #{}".format( chunk_num + 1, acc_string, try_count ) ) handle = self.entrez.efetch( db=db, rettype=rettype, retmode=retmode, id=acc_string, **kwargs ) with open(output_file_path, "w") as outf: for line in handle: outf.write(line) output_files.append(output_file_path) except IOError: logger.warning( "Error fetching file {}: {}, try #{} probably because NCBI is too busy.".format( chunk_num + 1, acc_string, try_count ) ) try_count += 1 if try_count > 4: logger.warning("Tried too many times. Aborting.") raise # if the fetch failed, wait a few seconds and try again. logger.info("Waiting and retrying...") time.sleep(2) continue break # assert that we are not trying to remove the intermediate files without writing a combined file if remove_separate_files: assert combined_file_prefix, """The intermediate files can only be removed if a combined file is written via combined_file_prefix""" # build a path to the combined genome file if combined_file_prefix: concatenated_genome_file_path = os.path.join( output_directory, combined_file_prefix + output_extension ) if not force_overwrite: assert not os.path.exists(concatenated_genome_file_path), ( """File %s already exists. Consider removing this file or specifying a different output directory. The files for the accessions specified can be overwritten if you add force_overwrite flag. Processing aborted.""" % output_file_path ) # concatenate the files together into one genome file with open(concatenated_genome_file_path, "w") as outfile: for file_path in output_files: with open(file_path) as infile: for line in infile: outfile.write(line) # if the option is specified, remove the intermediate fasta files if remove_separate_files: while len(output_files) > 0: os.unlink(output_files.pop()) # add the combined file to the list of files returned output_files.append(concatenated_genome_file_path) # return list of files return output_files def search(self, query, *args, db="nuccore", idtype="acc", **kwargs): # enforce JSON return mode kwargs["retmode"] = "json" # if the user specifies retmax, use it and limit there # otherwise page 200 at a time and return all if "retmax" not in kwargs or not kwargs["retmax"]: kwargs["retmax"] = 100000 return_all = True else: return_all = False kwargs["retstart"] = kwargs.get("retstart", 0) def esearch_json(term, *args, **kwargs): handle = self.entrez.esearch(term=term, *args, **kwargs) json_result = json.loads(handle.read()) return json_result def result_ids(json): if ( "esearchresult" in json_results and "idlist" in json_results["esearchresult"] ): return json_results["esearchresult"]["idlist"] else: raise NCBIFileException("ESearch error") has_more = True while has_more: json_results = esearch_json( term=query, *args, db=db, idtype=idtype, **kwargs ) for acc in result_ids(json_results): yield acc if return_all and ( "count" in json_results["esearchresult"] and int(json_results["esearchresult"]["count"]) > kwargs["retmax"] + kwargs["retstart"] ): kwargs["retstart"] += kwargs["retmax"] # sleep to throttle requests to <2 per second per NCBI guidelines: # https://www.ncbi.nlm.nih.gov/books/NBK25497/#chapter2.Usage_Guidelines_and_Requiremen time.sleep(0.5) else: has_more = False snakemake-5.10.0/snakemake/remote/S3.py000066400000000000000000000307061361131222100176230ustar00rootroot00000000000000__author__ = "Christopher Tomkins-Tinch" __copyright__ = "Copyright 2015, Christopher Tomkins-Tinch" __email__ = "tomkinsc@broadinstitute.org" __license__ = "MIT" # built-ins import os import re import math import functools import concurrent.futures # module-specific from snakemake.remote import AbstractRemoteObject, AbstractRemoteProvider from snakemake.exceptions import WorkflowError, S3FileException try: # third-party modules import boto3 import botocore except ImportError as e: raise WorkflowError( "The Python 3 package 'boto3' " "needs to be installed to use S3 remote() file functionality. %s" % e.msg ) class RemoteProvider( AbstractRemoteProvider ): # class inherits from AbstractRemoteProvider supports_default = True # class variable def __init__( self, *args, keep_local=False, stay_on_remote=False, is_default=False, **kwargs ): super(RemoteProvider, self).__init__( *args, keep_local=keep_local, stay_on_remote=stay_on_remote, is_default=is_default, **kwargs ) # in addition to methods provided by AbstractRemoteProvider, we add these in self._s3c = S3Helper(*args, **kwargs) # _private variable by convention def remote_interface(self): return self._s3c @property # decorator, so that this function can be access as an attribute, instead of a method def default_protocol(self): """The protocol that is prepended to the path when no protocol is specified.""" return "s3://" @property # decorator, so that this function can be access as an attribute, instead of a method def available_protocols(self): """List of valid protocols for this remote provider.""" return ["s3://"] class RemoteObject(AbstractRemoteObject): """ This is a class to interact with the AWS S3 object store. """ def __init__(self, *args, keep_local=False, provider=None, **kwargs): super(RemoteObject, self).__init__( *args, keep_local=keep_local, provider=provider, **kwargs ) if provider: self._s3c = provider.remote_interface() else: self._s3c = S3Helper(*args, **kwargs) # === Implementations of abstract class members === def exists(self): if self._matched_s3_path: return self._s3c.exists_in_bucket(self.s3_bucket, self.s3_key) else: raise S3FileException( "The file cannot be parsed as an s3 path in form 'bucket/key': %s" % self.local_file() ) def mtime(self): if self.exists(): return self._s3c.key_last_modified(self.s3_bucket, self.s3_key) else: raise S3FileException( "The file does not seem to exist remotely: %s" % self.local_file() ) def size(self): if self.exists(): return self._s3c.key_size(self.s3_bucket, self.s3_key) else: return self._iofile.size_local def download(self): self._s3c.download_from_s3(self.s3_bucket, self.s3_key, self.local_file()) os.sync() # ensure flush to disk def upload(self): self._s3c.upload_to_s3( self.s3_bucket, self.local_file(), self.s3_key, extra_args=self.kwargs.get("ExtraArgs", None), config=self.kwargs.get("Config", None), ) @property def list(self): return self._s3c.list_keys(self.s3_bucket) # === Related methods === @property def _matched_s3_path(self): return re.search("(?P[^/]*)/(?P.*)", self.local_file()) @property def s3_bucket(self): if len(self._matched_s3_path.groups()) == 2: return self._matched_s3_path.group("bucket") return None @property def name(self): return self.s3_key @property def s3_key(self): if len(self._matched_s3_path.groups()) == 2: return self._matched_s3_path.group("key") def s3_create_stub(self): if self._matched_s3_path: if not self.exists: self._s3c.download_from_s3( self.s3_bucket, self.s3_key, self.file, create_stub_only=True ) else: raise S3FileException( "The file to be downloaded cannot be parsed as an s3 path in form 'bucket/key': %s" % self.local_file() ) class S3Helper(object): def __init__(self, *args, **kwargs): # as per boto, expects the environment variables to be set: # AWS_ACCESS_KEY_ID # AWS_SECRET_ACCESS_KEY # Otherwise these values need to be passed in as kwargs # allow key_id and secret to be specified with aws_, gs_, or no prefix. # Standardize to the aws_ prefix expected by boto. if "gs_access_key_id" in kwargs: kwargs["aws_access_key_id"] = kwargs.pop("gs_access_key_id") if "gs_secret_access_key" in kwargs: kwargs["aws_secret_access_key"] = kwargs.pop("gs_secret_access_key") if "access_key_id" in kwargs: kwargs["aws_access_key_id"] = kwargs.pop("access_key_id") if "secret_access_key" in kwargs: kwargs["aws_secret_access_key"] = kwargs.pop("secret_access_key") if "host" in kwargs: kwargs["endpoint_url"] = kwargs.pop("host") self.s3 = boto3.resource("s3", **kwargs) def bucket_exists(self, bucket_name): try: self.s3.meta.client.head_bucket(Bucket=bucket_name) return True except: return False def upload_to_s3( self, bucket_name, file_path, key=None, use_relative_path_for_key=True, relative_start_dir=None, extra_args=None, config=None, ): """ Upload a file to S3 This function uploads a file to an AWS S3 bucket. Args: bucket_name: the name of the S3 bucket to use (bucket name only, not ARN) file_path: The path to the file to upload. key: The key to set for the file on S3. If not specified, this will default to the name of the file. use_relative_path_for_key: If set to True (default), and key is None, the S3 key will include slashes representing the path of the file relative to the CWD. If False only the file basename will be used for the key. relative_start_dir: The start dir to use for use_relative_path_for_key. No effect if key is set. Returns: The key of the file on S3 if written, None otherwise """ file_path = os.path.realpath(os.path.expanduser(file_path)) assert bucket_name, "bucket_name must be specified" assert os.path.exists(file_path), ( "The file path specified does not exist: %s" % file_path ) assert os.path.isfile(file_path), ( "The file path specified does not appear to be a file: %s" % file_path ) if not self.bucket_exists(bucket_name): self.s3.create_bucket(Bucket=bucket_name) if not key: if use_relative_path_for_key: if relative_start_dir: path_key = os.path.relpath(file_path, relative_start_dir) else: path_key = os.path.relpath(file_path) else: path_key = os.path.basename(file_path) key = path_key k = self.s3.Object(bucket_name, key) try: k.upload_file(file_path, ExtraArgs=extra_args, Config=config) except: raise def download_from_s3( self, bucket_name, key, destination_path=None, expandKeyIntoDirs=True, make_dest_dirs=True, create_stub_only=False, ): """ Download a file from s3 This function downloads an object from a specified AWS S3 bucket. Args: bucket_name: the name of the S3 bucket to use (bucket name only, not ARN) destination_path: If specified, the file will be saved to this path, otherwise cwd. expandKeyIntoDirs: Since S3 keys can include slashes, if this is True (defult) then S3 keys with slashes are expanded into directories on the receiving end. If it is False, the key is passed to os.path.basename() to get the substring following the last slash. make_dest_dirs: If this is True (default) and the destination path includes directories that do not exist, they will be created. Returns: The destination path of the downloaded file on the receiving end, or None if the destination_path could not be downloaded """ assert bucket_name, "bucket_name must be specified" assert key, "Key must be specified" if destination_path: destination_path = os.path.realpath(os.path.expanduser(destination_path)) else: if expandKeyIntoDirs: destination_path = os.path.join(os.getcwd(), key) else: destination_path = os.path.join(os.getcwd(), os.path.basename(key)) # if the destination path does not exist if make_dest_dirs: os.makedirs(os.path.dirname(destination_path), exist_ok=True) k = self.s3.Object(bucket_name, key) try: if not create_stub_only: k.download_file(destination_path) else: # just create an empty file with the right timestamps with open(destination_path, "wb") as fp: os.utime( fp.name, (k.last_modified.timestamp(), k.last_modified.timestamp()), ) return destination_path except: return None def delete_from_bucket(self, bucket_name, key): """ Delete a file from s3 This function deletes an object from a specified AWS S3 bucket. Args: bucket_name: the name of the S3 bucket to use (bucket name only, not ARN) key: the key of the object to delete from the bucket Returns: The name of the object deleted """ assert bucket_name, "bucket_name must be specified" assert key, "Key must be specified" k = self.s3.Object(bucket_name, key) ret = k.delete() return ret.name def exists_in_bucket(self, bucket_name, key): """ Returns whether the key exists in the bucket Args: bucket_name: the name of the S3 bucket to use (bucket name only, not ARN) key: the key of the object to delete from the bucket Returns: True | False """ assert bucket_name, "bucket_name must be specified" assert key, "Key must be specified" try: self.s3.Object(bucket_name, key).load() except botocore.exceptions.ClientError as e: if e.response["Error"]["Code"] == "404": return False else: raise return True def key_size(self, bucket_name, key): """ Returns the size of a key based on a HEAD request Args: bucket_name: the name of the S3 bucket to use (bucket name only, not ARN) key: the key of the object to delete from the bucket Returns: Size in kb """ assert bucket_name, "bucket_name must be specified" assert key, "Key must be specified" k = self.s3.Object(bucket_name, key) return k.content_length // 1024 def key_last_modified(self, bucket_name, key): """ Returns a timestamp of a key based on a HEAD request Args: bucket_name: the name of the S3 bucket to use (bucket name only, not ARN) key: the key of the object to delete from the bucket Returns: timestamp """ assert bucket_name, "bucket_name must be specified" assert key, "Key must be specified" k = self.s3.Object(bucket_name, key) return k.last_modified.timestamp() def list_keys(self, bucket_name): b = self.s3.Bucket(bucket_name) return [o.key for o in b.objects.iterator()] snakemake-5.10.0/snakemake/remote/S3Mocked.py000066400000000000000000000105511361131222100207420ustar00rootroot00000000000000__author__ = "Christopher Tomkins-Tinch" __copyright__ = "Copyright 2015, Christopher Tomkins-Tinch" __email__ = "tomkinsc@broadinstitute.org" __license__ = "MIT" # built-ins import os, sys from contextlib import contextmanager import pickle import time import threading import functools # intra-module from snakemake.remote.S3 import ( RemoteObject as S3RemoteObject, RemoteProvider as S3RemoteProvider, ) from snakemake.remote.S3 import S3Helper from snakemake.decorators import dec_all_methods from snakemake.exceptions import WorkflowError try: # third-party import boto3 from moto import mock_s3 except ImportError as e: raise WorkflowError( "The Python 3 packages 'moto' and boto3' " + "need to be installed to use S3Mocked remote() file functionality. %s" % e.msg ) def noop(): pass def pickled_moto_wrapper(func): """ This is a class decorator that in turn decorates all methods within a class to mock out boto calls with moto-simulated ones. Since the moto backends are not presistent across calls by default, the wrapper also pickles the bucket state after each function call, and restores it before execution. This way uploaded files are available for follow-on tasks. Since snakemake may execute with multiple threads it also waits for the pickled bucket state file to be available before loading it in. This is a hackey alternative to using proper locks, but works ok in practice. """ def wrapper_func(self, *args, **kwargs): moto_context_file = "motoState.p" moto_context = mock_s3() moto_context.start() moto_context.backends["global"].reset = noop # load moto buckets from pickle if os.path.isfile(moto_context_file) and os.path.getsize(moto_context_file) > 0: with file_lock(moto_context_file): with open(moto_context_file, "rb") as f: moto_context.backends["global"].buckets = pickle.load(f) mocked_function = moto_context(func) retval = mocked_function(self, *args, **kwargs) with file_lock(moto_context_file): with open(moto_context_file, "wb") as f: pickle.dump(moto_context.backends["global"].buckets, f) moto_context.stop() return retval functools.update_wrapper(wrapper_func, func) wrapper_func.__wrapped__ = func return wrapper_func @dec_all_methods(pickled_moto_wrapper, prefix=None) class RemoteProvider(S3RemoteProvider): supports_default = True def __init__(self, *args, **kwargs): super(RemoteProvider, self).__init__(*args, **kwargs) @dec_all_methods(pickled_moto_wrapper, prefix=None) class RemoteObject(S3RemoteObject): """ This is a derivative of the S3 remote provider that mocks out boto-based S3 calls using the "moto" Python package. Only the initializer is different; it "uploads" the input test file to the moto-simulated bucket at the start. """ def __init__( self, *args, keep_local=False, stay_on_remote=False, provider=None, **kwargs ): super(RemoteObject, self).__init__( *args, keep_local=keep_local, stay_on_remote=False, provider=provider, **kwargs ) bucket_name = "test-remote-bucket" test_file = "test.txt" s3 = boto3.resource("s3") s3.create_bucket(Bucket=bucket_name) # "Upload" files that should be in S3 before tests... s3c = S3Helper() if not s3c.exists_in_bucket(bucket_name, test_file): s3c.upload_to_s3(bucket_name, test_file) # ====== Helpers ===== def touch(fname, mode=0o666, dir_fd=None, **kwargs): # create lock file faster # https://stackoverflow.com/a/1160227 flags = os.O_CREAT | os.O_APPEND with os.fdopen(os.open(fname, flags=flags, mode=mode, dir_fd=dir_fd)) as f: os.utime( f.fileno() if os.utime in os.supports_fd else fname, dir_fd=None if os.supports_fd else dir_fd, **kwargs ) @contextmanager def file_lock(filepath): lock_file = filepath + ".lock" while os.path.isfile(lock_file): time.sleep(2) touch(lock_file) try: yield finally: try: os.remove(lock_file) except OSError: pass snakemake-5.10.0/snakemake/remote/SFTP.py000066400000000000000000000127021361131222100201060ustar00rootroot00000000000000__author__ = "Christopher Tomkins-Tinch" __copyright__ = "Copyright 2015, Christopher Tomkins-Tinch" __email__ = "tomkinsc@broadinstitute.org" __license__ = "MIT" import os from contextlib import contextmanager # module-specific from snakemake.remote import AbstractRemoteProvider, DomainObject from snakemake.exceptions import SFTPFileException, WorkflowError try: # third-party modules import pysftp except ImportError as e: raise WorkflowError( "The Python 3 package 'pysftp' " + "must be installed to use SFTP remote() file functionality. %s" % e.msg ) class RemoteProvider(AbstractRemoteProvider): supports_default = True allows_directories = True def __init__( self, *args, keep_local=False, stay_on_remote=False, is_default=False, **kwargs ): super(RemoteProvider, self).__init__( *args, keep_local=keep_local, stay_on_remote=stay_on_remote, is_default=is_default, **kwargs ) @property def default_protocol(self): """The protocol that is prepended to the path when no protocol is specified.""" return "sftp://" @property def available_protocols(self): """List of valid protocols for this remote provider.""" return ["ssh://", "sftp://"] class RemoteObject(DomainObject): """ This is a class to interact with an SFTP server. """ def __init__(self, *args, keep_local=False, provider=None, **kwargs): super(RemoteObject, self).__init__( *args, keep_local=keep_local, provider=provider, **kwargs ) # === Implementations of abstract class members === @contextmanager # makes this a context manager. after 'yield' is __exit__() def sftpc(self): # if args have been provided to remote(), use them over those given to RemoteProvider() args_to_use = self.provider.args if len(self.args): args_to_use = self.args # use kwargs passed in to remote() to override those given to the RemoteProvider() # default to the host and port given as part of the file, falling back to one specified # as a kwarg to remote() or the RemoteProvider (overriding the latter with the former if both) kwargs_to_use = {} kwargs_to_use["host"] = self.host kwargs_to_use["port"] = int(self.port) if self.port else 22 for k, v in self.provider.kwargs.items(): kwargs_to_use[k] = v for k, v in self.kwargs.items(): kwargs_to_use[k] = v conn = pysftp.Connection(*args_to_use, **kwargs_to_use) yield conn conn.close() def exists(self): if self._matched_address: with self.sftpc() as sftpc: return sftpc.exists(self.remote_path) return False else: raise SFTPFileException( "The file cannot be parsed as an SFTP path in form 'host:port/path/to/file': %s" % self.local_file() ) def mtime(self): if self.exists(): with self.sftpc() as sftpc: # As per local operation, don't follow symlinks when reporting mtime attr = sftpc.lstat(self.remote_path) return int(attr.st_mtime) else: raise SFTPFileException( "The file does not seem to exist remotely: %s" % self.local_file() ) def is_newer(self, time): """ Returns true if the file is newer than time, or if it is a symlink that points to a file newer than time. """ with self.sftpc() as sftpc: return ( sftpc.stat(self.remote_path).st_mtime > time or sftpc.lstat(self.remote_path).st_mtime > time ) def size(self): if self.exists(): with self.sftpc() as sftpc: attr = sftpc.stat(self.remote_path) return int(attr.st_size) else: return self._iofile.size_local def download(self, make_dest_dirs=True): with self.sftpc() as sftpc: if self.exists(): # if the destination path does not exist if make_dest_dirs: os.makedirs(os.path.dirname(self.local_path), exist_ok=True) sftpc.get( remotepath=self.remote_path, localpath=self.local_path, preserve_mtime=True, ) os.sync() # ensure flush to disk else: raise SFTPFileException( "The file does not seem to exist remotely: %s" % self.local_file() ) def upload(self): with self.sftpc() as sftpc: sftpc.put( localpath=self.local_path, remotepath=self.remote_path, confirm=True, preserve_mtime=True, ) @property def list(self): file_list = [] first_wildcard = self._iofile.constant_prefix() dirname = first_wildcard.replace(self.path_prefix, "") with self.sftpc() as sftpc: def _append_item(file_path): file_path = file_path.lstrip("/") file_list.append(file_path) sftpc.walktree( dirname, fcallback=_append_item, dcallback=_append_item, ucallback=_append_item, ) return file_list snakemake-5.10.0/snakemake/remote/XRootD.py000066400000000000000000000173721361131222100205210ustar00rootroot00000000000000__author__ = "Chris Burr" __copyright__ = "Copyright 2017, Chris Burr" __email__ = "christopher.burr@cern.ch" __license__ = "MIT" import os from os.path import abspath, join, normpath import re from snakemake.remote import AbstractRemoteObject, AbstractRemoteProvider from snakemake.exceptions import WorkflowError, XRootDFileException try: from XRootD import client from XRootD.client.flags import DirListFlags, MkDirFlags, StatInfoFlags except ImportError as e: raise WorkflowError( "The Python 3 package 'XRootD' must be installed to use XRootD " "remote() file functionality. %s" % e.msg ) class RemoteProvider(AbstractRemoteProvider): def __init__( self, *args, keep_local=False, stay_on_remote=False, is_default=False, **kwargs ): super(RemoteProvider, self).__init__( *args, keep_local=keep_local, stay_on_remote=stay_on_remote, is_default=is_default, **kwargs ) self._xrd = XRootDHelper() def remote_interface(self): return self._xrd @property def default_protocol(self): """The protocol that is prepended to the path when no protocol is specified.""" return "root://" @property def available_protocols(self): """List of valid protocols for this remote provider.""" return ["root://", "roots://", "rootk://"] class RemoteObject(AbstractRemoteObject): """ This is a class to interact with XRootD servers.""" def __init__( self, *args, keep_local=False, stay_on_remote=False, provider=None, **kwargs ): super(RemoteObject, self).__init__( *args, keep_local=keep_local, stay_on_remote=stay_on_remote, provider=provider, **kwargs ) if provider: self._xrd = provider.remote_interface() else: self._xrd = XRootDHelper() # === Implementations of abstract class members === def exists(self): return self._xrd.exists(self.remote_file()) def mtime(self): if self.exists(): return self._xrd.file_last_modified(self.remote_file()) else: raise XRootDFileException( "The file does not seem to exist remotely: %s" % self.remote_file() ) def size(self): if self.exists(): return self._xrd.file_size(self.remote_file()) else: return self._iofile.size_local def download(self): assert not self.stay_on_remote self._xrd.copy(self.remote_file(), self.file()) def upload(self): assert not self.stay_on_remote self._xrd.copy(self.file(), self.remote_file()) @property def name(self): return self.local_file() @property def list(self): dirname = os.path.dirname(self._iofile.constant_prefix()) + "/" files = list(self._xrd.list_directory_recursive(dirname)) return [normpath(f) for f in files] def remove(self): self._xrd.remove(self.remote_file()) class XRootDHelper(object): def __init__(self): self._clients = {} def get_client(self, domain): try: return self._clients[domain] except KeyError: self._clients[domain] = client.FileSystem(domain) return self._clients[domain] def _parse_url(self, url): match = re.search( "(?P(?:[A-Za-z]+://)[A-Za-z0-9:\_\-\.]+\:?/)(?P/.+)", url ) if match is None: return None domain = match.group("domain") dirname, filename = os.path.split(match.group("path")) # We need a trailing / to keep XRootD happy dirname += "/" return domain, dirname, filename def exists(self, url): domain, dirname, filename = self._parse_url(url) status, dirlist = self.get_client(domain).dirlist(dirname) if not status.ok: if status.errno == 3011: return False else: raise XRootDFileException( "Error listing directory " + dirname + " on domain " + domain + "\n" + repr(status) + "\n" + repr(dirlist) ) return filename in [f.name for f in dirlist.dirlist] def _get_statinfo(self, url): domain, dirname, filename = self._parse_url(url) matches = [ f for f in self.list_directory(domain, dirname) if f.name == filename ] assert len(matches) == 1 return matches[0].statinfo def file_last_modified(self, filename): return self._get_statinfo(filename).modtime def file_size(self, filename): return self._get_statinfo(filename).size def copy(self, source, destination): # Prepare the source path for XRootD if not self._parse_url(source): source = abspath(source) # Prepare the destination path for XRootD assert os.path.basename(source) == os.path.basename(destination) if self._parse_url(destination): domain, dirname, filename = self._parse_url(destination) self.makedirs(domain, dirname) else: destination = abspath(destination) if not os.path.isdir(os.path.dirname(destination)): os.makedirs(os.path.dirname(destination)) # Perform the copy operation process = client.CopyProcess() process.add_job(source, destination) process.prepare() status, returns = process.run() if not status.ok or not returns[0]["status"].ok: raise XRootDFileException( "Error copying from " + source + " to " + destination, repr(status), repr(returns), ) def makedirs(self, domain, dirname): print("Making directories", domain, dirname) assert dirname.endswith("/") status, _ = self.get_client(domain).mkdir(dirname, MkDirFlags.MAKEPATH) if not status.ok: raise XRootDFileException( "Failed to create directory " + dirname, repr(status) ) def list_directory(self, domain, dirname): status, dirlist = self.get_client(domain).dirlist(dirname, DirListFlags.STAT) if not status.ok: raise XRootDFileException( "Error listing directory " + dirname + " on domain " + domain + "\n" + repr(status) + "\n" + repr(dirlist) ) return dirlist.dirlist def list_directory_recursive(self, start_url): assert start_url.endswith("/") domain, dirname, filename = self._parse_url(start_url) assert not filename filename = join(dirname, filename) for f in self.list_directory(domain, dirname): if f.statinfo.flags & StatInfoFlags.IS_DIR: for _f_name in self.list_directory_recursive( domain + dirname + f.name + "/" ): yield _f_name else: # Only yield files as directories don't have timestamps on XRootD yield domain + dirname + f.name def remove(self, url): domain, dirname, filename = self._parse_url(url) filename = join(dirname, filename) status, _ = self.get_client(domain).rm(filename) if not status.ok: raise XRootDFileException( "Failed to remove file " + filename + " from remote " + domain + "\n" + repr(status) ) snakemake-5.10.0/snakemake/remote/__init__.py000066400000000000000000000200161361131222100210660ustar00rootroot00000000000000__author__ = "Christopher Tomkins-Tinch" __copyright__ = "Copyright 2015, Christopher Tomkins-Tinch" __email__ = "tomkinsc@broadinstitute.org" __license__ = "MIT" # built-ins import os import sys import re from abc import ABCMeta, abstractmethod from wrapt import ObjectProxy import copy # module-specific import snakemake.io class StaticRemoteObjectProxy(ObjectProxy): """Proxy that implements static-ness for remote objects. The constructor takes a real RemoteObject and returns a proxy that behaves the same except for the exists() and mtime() methods. """ def exists(self): return True def mtime(self): return float("-inf") def is_newer(self, time): return False def __copy__(self): copied_wrapped = copy.copy(self.__wrapped__) return type(self)(copied_wrapped) def __deepcopy__(self): copied_wrapped = copy.deepcopy(self.__wrapped__) return type(self)(copied_wrapped) class AbstractRemoteProvider: """ This is an abstract class to be used to derive remote provider classes. These might be used to hold common credentials, and are then passed to RemoteObjects. """ __metaclass__ = ABCMeta supports_default = False allows_directories = False def __init__( self, *args, keep_local=False, stay_on_remote=False, is_default=False, **kwargs ): self.args = args self.stay_on_remote = stay_on_remote self.keep_local = keep_local self.is_default = is_default self.kwargs = kwargs def remote( self, value, *args, keep_local=None, stay_on_remote=None, static=False, **kwargs ): if snakemake.io.is_flagged(value, "temp"): raise SyntaxError("Remote and temporary flags are mutually exclusive.") if snakemake.io.is_flagged(value, "protected"): raise SyntaxError("Remote and protected flags are mutually exclusive.") if keep_local is None: keep_local = self.keep_local if stay_on_remote is None: stay_on_remote = self.stay_on_remote def _set_protocol(value): """Adds the default protocol to `value` if it doesn't already have one""" protocol = self.default_protocol for p in self.available_protocols: if value.startswith(p): value = value[len(p) :] protocol = p break return protocol, value if isinstance(value, str): protocol, value = _set_protocol(value) value = protocol + value if stay_on_remote else value else: protocol, value = list(zip(*[_set_protocol(v) for v in value])) if len(set(protocol)) != 1: raise SyntaxError("A single protocol must be used per RemoteObject") protocol = set(protocol).pop() value = [protocol + v if stay_on_remote else v for v in value] if "protocol" not in kwargs: if "protocol" not in self.kwargs: kwargs["protocol"] = protocol else: kwargs["protocol"] = self.kwargs["protocol"] provider = sys.modules[self.__module__] # get module of derived class remote_object = provider.RemoteObject( *args, keep_local=keep_local, stay_on_remote=stay_on_remote, provider=self, **kwargs ) if static: remote_object = StaticRemoteObjectProxy(remote_object) return snakemake.io.flag(value, "remote_object", remote_object) def glob_wildcards(self, pattern, *args, **kwargs): args = self.args if not args else args kwargs = self.kwargs if not kwargs else kwargs referenceObj = snakemake.io._IOFile(self.remote(pattern, *args, **kwargs)) remote_object = snakemake.io.get_flag_value(referenceObj, "remote_object") if not remote_object.stay_on_remote: pattern = "./" + remote_object.name pattern = os.path.normpath(pattern) key_list = [k for k in remote_object.list] return snakemake.io.glob_wildcards(pattern, files=key_list) @abstractmethod def default_protocol(self): """The protocol that is prepended to the path when no protocol is specified.""" pass @abstractmethod def available_protocols(self): """List of valid protocols for this remote provider.""" pass @abstractmethod def remote_interface(self): pass class AbstractRemoteObject: """ This is an abstract class to be used to derive remote object classes for different cloud storage providers. For example, there could be classes for interacting with Amazon AWS S3 and Google Cloud Storage, both derived from this common base class. """ __metaclass__ = ABCMeta def __init__( self, *args, protocol=None, keep_local=False, stay_on_remote=False, provider=None, **kwargs ): assert protocol is not None # self._iofile must be set before the remote object can be used, in io.py or elsewhere self._iofile = None self.args = args self.kwargs = kwargs self.keep_local = keep_local self.stay_on_remote = stay_on_remote self.provider = provider self.protocol = protocol @property def _file(self): if self._iofile is None: return None return self._iofile._file def file(self): return self._file def local_file(self): if self.stay_on_remote: return self._file[len(self.protocol) :] else: return self._file def remote_file(self): return self.protocol + self.local_file() @abstractmethod def close(self): pass @abstractmethod def exists(self): pass @abstractmethod def mtime(self): pass @abstractmethod def size(self): pass @abstractmethod def download(self, *args, **kwargs): pass @abstractmethod def upload(self, *args, **kwargs): pass @abstractmethod def list(self, *args, **kwargs): pass @abstractmethod def name(self, *args, **kwargs): pass @abstractmethod def remote(self, value, keep_local=False, stay_on_remote=False): pass @abstractmethod def remove(self): raise NotImplementedError("Removal of files is unavailable for this remote") def local_touch_or_create(self): self._iofile.touch_or_create() class DomainObject(AbstractRemoteObject): """This is a mixin related to parsing components out of a location path specified as (host|IP):port/remote/location """ def __init__(self, *args, **kwargs): super(DomainObject, self).__init__(*args, **kwargs) @property def _matched_address(self): return re.search( "^(?P[a-zA-Z]+\://)?(?P[A-Za-z0-9\-\.]+)(?:\:(?P[0-9]+))?(?P.*)$", self.local_file(), ) @property def name(self): return self.path_remainder # if we ever parse out the protocol directly # @property # def protocol(self): # if self._matched_address: # return self._matched_address.group("protocol") @property def host(self): if self._matched_address: return self._matched_address.group("host") @property def port(self): if self._matched_address: return self._matched_address.group("port") @property def path_prefix(self): # this is the domain and port, however specified before the path remainder return self._iofile._file[: self._iofile._file.index(self.path_remainder)] @property def path_remainder(self): if self._matched_address: return self._matched_address.group("path_remainder") @property def local_path(self): return self._iofile._file @property def remote_path(self): return self.path_remainder snakemake-5.10.0/snakemake/remote/dropbox.py000066400000000000000000000131701361131222100210070ustar00rootroot00000000000000__author__ = "Christopher Tomkins-Tinch" __copyright__ = "Copyright 2015, Christopher Tomkins-Tinch" __email__ = "tomkinsc@broadinstitute.org" __license__ = "MIT" import os # module-specific from snakemake.remote import AbstractRemoteProvider, AbstractRemoteObject from snakemake.exceptions import DropboxFileException, WorkflowError try: # third-party modules import dropbox # The official Dropbox API library except ImportError as e: raise WorkflowError( "The Python 3 package 'dropbox' " "must be installed to use Dropbox remote() file " "functionality. %s" % e.msg ) class RemoteProvider(AbstractRemoteProvider): def __init__( self, *args, keep_local=False, stay_on_remote=False, is_default=False, **kwargs ): super(RemoteProvider, self).__init__( *args, keep_local=keep_local, stay_on_remote=stay_on_remote, is_default=is_default, **kwargs ) self._dropboxc = dropbox.Dropbox(*args, **kwargs) try: self._dropboxc.users_get_current_account() except dropbox.exceptions.AuthError as err: DropboxFileException( "ERROR: Invalid Dropbox OAuth access token; try re-generating an access token from the app console on the web." ) def remote_interface(self): return self._dropboxc @property def default_protocol(self): """The protocol that is prepended to the path when no protocol is specified.""" return "dropbox://" @property def available_protocols(self): """List of valid protocols for this remote provider.""" return ["dropbox://"] class RemoteObject(AbstractRemoteObject): """ This is a class to interact with the Dropbox API. """ def __init__(self, *args, keep_local=False, provider=None, **kwargs): super(RemoteObject, self).__init__( *args, keep_local=keep_local, provider=provider, **kwargs ) if provider: self._dropboxc = provider.remote_interface() else: self._dropboxc = dropbox.Dropbox(*args, **kwargs) try: self._dropboxc.users_get_current_account() except dropbox.exceptions.AuthError as err: DropboxFileException( "ERROR: Invalid Dropbox OAuth access token; try re-generating an access token from the app console on the web." ) # === Implementations of abstract class members === def exists(self): try: metadata = self._dropboxc.files_get_metadata(self.dropbox_file()) return True except: return False def mtime(self): if self.exists(): metadata = self._dropboxc.files_get_metadata(self.dropbox_file()) epochTime = metadata.server_modified.timestamp() return epochTime else: raise DropboxFileException( "The file does not seem to exist remotely: %s" % self.dropbox_file() ) def size(self): if self.exists(): metadata = self._dropboxc.files_get_metadata(self.dropbox_file()) return int(metadata.size) else: return self._iofile.size_local def download(self, make_dest_dirs=True): if self.exists(): # if the destination path does not exist, make it if make_dest_dirs: os.makedirs(os.path.dirname(self.local_file()), exist_ok=True) self._dropboxc.files_download_to_file( self.local_file(), self.dropbox_file() ) os.sync() # ensure flush to disk else: raise DropboxFileException( "The file does not seem to exist remotely: %s" % self.dropbox_file() ) def upload(self, mode=dropbox.files.WriteMode("overwrite")): # Chunk file into 10MB slices because Dropbox does not accept more than 150MB chunks chunksize = 10000000 with open(self.local_file(), mode="rb") as f: data = f.read(chunksize) # Start upload session res = self._dropboxc.files_upload_session_start(data) offset = len(data) # Upload further chunks until file is complete while len(data) == chunksize: data = f.read(chunksize) self._dropboxc.files_upload_session_append(data, res.session_id, offset) offset += len(data) # Finish session and store in the desired path self._dropboxc.files_upload_session_finish( f.read(chunksize), dropbox.files.UploadSessionCursor(res.session_id, offset), dropbox.files.CommitInfo(path=self.dropbox_file(), mode=mode), ) def dropbox_file(self): return ( "/" + self.local_file() if not self.local_file().startswith("/") else self.local_file() ) @property def name(self): return self.local_file() @property def list(self): file_list = [] first_wildcard = self._iofile.constant_prefix() dirname = ( "/" + first_wildcard if not first_wildcard.startswith("/") else first_wildcard ) while "//" in dirname: dirname = dirname.replace("//", "/") dirname = dirname.rstrip("/") for item in self._dropboxc.files_list_folder(dirname, recursive=True).entries: file_list.append( os.path.join(os.path.dirname(item.path_lower), item.name).lstrip("/") ) return file_list snakemake-5.10.0/snakemake/remote/gfal.py000066400000000000000000000117121361131222100202430ustar00rootroot00000000000000__author__ = "Johannes Köster" __copyright__ = "Copyright 2017-2019, Johannes Köster" __email__ = "johannes.koester@tu-dortmund.de" __license__ = "MIT" import os import re import shutil import subprocess as sp from datetime import datetime import time from snakemake.remote import AbstractRemoteObject, AbstractRemoteProvider from snakemake.exceptions import WorkflowError from snakemake.common import lazy_property from snakemake.logging import logger if not shutil.which("gfal-copy"): raise WorkflowError( "The gfal-* commands need to be available for " "gfal remote support." ) class RemoteProvider(AbstractRemoteProvider): supports_default = True allows_directories = True def __init__( self, *args, keep_local=False, stay_on_remote=False, is_default=False, retry=5, **kwargs ): super(RemoteProvider, self).__init__( *args, keep_local=keep_local, stay_on_remote=stay_on_remote, is_default=is_default, **kwargs ) self.retry = retry @property def default_protocol(self): """The protocol that is prepended to the path when no protocol is specified.""" return "gsiftp://" @property def available_protocols(self): """List of valid protocols for this remote provider.""" # TODO gfal provides more. Extend this list. return ["gsiftp://", "srm://"] class RemoteObject(AbstractRemoteObject): mtime_re = re.compile(r"^\s*Modify: (.+)$", flags=re.MULTILINE) size_re = re.compile(r"^\s*Size: ([0-9]+).*$", flags=re.MULTILINE) def __init__(self, *args, keep_local=False, provider=None, **kwargs): super(RemoteObject, self).__init__( *args, keep_local=keep_local, provider=provider, **kwargs ) def _gfal(self, cmd, *args, retry=None, raise_workflow_error=True): if retry is None: retry = self.provider.retry _cmd = ["gfal-" + cmd] + list(args) for i in range(retry + 1): try: logger.debug(_cmd) return sp.run( _cmd, check=True, stderr=sp.PIPE, stdout=sp.PIPE ).stdout.decode() except sp.CalledProcessError as e: if i == retry: if raise_workflow_error: raise WorkflowError( "Error calling gfal-{}:\n{}".format(cmd, e.stderr.decode()) ) else: raise e else: # try again after some seconds time.sleep(1) continue # === Implementations of abstract class members === def exists(self): try: self._gfal( "ls", "-a", self.remote_file(), retry=0, raise_workflow_error=False ) except sp.CalledProcessError as e: if e.returncode == 2: # exit code 2 means no such file or directory return False else: raise WorkflowError( "Error calling gfal-ls:\n{}".format(e.stderr.decode()) ) # exit code 0 means that the file is present return True def _stat(self): stat = self._gfal("stat", self.remote_file()) return stat def mtime(self): # assert self.exists() stat = self._stat() mtime = self.mtime_re.search(stat).group(1) date = datetime.strptime(mtime, "%Y-%m-%d %H:%M:%S.%f") return date.timestamp() def size(self): # assert self.exists() stat = self._stat() size = self.size_re.search(stat).group(1) return int(size) def download(self): if self.exists(): if self.size() == 0: # Globus erroneously thinks that a transfer is incomplete if a # file is empty. Hence we manually touch the local file. self.local_touch_or_create() return self.local_file() # Download file. Wait for staging. source = self.remote_file() target = "file://" + os.path.abspath(self.local_file()) # disable all timeouts (file transfers can take a long time) self._gfal( "copy", "-p", "-f", "-n", "4", "-t", "0", "-T", "0", source, target ) os.sync() return self.local_file() return None def upload(self): target = self.remote_file() source = "file://" + os.path.abspath(self.local_file()) # disable all timeouts (file transfers can take a long time) self._gfal("copy", "-p", "-f", "-n", "4", "-t", "0", "-T", "0", source, target) @property def list(self): # TODO implement listing of remote files with patterns raise NotImplementedError() def host(self): return self.local_file().split("/")[0] snakemake-5.10.0/snakemake/remote/gridftp.py000066400000000000000000000047671361131222100210050ustar00rootroot00000000000000__author__ = "Johannes Köster" __copyright__ = "Copyright 2017-2019, Johannes Köster" __email__ = "johannes.koester@tu-dortmund.de" __license__ = "MIT" import os import subprocess as sp import time import shutil from snakemake.exceptions import WorkflowError from snakemake.logging import logger if not shutil.which("globus-url-copy"): raise WorkflowError( "The globus-url-copy command has to be available for " "gridftp remote support." ) if not shutil.which("gfal-ls"): raise WorkflowError( "The gfal-* commands need to be available for " "gridftp remote support." ) from snakemake.remote import gfal class RemoteProvider(gfal.RemoteProvider): pass class RemoteObject(gfal.RemoteObject): def _globus(self, *args): retry = self.provider.retry cmd = ["globus-url-copy"] + list(args) for i in range(retry + 1): try: logger.debug(" ".join(cmd)) return sp.run( cmd, check=True, stderr=sp.PIPE, stdout=sp.PIPE ).stdout.decode() except sp.CalledProcessError as e: if i == retry: raise WorkflowError( "Error calling globus-url-copy:\n{}".format( cmd, e.stderr.decode() ) ) else: # try again after some seconds time.sleep(1) continue def download(self): if self.exists(): if self.size() == 0: # Globus erroneously thinks that a transfer is incomplete if a # file is empty. Hence we manually touch the local file. self.local_touch_or_create() return self.local_file() # Download file. Wait for staging. source = self.remote_file() target = "file://" + os.path.abspath(self.local_file()) self._globus( "-parallel", "4", "-create-dest", "-recurse", "-dp", source, target ) os.sync() return self.local_file() return None def upload(self): target = self.remote_file() source = "file://" + os.path.abspath(self.local_file()) if self.exists(): # first delete file, such that globus does not fail self._gfal("rm", target) self._globus( "-parallel", "4", "-create-dest", "-recurse", "-dp", source, target ) snakemake-5.10.0/snakemake/remote/iRODS.py000066400000000000000000000207501361131222100202540ustar00rootroot00000000000000__author__ = "Oliver Stolpe" __copyright__ = "Copyright 2017, BIH Core Unit Bioinformatics" __email__ = "oliver.stolpe@bihealth.org" __license__ = "MIT" import os import re from contextlib import contextmanager from datetime import datetime, timedelta from pytz import timezone # module-specific from snakemake.remote import AbstractRemoteProvider, AbstractRemoteObject from snakemake.exceptions import WorkflowError try: # third-party modules from irods.session import iRODSSession from irods.meta import iRODSMeta from irods.models import DataObject from irods.exception import CollectionDoesNotExist, DataObjectDoesNotExist import irods.keywords as kw except ImportError as e: raise WorkflowError( "The Python 3 package 'python-irodsclient' " + "must be installed to use iRODS remote() file functionality. %s" % e.msg ) utc = datetime.utcfromtimestamp(0) def _irods_session(*args, **kwargs): try: irods_env_file = os.environ["IRODS_ENVIRONMENT_FILE"] except KeyError: irods_env_file = kwargs.get( "irods_env_file", os.path.expanduser("~/.irods/irods_environment.json") ) if not os.path.isfile(irods_env_file): raise WorkflowError( "Expecting iRODS configuration file in %s, but none found." % kwargs["irods_env_file"] ) with iRODSSession(irods_env_file=irods_env_file) as session: try: session.collections.get( os.path.join(os.sep, session.zone, "home", session.username) ) except ConnectionError as e: raise e return session class RemoteProvider(AbstractRemoteProvider): supports_default = True def __init__( self, *args, keep_local=False, stay_on_remote=False, is_default=False, **kwargs ): super(RemoteProvider, self).__init__( *args, keep_local=keep_local, stay_on_remote=stay_on_remote, is_default=is_default, **kwargs ) self._irods_session = _irods_session(*args, **kwargs) def remote_interface(self): return self._irods_session @property def default_protocol(self): """The protocol that is prepended to the path when no protocol is specified.""" return "irods://" @property def available_protocols(self): """List of valid protocols for this remote provider.""" return ["irods://"] class RemoteObject(AbstractRemoteObject): """ This is a class to interact with an iRODS server. """ def __init__(self, *args, keep_local=False, provider=None, **kwargs): super(RemoteObject, self).__init__( *args, keep_local=keep_local, provider=provider, **kwargs ) if provider: self._irods_session = provider.remote_interface() self._timezone = provider.kwargs.get("timezone") else: self._irods_session = _irods_session(*args, **kwargs) def exists(self): try: self._irods_session.data_objects.get(self.remote_path) return True except (CollectionDoesNotExist, DataObjectDoesNotExist): return False def _convert_time(self, timestamp, tz=None): dt = timestamp.replace(tzinfo=timezone("UTC")) if tz: dt = dt.astimezone(timezone(tz)) return dt def mtime(self): if self.exists(): obj = self._irods_session.data_objects.get(self.remote_path) meta = self._irods_session.metadata.get(DataObject, self.remote_path) # if mtime was set in metadata during upload, take this information # otherwise fall back to iRODS timestamp (upload time!) and change # timezone accordingly (iRODS might ignore the servers local timezone) for m in meta: if m.name == "mtime": mtime = float(m.value) break else: dt = self._convert_time(obj.modify_time, self._timezone) utc2 = self._convert_time(utc) mtime = (dt - utc2).total_seconds() return int(mtime) else: raise WorkflowError( "The file does not seem to exist remotely: %s" % self.local_file() ) def atime(self): if self.exists(): obj = self._irods_session.data_objects.get(self.remote_path) meta = self._irods_session.metadata.get(DataObject, self.remote_path) # if mtime was set in metadata during upload, take this information # otherwise fall back to iRODS timestamp (upload time!) and change # timezone accordingly (iRODS might ignore the servers local timezone) for m in meta: if m.name == "atime": atime = float(m.value) break else: dt = self._convert_time(obj.modify_time, self._timezone) utc2 = self._convert_time(utc) atime = (dt - utc2).total_seconds() return int(atime) else: raise WorkflowError("File doesn't exist remotely: %s" % self.local_file()) def is_newer(self, time): """ Returns true of the file is newer than time, or if it is a symlink that points to a file newer than time. """ return self.mtime() > time def size(self): if self.exists(): obj = self._irods_session.data_objects.get(self.remote_path) return int(obj.size) else: return self._iofile.size_local def download(self, make_dest_dirs=True): if self.exists(): if make_dest_dirs: os.makedirs(os.path.dirname(self.local_path), exist_ok=True) # force irods to overwrite existing file if this option is set opt = {} if self.kwargs.get("overwrite"): opt[kw.FORCE_FLAG_KW] = "" # get object and change timestamp obj = self._irods_session.data_objects.get( self.remote_path, self.local_path, options=opt ) os.utime(self.local_path, (self.atime(), self.mtime())) os.sync() else: raise WorkflowError( "The file does not seem to exist remotely: %s" % self.local_file() ) def upload(self): # get current local timestamp stat = os.stat(self.local_path) # create folder structure on remote folders = os.path.dirname(self.remote_path).split(os.sep)[1:] collpath = os.sep for folder in folders: collpath = os.path.join(collpath, folder) try: self._irods_session.collections.get(collpath) except: self._irods_session.collections.create(collpath) # upload file and store local timestamp in metadata since irods sets the files modification time to # the upload time rather than retaining the local modification time self._irods_session.data_objects.put(self.local_path, self.remote_path) # erase meta data (if exists) before adding it. there is no update routine available in the API for m in self._irods_session.metadata.get(DataObject, self.remote_path): if m.name in ("mtime", "atime", "ctime"): self._irods_session.metadata.remove( DataObject, self.remote_path, iRODSMeta(m.name, m.value, m.units) ) self._irods_session.metadata.add( DataObject, self.remote_path, iRODSMeta("mtime", str(stat.st_mtime), "s") ) self._irods_session.metadata.add( DataObject, self.remote_path, iRODSMeta("atime", str(stat.st_atime), "s") ) self._irods_session.metadata.add( DataObject, self.remote_path, iRODSMeta("ctime", str(stat.st_ctime), "s") ) @property def remote_path(self): return os.path.join(os.sep, self._irods_session.zone, self.local_file()) @property def name(self): return self.local_file() @property def local_path(self): return self.local_file() @property def list(self): file_list = [] first_wildcard = self._iofile.constant_prefix() dirname = os.path.dirname(first_wildcard) collection = self._irods_session.collections.get(dirname) for _, _, objs in collection.walk(): for obj in objs: file_list.append(obj.path.lstrip("/")) return file_list snakemake-5.10.0/snakemake/remote/webdav.py000066400000000000000000000164141361131222100206060ustar00rootroot00000000000000__author__ = "Christopher Tomkins-Tinch" __copyright__ = "Copyright 2017, Christopher Tomkins-Tinch" __email__ = "tomkinsc@broadinstitute.org" __license__ = "MIT" import os, sys import email.utils from contextlib import contextmanager import functools # module-specific from snakemake.remote import AbstractRemoteProvider, AbstractRemoteObject, DomainObject from snakemake.exceptions import WebDAVFileException, WorkflowError try: # third-party modules import aioeasywebdav import asyncio except ImportError as e: raise WorkflowError( "The Python 3 packages 'aioeasywebdav' " " and 'asyncio' must be present to use WebDAV remote() file " "functionality. %s" % e.msg ) class RemoteProvider(AbstractRemoteProvider): def __init__( self, *args, keep_local=False, stay_on_remote=False, is_default=False, **kwargs ): # loop = asyncio.get_event_loop() super(RemoteProvider, self).__init__( *args, keep_local=keep_local, stay_on_remote=stay_on_remote, is_default=is_default, **kwargs ) @property def default_protocol(self): """The protocol that is prepended to the path when no protocol is specified.""" return "https://" @property def available_protocols(self): """List of valid protocols for this remote provider.""" return ["http://", "https://"] class RemoteObject(DomainObject): """ This is a class to interact with a WebDAV file store. """ def __init__(self, *args, keep_local=False, **kwargs): # self.loop = asyncio.get_event_loop() super(RemoteObject, self).__init__(*args, keep_local=keep_local, **kwargs) @contextmanager def webdavc(self): newloop = False if not hasattr(self, "loop"): try: self.loop = asyncio.get_event_loop() if self.loop.is_running(): raise NotImplementedError( "Cannot use aioutils in " "asynchroneous environment" ) except: newloop = True self.loop = asyncio.new_event_loop() asyncio.set_event_loop(self.loop) self.loop = asyncio.new_event_loop() asyncio.set_event_loop(self.loop) if not hasattr(self, "conn") or ( hasattr(self, "conn") and not isinstance(self.conn, aioeasywebdav.Client) ): # if args have been provided to remote(), use them over those given to RemoteProvider() args_to_use = self.provider.args if len(self.args): args_to_use = self.args # use kwargs passed in to remote() to override those given to the RemoteProvider() # default to the host and port given as part of the file, falling back to one specified # as a kwarg to remote() or the RemoteProvider (overriding the latter with the former if both) kwargs_to_use = {} kwargs_to_use["host"] = self.host kwargs_to_use["protocol"] = self.protocol kwargs_to_use["port"] = int(self.port) if self.port != None else 443 for k, v in self.provider.kwargs.items(): kwargs_to_use[k] = v for k, v in self.kwargs.items(): kwargs_to_use[k] = v # easywebdav wants the protocol without "://" kwargs_to_use["protocol"] = kwargs_to_use["protocol"].replace("://", "") # monkey patch aioeasywebdav to noop _rate_calc() # since we don't care about download progress and # the parent (connection) object may be removed before the # sleep coroutine has a chance to be scheduled/finish, # and aioeasywebdav only calls close() on __del__() async def noop(_): pass aioeasywebdav.Client._rate_calc = noop self.conn = aioeasywebdav.connect(*args_to_use, **kwargs_to_use) yield # === Implementations of abstract class members === def exists(self): with self.webdavc() as webdavc: path_to_try = self.webdav_file return self.loop.run_until_complete(self.conn.exists(self.webdav_file)) def mtime(self): if self.exists(): with self.webdavc() as webdavc: metadata = self.loop.run_until_complete( self.conn.ls(remote_path=self.webdav_file) )[0] parsed_date = email.utils.parsedate_tz(metadata.mtime) epoch_time = email.utils.mktime_tz(parsed_date) return epoch_time else: raise EasyWebDAVFileException( "The file does not seem to exist remotely: %s" % self.webdav_file ) def size(self): if self.exists(): with self.webdavc() as webdavc: metadata = self.loop.run_until_complete( self.conn.ls(remote_path=self.webdav_file) )[0] return int(metadata.size) else: return self._iofile.size_local def download(self, make_dest_dirs=True): if self.exists(): # if the destination path does not exist, make it if make_dest_dirs: os.makedirs(os.path.dirname(self.local_file()), exist_ok=True) with self.webdavc() as webdavc: self.loop.run_until_complete( self.conn.download(self.webdav_file, self.local_file()) ) os.sync() # ensure flush to disk else: raise EasyWebDAVFileException( "The file does not seem to exist remotely: %s" % self.webdav_file ) def upload(self): # make containing folder with self.webdavc() as webdavc: self.loop.run_until_complete( self.conn.mkdirs(os.path.dirname(self.webdav_file)) ) self.loop.run_until_complete( self.conn.upload(self.local_file(), self.webdav_file) ) @property def webdav_file(self): filepath = ( self.local_file().replace(self.host, "").replace(":" + str(self.port), "") ) filepath = filepath if not filepath.startswith("/") else filepath[1:] return filepath @property def name(self): return self.local_file() @property def list(self): file_list = [] first_wildcard = ( self._iofile.constant_prefix() .replace(self.host, "") .replace(":" + str(self.port), "") ) dirname = ( first_wildcard[1:] if first_wildcard.startswith("/") else first_wildcard ) while "//" in dirname: dirname = dirname.replace("//", "/") dirname = dirname.rstrip("/") + "/" with self.webdavc() as webdavc: for item in self.loop.run_until_complete(self.conn.ls(dirname)): file_list.append( os.path.join(os.path.dirname(dirname), item.name.lstrip("/")) ) file_list.append( os.path.join( self._iofile.constant_prefix(), os.path.basename(item.name) ) ) return file_list snakemake-5.10.0/snakemake/report.css000066400000000000000000000045431361131222100175160ustar00rootroot00000000000000/** Credits for the colors and font selection go to the Twitter Bootstrap framework. */ body { color: rgb(51, 51, 51); font-size: 10pt; padding-top: 10px; font-family: "Helvetica Neue",Helvetica,Arial,sans-serif; } h1 { font-size: 150%; } h2 { font-size: 140%; } h3 { font-size: 130%; } h4 { font-size: 120%; } h5 { font-size: 110%; } h6 { font-size: 100%; } div#attachments { display: inline-block; color: gray; border-width: 1px; border-style: solid; border-color: white; border-radius: 4px 4px 4px 4px; padding: 0px; } div#attachments dt { margin-top: 2px; margin-bottom: 2px; } div#attachments dd p { margin-top: 2px; margin-bottom: 2px; } div#attachments :target dt { font-weight: bold; } div#attachments :target a { color: rgb(70, 136, 71); } h1.title { text-align: center; font-size: 180%; } div.document { position: relative; background: white; max-width: 800px; margin: auto; padding: 20px; border: 1px solid rgb(221, 221, 221); border-radius: 4px 4px 4px 4px; } div.document:after { content: "snakemake report"; position: absolute; top: -1px; right: -1px; padding: 3px 7px; background-color: #f5f5f5; border: 1px solid rgb(221, 221, 221); color: #9da0a4; font-weight: bold; font-size: 12pt; border-radius: 0 0 0 4px; } div.document p { text-align: justify; } div#metadata { text-align: right; } table.docutils { border: none; border-collapse: collapse; border-top: 2px solid gray; border-bottom: 2px solid gray; text-align: center; } table.docutils th { border: none; border-top: 2px solid gray; border-bottom: 2px solid gray; padding: 5px; } table.docutils td { border: none; padding: 5px; } table.docutils th:last-child, td:last-child { text-align: left; } table.docutils th:first-child, td:first-child { text-align: right; } table.docutils th:only-child, td:only-child { text-align: center; } table.docutils.footnote { border: none; text-align: left; } a { color: rgb(0, 136, 204); text-decoration: none; } a:hover { color: rgb(0, 85, 128); text-decoration: underline; } div.figure { margin-left: 2em; margin-right: 2em; } img { max-width: 100%; } p.caption { font-style: italic; } snakemake-5.10.0/snakemake/report/000077500000000000000000000000001361131222100167765ustar00rootroot00000000000000snakemake-5.10.0/snakemake/report/__init__.py000066400000000000000000000535251361131222100211210ustar00rootroot00000000000000__author__ = "Johannes Köster" __copyright__ = "Copyright 2015-2019, Johannes Köster" __email__ = "koester@jimmy.harvard.edu" __license__ = "MIT" import os import sys import mimetypes import base64 import textwrap import datetime import io import uuid import json import time import shutil import subprocess as sp import itertools import csv from collections import namedtuple, defaultdict import requests from docutils.parsers.rst.directives.images import Image, Figure from docutils.parsers.rst import directives from docutils.core import publish_file, publish_parts from snakemake import script, wrapper from snakemake.utils import format from snakemake.logging import logger from snakemake.io import is_flagged, get_flag_value from snakemake.exceptions import WorkflowError from snakemake.script import Snakemake from snakemake import __version__ from snakemake.common import num_if_possible from snakemake import logging class EmbeddedMixin(object): """ Replaces the URI of a directive with a base64-encoded version. Useful for embedding images/figures in reports. """ def run(self): """ Image.run() handles most of the """ result = Image.run(self) reference = directives.uri(self.arguments[0]) self.options["uri"] = data_uri_from_file(reference) return result # Create (and register) new image:: and figure:: directives that use a base64 # data URI instead of pointing to a filename. class EmbeddedImage(Image, EmbeddedMixin): pass directives.register_directive("embeddedimage", EmbeddedImage) class EmbeddedFigure(Figure, EmbeddedMixin): pass directives.register_directive("embeddedfigure", EmbeddedFigure) def data_uri(data, filename, encoding="utf8", mime="text/plain"): """Craft a base64 data URI from file with proper encoding and mimetype.""" data = base64.b64encode(data) uri = "data:{mime};charset={charset};filename={filename};base64,{data}" "".format( filename=filename, mime=mime, charset=encoding, data=data.decode("utf-8") ) return uri def mime_from_file(file): mime, encoding = mimetypes.guess_type(file) if mime is None: mime = "text/plain" logger.info( "Could not detect mimetype for {}, assuming " "text/plain.".format(file) ) return mime, encoding def data_uri_from_file(file, defaultenc="utf8"): """Craft a base64 data URI from file with proper encoding and mimetype.""" mime, encoding = mime_from_file(file) if encoding is None: encoding = defaultenc with open(file, "rb") as f: return data_uri(f.read(), os.path.basename(file), encoding, mime) def report( text, path, stylesheet=None, defaultenc="utf8", template=None, metadata=None, **files ): if stylesheet is None: os.path.join(os.path.dirname(__file__), "report.css") outmime, _ = mimetypes.guess_type(path) if outmime != "text/html": raise ValueError("Path to report output has to be an HTML file.") definitions = textwrap.dedent( """ .. role:: raw-html(raw) :format: html """ ) metadata = textwrap.dedent( """ .. container:: :name: metadata {metadata}{date} """ ).format( metadata=metadata + " | " if metadata else "", date=datetime.date.today().isoformat(), ) text = format(textwrap.dedent(text), stepout=3) attachments = [] if files: attachments = [ textwrap.dedent( """ .. container:: :name: attachments """ ) ] for name, _files in sorted(files.items()): if not isinstance(_files, list): _files = [_files] links = [] for file in sorted(_files): data = data_uri_from_file(file) links.append( ':raw-html:`{filename}`'.format( data=data, filename=os.path.basename(file) ) ) links = "\n\n ".join(links) attachments.append( """ .. container:: :name: {name} {name}: {links} """.format( name=name, links=links ) ) text = definitions + text + "\n\n" + "\n\n".join(attachments) + metadata overrides = dict() if template is not None: overrides["template"] = template if stylesheet is not None: overrides["stylesheet_path"] = stylesheet html = open(path, "w") publish_file( source=io.StringIO(text), destination=html, writer_name="html", settings_overrides=overrides, ) class Category: def __init__(self, name): if name is None: name = "Other" self.name = name self.id = "results-{name}".format(name=name.replace(" ", "_")) self.content_id = self.id + "-content" def __eq__(self, other): return self.name.__eq__(other.name) def __hash__(self): return self.name.__hash__() def __lt__(self, other): if self.name == "other": return False return self.name.__lt__(other.name) class RuleRecord: def __init__(self, job, job_rec): import yaml self.name = job_rec.rule self._rule = job.rule self.singularity_img_url = job_rec.singularity_img_url self.conda_env = None self._conda_env_raw = None if job_rec.conda_env: self._conda_env_raw = base64.b64decode(job_rec.conda_env).decode() self.conda_env = yaml.load(self._conda_env_raw, Loader=yaml.Loader) self.n_jobs = 1 self.output = list(job_rec.output) self.id = uuid.uuid4() def code(self): try: from pygments.lexers import get_lexer_by_name from pygments.formatters import HtmlFormatter from pygments import highlight import pygments.util except ImportError: raise WorkflowError( "Python package pygments must be installed to create reports." ) source, language = None, None if self._rule.shellcmd is not None: source = self._rule.shellcmd language = "bash" elif self._rule.script is not None: logger.info("Loading script code for rule {}".format(self.name)) _, source, language = script.get_source( self._rule.script, self._rule.basedir ) source = source.decode() elif self._rule.wrapper is not None: logger.info("Loading wrapper code for rule {}".format(self.name)) _, source, language = script.get_source( wrapper.get_script( self._rule.wrapper, prefix=self._rule.workflow.wrapper_prefix ) ) source = source.decode() try: lexer = get_lexer_by_name(language) return highlight( source, lexer, HtmlFormatter(linenos=True, cssclass="source", wrapcode=True), ) except pygments.util.ClassNotFound: return "
source
" def add(self, job_rec): self.n_jobs += 1 self.output.extend(job_rec.output) def __eq__(self, other): return ( self.name == other.name and self.conda_env == other.conda_env and self.singularity_img_url == other.singularity_img_url ) class ConfigfileRecord: def __init__(self, configfile): self.name = configfile def code(self): try: from pygments.lexers import get_lexer_by_name from pygments.formatters import HtmlFormatter from pygments import highlight except ImportError: raise WorkflowError( "Python package pygments must be installed to create reports." ) language = ( "yaml" if self.name.endswith(".yaml") or self.name.endswith(".yml") else "json" ) lexer = get_lexer_by_name(language) with open(self.name) as f: return highlight( f.read(), lexer, HtmlFormatter(linenos=True, cssclass="source", wrapcode=True), ) class JobRecord: def __init__(self): self.job = None self.rule = None self.starttime = sys.maxsize self.endtime = 0 self.output = [] self.conda_env_file = None self.singularity_img_url = None class FileRecord: def __init__(self, path, job, caption, env, category): self.path = path self.target = os.path.basename(path) self.size = os.path.getsize(self.path) logger.info("Adding {} ({:.2g} MB).".format(self.name, self.size / 1e6)) self.raw_caption = caption self.mime, _ = mime_from_file(self.path) self.id = uuid.uuid4() self.job = job self.wildcards = logging.format_wildcards(job.wildcards) self.params = logging.format_dict(job.params) self.png_uri = None self.category = category if self.is_img: convert = shutil.which("convert") if convert is not None: try: # 2048 aims at a reasonable balance between what displays # can show in a png-preview image and what renders quick # into a small enough png max_width = "2048" max_height = "2048" # '>' means only larger images scaled down to within max-dimensions max_spec = max_width + "x" + max_height + ">" png = sp.check_output( ["convert", "-resize", max_spec, self.path, "png:-"], stderr=sp.PIPE, ) uri = data_uri( png, os.path.basename(self.path) + ".png", mime="image/png" ) self.png_uri = uri except sp.CalledProcessError as e: logger.warning( "Failed to convert image to png with " "imagemagick convert: {}".format(e.stderr) ) else: logger.warning( "Command convert not in $PATH. Install " "imagemagick in order to have embedded " "images and pdfs in the report." ) if self.is_table: if self.size > 1e6: logger.warning( "Table {} >1MB. Rendering as generic file.".format(self.path) ) else: with open(self.path) as table: dialect = None for prefix in range(10, 17): try: table.seek(0) dialect = csv.Sniffer().sniff(table.read(prefix)) break except csv.Error: pass except UnicodeDecodeError: # table is not readable as UTF-8 break if dialect is None: logger.warning( "Failed to infer CSV/TSV dialect from table {}. " "Rendering as generic file.".format(self.path) ) else: table.seek(0) reader = csv.reader(table, dialect) columns = next(reader) table = map(lambda row: list(map(num_if_possible, row)), reader) template = env.get_template("table.html") html = template.render( columns=columns, table=table, name=self.name ).encode() self.mime = "text/html" self.path = os.path.basename(self.path) + ".html" self.data_uri = data_uri(html, self.path, mime=self.mime) return # fallback self.data_uri = data_uri_from_file(path) def render(self, env, rst_links, categories, files): if self.raw_caption is not None: try: from jinja2 import Template except ImportError as e: raise WorkflowError( "Python package jinja2 must be installed to create reports." ) job = self.job snakemake = Snakemake( job.input, job.output, job.params, job.wildcards, job.threads, job.resources, job.log, job.dag.workflow.config, job.rule.name, None, ) try: caption = open(self.raw_caption).read() + rst_links caption = env.from_string(caption).render( snakemake=snakemake, categories=categories, files=files ) self.caption = publish_parts(caption, writer_name="html")["body"] except Exception as e: raise WorkflowError( "Error loading caption file of output " "marked for report.", e ) @property def is_img(self): web_safe = { "image/gif", "image/jpeg", "image/png", "image/svg+xml", "application/pdf", } return self.mime in web_safe @property def is_text(self): return self.is_table or self.mime == "text/plain" @property def is_table(self): return self.mime in {"text/csv", "text/tab-separated-values"} @property def is_vega(self): return ( self.mime == "application/json" and self.path.endswith(".vl.json") or self.path.endswith(".vg.json") ) @property def icon(self): if self.is_img: return "image" elif self.is_text: return "file-text" else: return "file" @property def name(self): return os.path.basename(self.path) def rulegraph_d3_spec(dag): try: import networkx as nx from networkx.drawing.nx_agraph import graphviz_layout from networkx.readwrite import json_graph except ImportError as e: raise WorkflowError( "Python packages networkx and pygraphviz must be " "installed to create reports.", e, ) g = nx.DiGraph() g.add_nodes_from(sorted(job.rule.name for job in dag.jobs)) for job in dag.jobs: target = job.rule.name for dep in dag.dependencies[job]: source = dep.rule.name g.add_edge(source, target) pos = graphviz_layout(g, "dot", args="-Grankdir=BT") xmax = max(x for x, y in pos.values()) + 100 # add offset to account for labels ymax = max(y for x, y in pos.values()) def encode_node(node): x, y = pos[node] return {"rule": node, "fx": x, "fy": y} nodes = list(map(encode_node, g.nodes)) idx = {node: i for i, node in enumerate(g.nodes)} links = [{"target": idx[u], "source": idx[v], "value": 1} for u, v in g.edges] return {"nodes": nodes, "links": links}, xmax, ymax def get_resource_as_string(url): r = requests.get(url) if r.status_code == requests.codes.ok: return r.text raise WorkflowError( "Failed to download resource needed for " "report: {}".format(url) ) def auto_report(dag, path): try: from jinja2 import Template, Environment, PackageLoader except ImportError as e: raise WorkflowError( "Python package jinja2 must be installed to create reports." ) if not path.endswith(".html"): raise WorkflowError("Report file does not end with .html") logger.info("Creating report...") env = Environment( loader=PackageLoader("snakemake", "report"), trim_blocks=True, lstrip_blocks=True, ) env.filters["get_resource_as_string"] = get_resource_as_string persistence = dag.workflow.persistence results = defaultdict(list) records = defaultdict(JobRecord) recorded_files = set() for job in dag.jobs: for f in itertools.chain(job.expanded_output, job.input): if is_flagged(f, "report") and f not in recorded_files: if not f.exists: raise WorkflowError( "File {} marked for report but does " "not exist.".format(f) ) if os.path.isfile(f): report_obj = get_flag_value(f, "report") category = Category(report_obj.category) results[category].append( FileRecord(f, job, report_obj.caption, env, category) ) recorded_files.add(f) for f in job.expanded_output: meta = persistence.metadata(f) if not meta: logger.warning( "Missing metadata for file {}. Maybe metadata " "was deleted or it was created using an older " "version of Snakemake. This is a non critical " "warning.".format(f) ) continue try: job_hash = meta["job_hash"] rule = meta["rule"] rec = records[(job_hash, rule)] rec.rule = rule rec.job = job rec.starttime = min(rec.starttime, meta["starttime"]) rec.endtime = max(rec.endtime, meta["endtime"]) rec.conda_env_file = None rec.conda_env = meta["conda_env"] rec.singularity_img_url = meta["singularity_img_url"] rec.output.append(f) except KeyError as e: print(e) logger.warning( "Metadata for file {} was created with a too " "old Snakemake version.".format(f) ) for catresults in results.values(): catresults.sort(key=lambda res: res.name) # prepare runtimes runtimes = [ {"rule": rec.rule, "runtime": rec.endtime - rec.starttime} for rec in sorted(records.values(), key=lambda rec: rec.rule) ] # prepare end times timeline = [ { "rule": rec.rule, "starttime": datetime.datetime.fromtimestamp(rec.starttime).isoformat(), "endtime": datetime.datetime.fromtimestamp(rec.endtime).isoformat(), } for rec in sorted(records.values(), key=lambda rec: rec.rule) ] # prepare per-rule information rules = defaultdict(list) for rec in records.values(): rule = RuleRecord(rec.job, rec) if rec.rule not in rules: rules[rec.rule].append(rule) else: merged = False for other in rules[rec.rule]: if rule == other: other.add(rec) merged = True break if not merged: rules[rec.rule].append(rule) # rulegraph rulegraph, xmax, ymax = rulegraph_d3_spec(dag) # configfiles configfiles = [ConfigfileRecord(f) for f in dag.workflow.configfiles] seen = set() files = [ seen.add(res.target) or res for cat in results.values() for res in cat if res.target not in seen ] rst_links = textwrap.dedent( """ .. _Results: #results .. _Rules: #rules .. _Statistics: #stats {% for cat, catresults in categories|dictsort %} .. _{{ cat.name }}: #{{ cat.id }} {% for res in files %} .. _{{ res.target }}: #{{ res.id }} {% endfor %} {% endfor %} .. _ """ ) for cat, catresults in results.items(): for res in catresults: res.render(env, rst_links, results, files) # global description text = "" if dag.workflow.report_text: with open(dag.workflow.report_text) as f: class Snakemake: config = dag.workflow.config text = f.read() + rst_links text = publish_parts( env.from_string(text).render( snakemake=Snakemake, categories=results, files=files ), writer_name="html", )["body"] # record time now = "{} {}".format(datetime.datetime.now().ctime(), time.tzname[0]) results_size = sum(res.size for cat in results.values() for res in cat) try: from pygments.formatters import HtmlFormatter except ImportError: raise WorkflowError( "Python package pygments must be installed to create reports." ) # render HTML template = env.get_template("report.html") with open(path, "w", encoding="utf-8") as out: out.write( template.render( results=results, results_size=results_size, configfiles=configfiles, text=text, rulegraph_nodes=rulegraph["nodes"], rulegraph_links=rulegraph["links"], rulegraph_width=xmax + 20, rulegraph_height=ymax + 20, runtimes=runtimes, timeline=timeline, rules=[rec for recs in rules.values() for rec in recs], version=__version__, now=now, pygments_css=HtmlFormatter(style="trac").get_style_defs(".source"), ) ) logger.info("Report created.") snakemake-5.10.0/snakemake/report/report.html000066400000000000000000000606441361131222100212110ustar00rootroot00000000000000 Snakemake Report

Loading Snakemake Report...

Please enable Javascript in your browser to see this report.

Loading {{ results_size|filesizeformat }}. For large reports, this can take a while.

Workflow

{{ text }}

Detailed software versions can be found under Rules.

Results

{% for cat, catresults in results|dictsort %}
{% for res in catresults %} {% endfor %}
Workflow resultes
File Size Description Job properties
{{ res.name }} {{ res.size|filesizeformat }} {{ res.caption }} {% if res.wildcards %} {% endif %} {% if res.params %} {% endif %}
Job properties
Rule{{ res.job.rule }}
Wildcards{{ res.wildcards }}
Params{{ res.params }}
{% endfor %}

Statistics

If the workflow has been executed in cluster/cloud, runtimes include the waiting time in the queue.
{% if configfiles %}

Configuration

{% for configfile in configfiles %} {% endfor %}
Configuration files
File Code
{{ configfile.name }}
{{ configfile.code()|safe }}
{% endif %}

Rules

{% for rule in rules %} {% endfor %}
Workflow rules
Rule Jobs Output Singularity Conda environment Code
{{ rule.name }} {{ rule.n_jobs }}
    {% for f in rule.output %}
  • {{ f }}
    • {% endfor %}
{{ rule.singularity_img_url if rule.singularity_img_url is not none }} {% if rule.conda_env %}
    {% for dep in rule.conda_env["dependencies"] %}
  • {{ dep }}
    • {% endfor %}
{% endif %} 		{% if rule.code is not none %}
{{ rule.code()|safe }}
{% endif %}
snakemake-5.10.0/snakemake/report/table.html000066400000000000000000000037321361131222100207600ustar00rootroot00000000000000 {{ name }}
{% for colname in columns %} {% endfor %}
Tabular results
{{ colname|escape }}
snakemake-5.10.0/snakemake/resources.py000066400000000000000000000032101361131222100200430ustar00rootroot00000000000000import re class DefaultResources: def __init__(self, args=None): self.args = args def fallback(val): def callable(wildcards, input, attempt, threads, rulename): value = eval( val, {"input": input, "attempt": attempt, "threads": threads} ) return value return callable self.parsed = dict(_cores=1, _nodes=1) if self.args is not None: self.parsed.update(parse_resources(args, fallback=fallback)) def parse_resources(resources_args, fallback=None): """Parse resources from args.""" resources = dict() if resources_args is not None: valid = re.compile("[a-zA-Z_]\w*$") for res in resources_args: try: res, val = res.split("=") except ValueError: raise ValueError("Resources have to be defined as name=value pairs.") if not valid.match(res): raise ValueError( "Resource definition must start with a valid identifier." ) try: val = int(val) except ValueError: if fallback is not None: val = fallback(val) else: raise ValueError( "Resource definiton must contain an integer after the identifier." ) if res == "_cores": raise ValueError( "Resource _cores is already defined internally. Use a different name." ) resources[res] = val return resources snakemake-5.10.0/snakemake/rules.py000066400000000000000000001164071361131222100172000ustar00rootroot00000000000000__author__ = "Johannes Köster" __copyright__ = "Copyright 2015-2019, Johannes Köster" __email__ = "koester@jimmy.harvard.edu" __license__ = "MIT" import os import re import sys import inspect import sre_constants import collections from urllib.parse import urljoin from pathlib import Path from itertools import chain from snakemake.io import ( IOFile, _IOFile, protected, temp, dynamic, Namedlist, AnnotatedString, contains_wildcard_constraints, update_wildcard_constraints, ) from snakemake.io import ( expand, InputFiles, OutputFiles, Wildcards, Params, Log, Resources, strip_wildcard_constraints, ) from snakemake.io import ( apply_wildcards, is_flagged, not_iterable, is_callable, DYNAMIC_FILL, ReportObject, ) from snakemake.exceptions import ( RuleException, IOFileException, WildcardError, InputFunctionException, WorkflowError, IncompleteCheckpointException, ) from snakemake.logging import logger from snakemake.common import Mode, lazy_property, TBDInt class Rule: def __init__(self, *args, lineno=None, snakefile=None, restart_times=0): """ Create a rule Arguments name -- the name of the rule """ if len(args) == 2: name, workflow = args self.name = name self.workflow = workflow self.docstring = None self.message = None self._input = InputFiles() self._output = OutputFiles() self._params = Params() self._wildcard_constraints = dict() self.dependencies = dict() self.dynamic_output = set() self.dynamic_input = set() self.temp_output = set() self.protected_output = set() self.touch_output = set() self.subworkflow_input = dict() self.shadow_depth = None self.resources = None self.priority = 0 self._version = None self._log = Log() self._benchmark = None self._conda_env = None self._singularity_img = None self.env_modules = None self.group = None self._wildcard_names = None self.lineno = lineno self.snakefile = snakefile self.run_func = None self.shellcmd = None self.script = None self.notebook = None self.wrapper = None self.cwl = None self.norun = False self.is_branched = False self.is_checkpoint = False self.restart_times = 0 self.basedir = None elif len(args) == 1: other = args[0] self.name = other.name self.workflow = other.workflow self.docstring = other.docstring self.message = other.message self._input = InputFiles(other._input) self._output = OutputFiles(other._output) self._params = Params(other._params) self._wildcard_constraints = dict(other._wildcard_constraints) self.dependencies = dict(other.dependencies) self.dynamic_output = set(other.dynamic_output) self.dynamic_input = set(other.dynamic_input) self.temp_output = set(other.temp_output) self.protected_output = set(other.protected_output) self.touch_output = set(other.touch_output) self.subworkflow_input = dict(other.subworkflow_input) self.shadow_depth = other.shadow_depth self.resources = other.resources self.priority = other.priority self.version = other.version self._log = other._log self._benchmark = other._benchmark self._conda_env = other._conda_env self._singularity_img = other._singularity_img self.env_modules = other.env_modules self.group = other.group self._wildcard_names = ( set(other._wildcard_names) if other._wildcard_names is not None else None ) self.lineno = other.lineno self.snakefile = other.snakefile self.run_func = other.run_func self.shellcmd = other.shellcmd self.script = other.script self.notebook = other.notebook self.wrapper = other.wrapper self.cwl = other.cwl self.norun = other.norun self.is_branched = True self.is_checkpoint = other.is_checkpoint self.restart_times = other.restart_times self.basedir = other.basedir def dynamic_branch(self, wildcards, input=True): def get_io(rule): return ( (rule.input, rule.dynamic_input) if input else (rule.output, rule.dynamic_output) ) def partially_expand(f, wildcards): """Expand the wildcards in f from the ones present in wildcards This is done by replacing all wildcard delimiters by `{{` or `}}` that are not in `wildcards.keys()`. """ # perform the partial expansion from f's string representation s = str(f).replace("{", "{{").replace("}", "}}") for key in wildcards.keys(): s = s.replace("{{{{{}}}}}".format(key), "{{{}}}".format(key)) # build result anno_s = AnnotatedString(s) anno_s.flags = f.flags return IOFile(anno_s, f.rule) io, dynamic_io = get_io(self) branch = Rule(self) io_, dynamic_io_ = get_io(branch) expansion = collections.defaultdict(list) for i, f in enumerate(io): if f in dynamic_io: f = partially_expand(f, wildcards) try: for e in reversed(expand(str(f), zip, **wildcards)): # need to clone the flags so intermediate # dynamic remote file paths are expanded and # removed appropriately ioFile = IOFile(e, rule=branch) ioFile.clone_flags(f) expansion[i].append(ioFile) except KeyError: return None # replace the dynamic files with the expanded files replacements = [(i, io[i], e) for i, e in reversed(list(expansion.items()))] for i, old, exp in replacements: dynamic_io_.remove(old) io_._insert_items(i, exp) if not input: for i, old, exp in replacements: if old in branch.temp_output: branch.temp_output.discard(old) branch.temp_output.update(exp) if old in branch.protected_output: branch.protected_output.discard(old) branch.protected_output.update(exp) if old in branch.touch_output: branch.touch_output.discard(old) branch.touch_output.update(exp) branch.wildcard_names.clear() non_dynamic_wildcards = dict( (name, values[0]) for name, values in wildcards.items() if len(set(values)) == 1 ) # TODO have a look into how to concretize dependencies here branch._input, _, branch.dependencies = branch.expand_input( non_dynamic_wildcards ) branch._output, _ = branch.expand_output(non_dynamic_wildcards) resources = branch.expand_resources(non_dynamic_wildcards, branch._input, 1) branch._params = branch.expand_params( non_dynamic_wildcards, branch._input, branch._output, resources, omit_callable=True, ) branch.resources = dict(resources.items()) branch._log = branch.expand_log(non_dynamic_wildcards) branch._benchmark = branch.expand_benchmark(non_dynamic_wildcards) branch._conda_env = branch.expand_conda_env(non_dynamic_wildcards) return branch, non_dynamic_wildcards return branch def check_caching(self): if self.name in self.workflow.cache_rules: if len(self.output) == 0: raise RuleException( "Rules without output files cannot be cached.", rule=self ) if len(self.output) > 1: prefixes = set(out.multiext_prefix for out in self.output) if None in prefixes or len(prefixes) > 1: raise RuleException( "Rules with multiple output files must define them as a single multiext() " '(e.g. multiext("path/to/index", ".bwt", ".ann")). ' "The rationale is that multiple output files can only be unambiously resolved " "if they can be distinguished by a fixed set of extensions (i.e. mime types).", rule=self, ) if self.dynamic_output: raise RuleException( "Rules with dynamic output files may not be cached.", rule=self ) def has_wildcards(self): """ Return True if rule contains wildcards. """ return bool(self.wildcard_names) @property def version(self): return self._version @version.setter def version(self, version): if isinstance(version, str) and "\n" in version: raise WorkflowError( "Version string may not contain line breaks.", rule=self ) self._version = version @property def benchmark(self): return self._benchmark @benchmark.setter def benchmark(self, benchmark): if isinstance(benchmark, Path): benchmark = str(benchmark) if not callable(benchmark): benchmark = self.apply_default_remote(benchmark) benchmark = self._update_item_wildcard_constraints(benchmark) self._benchmark = IOFile(benchmark, rule=self) self.register_wildcards(self._benchmark.get_wildcard_names()) @property def conda_env(self): return self._conda_env @conda_env.setter def conda_env(self, conda_env): self._conda_env = IOFile(conda_env, rule=self) @property def singularity_img(self): return self._singularity_img @singularity_img.setter def singularity_img(self, singularity_img): self._singularity_img = singularity_img @property def input(self): return self._input def set_input(self, *input, **kwinput): """ Add a list of input files. Recursive lists are flattened. Arguments input -- the list of input files """ for item in input: self._set_inoutput_item(item) for name, item in kwinput.items(): self._set_inoutput_item(item, name=name) @property def output(self): return self._output @property def products(self): if self.benchmark: return chain(self.output, self.log, [self.benchmark]) else: return chain(self.output, self.log) def register_wildcards(self, wildcard_names): if self._wildcard_names is None: self._wildcard_names = wildcard_names else: if self.wildcard_names != wildcard_names: raise SyntaxError( "Not all output, log and benchmark files of " "rule {} contain the same wildcards. " "This is crucial though, in order to " "avoid that two or more jobs write to the " "same file.".format(self.name) ) @property def wildcard_names(self): if self._wildcard_names is None: return set() return self._wildcard_names def set_output(self, *output, **kwoutput): """ Add a list of output files. Recursive lists are flattened. After creating the output files, they are checked for duplicates. Arguments output -- the list of output files """ for item in output: self._set_inoutput_item(item, output=True) for name, item in kwoutput.items(): self._set_inoutput_item(item, output=True, name=name) for item in self.output: if self.dynamic_output and item not in self.dynamic_output: raise SyntaxError( "A rule with dynamic output may not define any " "non-dynamic output files." ) self.register_wildcards(item.get_wildcard_names()) # Check output file name list for duplicates self.check_output_duplicates() self.check_caching() def check_output_duplicates(self): """Check ``Namedlist`` for duplicate entries and raise a ``WorkflowError`` on problems. """ seen = dict() idx = None for name, value in self.output._allitems(): if name is None: if idx is None: idx = 0 else: idx += 1 if value in seen: raise WorkflowError( "Duplicate output file pattern in rule {}. First two " "duplicate for entries {} and {}".format( self.name, seen[value], name or idx ) ) seen[value] = name or idx def apply_default_remote(self, item): def is_annotated_callable(value): if isinstance(value, AnnotatedString): return bool(value.callable) def apply(value): if ( not is_flagged(value, "remote_object") and not is_flagged(value, "local") and not is_annotated_callable(value) and self.workflow.default_remote_provider is not None ): return self.workflow.apply_default_remote(value) else: return value assert not callable(item) if isinstance(item, dict): return {k: apply(v) for k, v in item.items()} elif isinstance(item, collections.abc.Iterable) and not isinstance(item, str): return [apply(e) for e in item] else: return apply(item) def update_wildcard_constraints(self): for i in range(len(self.output)): item = self.output[i] newitem = IOFile( self._update_item_wildcard_constraints(self.output[i]), rule=self ) # the updated item has to have the same flags newitem.clone_flags(item) self.output[i] = newitem def _update_item_wildcard_constraints(self, item): if not (self.wildcard_constraints or self.workflow._wildcard_constraints): return item try: return update_wildcard_constraints( item, self.wildcard_constraints, self.workflow._wildcard_constraints ) except ValueError as e: raise IOFileException(str(e), snakefile=self.snakefile, lineno=self.lineno) def _set_inoutput_item(self, item, output=False, name=None): """ Set an item to be input or output. Arguments item -- the item inoutput -- a Namedlist of either input or output items name -- an optional name for the item """ inoutput = self.output if output else self.input # Check to see if the item is a path, if so, just make it a string if isinstance(item, Path): item = str(item) if isinstance(item, str): item = self.apply_default_remote(item) # Check to see that all flags are valid # Note that "remote", "dynamic", and "expand" are valid for both inputs and outputs. if isinstance(item, AnnotatedString): for flag in item.flags: if not output and flag in [ "protected", "temp", "temporary", "directory", "touch", "pipe", ]: logger.warning( "The flag '{}' used in rule {} is only valid for outputs, not inputs.".format( flag, self ) ) if output and flag in ["ancient"]: logger.warning( "The flag '{}' used in rule {} is only valid for inputs, not outputs.".format( flag, self ) ) # add the rule to the dependencies if isinstance(item, _IOFile) and item.rule and item in item.rule.output: self.dependencies[item] = item.rule if output: item = self._update_item_wildcard_constraints(item) else: if ( contains_wildcard_constraints(item) and self.workflow.mode != Mode.subprocess ): logger.warning("Wildcard constraints in inputs are ignored.") # record rule if this is an output file output _item = IOFile(item, rule=self) if is_flagged(item, "temp"): if output: self.temp_output.add(_item) if is_flagged(item, "protected"): if output: self.protected_output.add(_item) if is_flagged(item, "touch"): if output: self.touch_output.add(_item) if is_flagged(item, "dynamic"): if output: self.dynamic_output.add(_item) else: self.dynamic_input.add(_item) if is_flagged(item, "report"): report_obj = item.flags["report"] if report_obj.caption is not None: r = ReportObject( os.path.join(self.workflow.current_basedir, report_obj.caption), report_obj.category, ) item.flags["report"] = r if is_flagged(item, "subworkflow"): if output: raise SyntaxError("Only input files may refer to a subworkflow") else: # record the workflow this item comes from sub = item.flags["subworkflow"] if _item in self.subworkflow_input: other = self.subworkflow_input[_item] if sub != other: raise WorkflowError( "The input file {} is ambiguously " "associated with two subworkflows " "{} and {}.".format(item, sub, other), rule=self, ) self.subworkflow_input[_item] = sub inoutput.append(_item) if name: inoutput._add_name(name) elif callable(item): if output: raise SyntaxError("Only input files can be specified as functions") inoutput.append(item) if name: inoutput._add_name(name) else: try: start = len(inoutput) for i in item: self._set_inoutput_item(i, output=output) if name: # if the list was named, make it accessible inoutput._set_name(name, start, end=len(inoutput)) except TypeError: raise SyntaxError( "Input and output files have to be specified as strings or lists of strings." ) @property def params(self): return self._params def set_params(self, *params, **kwparams): for item in params: self._set_params_item(item) for name, item in kwparams.items(): self._set_params_item(item, name=name) def _set_params_item(self, item, name=None): self.params.append(item) if name: self.params._add_name(name) @property def wildcard_constraints(self): return self._wildcard_constraints def set_wildcard_constraints(self, **kwwildcard_constraints): self._wildcard_constraints.update(kwwildcard_constraints) @property def log(self): return self._log def set_log(self, *logs, **kwlogs): for item in logs: self._set_log_item(item) for name, item in kwlogs.items(): self._set_log_item(item, name=name) for item in self.log: self.register_wildcards(item.get_wildcard_names()) def _set_log_item(self, item, name=None): # Pathlib compatibility if isinstance(item, Path): item = str(item) if isinstance(item, str) or callable(item): if not callable(item): item = self.apply_default_remote(item) item = self._update_item_wildcard_constraints(item) self.log.append(IOFile(item, rule=self) if isinstance(item, str) else item) if name: self.log._add_name(name) else: try: start = len(self.log) for i in item: self._set_log_item(i) if name: self.log._set_name(name, start, end=len(self.log)) except TypeError: raise SyntaxError("Log files have to be specified as strings.") def check_wildcards(self, wildcards): missing_wildcards = self.wildcard_names - set(wildcards.keys()) if missing_wildcards: raise RuleException( "Could not resolve wildcards in rule {}:\n{}".format( self.name, "\n".join(self.wildcard_names) ), lineno=self.lineno, snakefile=self.snakefile, ) def apply_input_function( self, func, wildcards, incomplete_checkpoint_func=lambda e: None, raw_exceptions=False, **aux_params ): incomplete = False if isinstance(func, _IOFile): func = func._file.callable elif isinstance(func, AnnotatedString): func = func.callable sig = inspect.signature(func) _aux_params = {k: v for k, v in aux_params.items() if k in sig.parameters} try: value = func(Wildcards(fromdict=wildcards), **_aux_params) except IncompleteCheckpointException as e: value = incomplete_checkpoint_func(e) incomplete = True except (Exception, BaseException) as e: if raw_exceptions: raise e else: raise InputFunctionException(e, rule=self, wildcards=wildcards) return value, incomplete def _apply_wildcards( self, newitems, olditems, wildcards, concretize=None, check_return_type=True, omit_callable=False, mapping=None, no_flattening=False, aux_params=None, apply_default_remote=True, incomplete_checkpoint_func=lambda e: None, allow_unpack=True, ): if aux_params is None: aux_params = dict() for name, item in olditems._allitems(): start = len(newitems) is_unpack = is_flagged(item, "unpack") _is_callable = is_callable(item) if _is_callable: if omit_callable: continue item, incomplete = self.apply_input_function( item, wildcards, incomplete_checkpoint_func=incomplete_checkpoint_func, is_unpack=is_unpack, **aux_params ) if apply_default_remote: item = self.apply_default_remote(item) if is_unpack and not incomplete: if not allow_unpack: raise WorkflowError( "unpack() is not allowed with params. " "Simply return a dictionary which can be directly ." "used, e.g. via {params[mykey]}." ) # Sanity checks before interpreting unpack() if not isinstance(item, (list, dict)): raise WorkflowError( "Can only use unpack() on list and dict", rule=self ) if name: raise WorkflowError( "Cannot combine named input file with unpack()", rule=self ) # Allow streamlined code with/without unpack if isinstance(item, list): pairs = zip([None] * len(item), item) else: assert isinstance(item, dict) pairs = item.items() else: pairs = [(name, item)] for name, item in pairs: is_iterable = True if not_iterable(item) or no_flattening: item = [item] is_iterable = False for item_ in item: if check_return_type and not isinstance(item_, str): raise WorkflowError( "Function did not return str or list " "of str.", rule=self ) concrete = concretize(item_, wildcards, _is_callable) newitems.append(concrete) if mapping is not None: mapping[concrete] = item_ if name: newitems._set_name( name, start, end=len(newitems) if is_iterable else None ) start = len(newitems) def expand_input(self, wildcards): def concretize_iofile(f, wildcards, is_from_callable): if is_from_callable: if isinstance(f, Path): f = str(Path) return IOFile(f, rule=self).apply_wildcards( wildcards, fill_missing=f in self.dynamic_input, fail_dynamic=self.dynamic_output, ) else: return f.apply_wildcards( wildcards, fill_missing=f in self.dynamic_input, fail_dynamic=self.dynamic_output, ) def handle_incomplete_checkpoint(exception): """If checkpoint is incomplete, target it such that it is completed before this rule gets executed.""" return exception.targetfile input = InputFiles() mapping = dict() try: self._apply_wildcards( input, self.input, wildcards, concretize=concretize_iofile, mapping=mapping, incomplete_checkpoint_func=handle_incomplete_checkpoint, ) except WildcardError as e: raise WildcardError( "Wildcards in input files cannot be " "determined from output files:", str(e), rule=self, ) if self.dependencies: dependencies = { f: self.dependencies[f_] for f, f_ in mapping.items() if f_ in self.dependencies } if None in self.dependencies: dependencies[None] = self.dependencies[None] else: dependencies = self.dependencies for f in input: f.check() return input, mapping, dependencies def expand_params(self, wildcards, input, output, resources, omit_callable=False): def concretize_param(p, wildcards, is_from_callable): if not is_from_callable: if isinstance(p, str): return apply_wildcards(p, wildcards) if isinstance(p, list): return [ (apply_wildcards(v, wildcards) if isinstance(v, str) else v) for v in p ] return p params = Params() try: # When applying wildcards to params, the return type need not be # a string, so the check is disabled. self._apply_wildcards( params, self.params, wildcards, concretize=concretize_param, check_return_type=False, omit_callable=omit_callable, allow_unpack=False, no_flattening=True, apply_default_remote=False, aux_params={ "input": input._plainstrings(), "resources": resources, "output": output._plainstrings(), "threads": resources._cores, }, incomplete_checkpoint_func=lambda e: "", ) except WildcardError as e: raise WildcardError( "Wildcards in params cannot be " "determined from output files. Note that you have " "to use a function to deactivate automatic wildcard expansion " "in params strings, e.g., `lambda wildcards: '{test}'`. Also " "see https://snakemake.readthedocs.io/en/stable/snakefiles/" "rules.html#non-file-parameters-for-rules:", str(e), rule=self, ) return params def expand_output(self, wildcards): output = OutputFiles(o.apply_wildcards(wildcards) for o in self.output) output._take_names(self.output._get_names()) mapping = {f: f_ for f, f_ in zip(output, self.output)} for f in output: f.check() # Note that we do not need to check for duplicate file names after # expansion as all output patterns have contain all wildcards anyway. return output, mapping def expand_log(self, wildcards): def concretize_logfile(f, wildcards, is_from_callable): if is_from_callable: return IOFile(f, rule=self) else: return f.apply_wildcards( wildcards, fill_missing=False, fail_dynamic=self.dynamic_output ) log = Log() try: self._apply_wildcards( log, self.log, wildcards, concretize=concretize_logfile ) except WildcardError as e: raise WildcardError( "Wildcards in log files cannot be " "determined from output files:", str(e), rule=self, ) for f in log: f.check() return log def expand_benchmark(self, wildcards): try: benchmark = ( self.benchmark.apply_wildcards(wildcards) if self.benchmark else None ) except WildcardError as e: raise WildcardError( "Wildcards in benchmark file cannot be " "determined from output files:", str(e), rule=self, ) if benchmark is not None: benchmark.check() return benchmark def expand_resources(self, wildcards, input, attempt): resources = dict() def apply(name, res, threads=None): if callable(res): aux = dict(rulename=self.name) if threads: aux["threads"] = threads try: try: res, _ = self.apply_input_function( res, wildcards, input=input, attempt=attempt, incomplete_checkpoint_func=lambda e: 0, raw_exceptions=True, **aux ) except FileNotFoundError as e: # Resources can depend on input files. Since expansion can happen during dryrun, # where input files are not yet present, we need to skip such resources and # mark them as [TBD]. if e.filename in input: # use zero for resource if it cannot yet be determined res = TBDInt(0) else: raise e except e: raise InputFunctionException(e, rule=self, wildcards=wildcards) if not isinstance(res, int): raise WorkflowError( "Resources function did not return int.", rule=self ) res = min(self.workflow.global_resources.get(name, res), res) return res threads = apply("_cores", self.resources["_cores"]) resources["_cores"] = threads for name, res in self.resources.items(): if name != "_cores": resources[name] = apply(name, res, threads=threads) resources = Resources(fromdict=resources) return resources def expand_group(self, wildcards): """Expand the group given wildcards.""" if callable(self.group): item, _ = self.apply_input_function(self.group, wildcards) return item elif isinstance(self.group, str): return apply_wildcards(self.group, wildcards, dynamic_fill=DYNAMIC_FILL) else: return self.group def expand_conda_env(self, wildcards): try: conda_env = ( self.conda_env.apply_wildcards(wildcards) if self.conda_env else None ) except WildcardError as e: raise WildcardError( "Wildcards in conda environment file cannot be " "determined from output files:", str(e), rule=self, ) if conda_env is not None: conda_env.check() return conda_env def is_producer(self, requested_output): """ Returns True if this rule is a producer of the requested output. """ try: for o in self.products: if o.match(requested_output): return True return False except sre_constants.error as ex: raise IOFileException( "{} in wildcard statement".format(ex), snakefile=self.snakefile, lineno=self.lineno, ) except ValueError as ex: raise IOFileException( "{}".format(ex), snakefile=self.snakefile, lineno=self.lineno ) def get_wildcards(self, requested_output): """ Return wildcard dictionary by matching regular expression output files to the requested concrete ones. Arguments requested_output -- a concrete filepath """ if requested_output is None: return dict() bestmatchlen = 0 bestmatch = None for o in self.products: match = o.match(requested_output) if match: l = self.get_wildcard_len(match.groupdict()) if not bestmatch or bestmatchlen > l: bestmatch = match.groupdict() bestmatchlen = l self.check_wildcards(bestmatch) return bestmatch @staticmethod def get_wildcard_len(wildcards): """ Return the length of the given wildcard values. Arguments wildcards -- a dict of wildcards """ return sum(map(len, wildcards.values())) def __lt__(self, rule): comp = self.workflow._ruleorder.compare(self, rule) return comp < 0 def __gt__(self, rule): comp = self.workflow._ruleorder.compare(self, rule) return comp > 0 def __str__(self): return self.name def __hash__(self): return self.name.__hash__() def __eq__(self, other): return self.name == other.name and self.output == other.output class Ruleorder: def __init__(self): self.order = list() def add(self, *rulenames): """ Records the order of given rules as rule1 > rule2 > rule3, ... """ self.order.append(list(rulenames)) def compare(self, rule1, rule2): """ Return whether rule2 has a higher priority than rule1. """ # if rules have the same name, they have been specialized by dynamic output # in that case, clauses are irrelevant and have to be skipped if rule1.name != rule2.name: # try the last clause first, # i.e. clauses added later overwrite those before. for clause in reversed(self.order): try: i = clause.index(rule1.name) j = clause.index(rule2.name) # rules with higher priority should have a smaller index comp = j - i if comp < 0: comp = -1 elif comp > 0: comp = 1 return comp except ValueError: pass # if no ruleorder given, prefer rule without wildcards wildcard_cmp = rule2.has_wildcards() - rule1.has_wildcards() if wildcard_cmp != 0: return wildcard_cmp return 0 def __iter__(self): return self.order.__iter__() class RuleProxy: def __init__(self, rule): self.rule = rule @lazy_property def output(self): return self._to_iofile(self.rule.output) @lazy_property def input(self): return self.rule.input._stripped_constraints() @lazy_property def params(self): return self.rule.params._clone() @property def benchmark(self): return IOFile(strip_wildcard_constraints(self.rule.benchmark), rule=self.rule) @lazy_property def log(self): return self._to_iofile(self.rule.log) def _to_iofile(self, files): def cleanup(f): prefix = self.rule.workflow.default_remote_prefix # remove constraints and turn this into a plain string cleaned = strip_wildcard_constraints(f) if ( self.rule.workflow.default_remote_provider is not None and f.startswith(prefix) and not is_flagged(f, "local") ): cleaned = f[len(prefix) + 1 :] cleaned = IOFile(cleaned, rule=self.rule) else: cleaned = IOFile(AnnotatedString(cleaned), rule=self.rule) cleaned.clone_remote_object(f) return cleaned files = Namedlist(files, custom_map=cleanup) return files snakemake-5.10.0/snakemake/scheduler.py000066400000000000000000000507671361131222100200320ustar00rootroot00000000000000__author__ = "Johannes Köster" __copyright__ = "Copyright 2015-2019, Johannes Köster" __email__ = "koester@jimmy.harvard.edu" __license__ = "MIT" import os, signal, sys import threading import operator from functools import partial from collections import defaultdict from itertools import chain, accumulate from contextlib import ContextDecorator import time from snakemake.executors import DryrunExecutor, TouchExecutor, CPUExecutor from snakemake.executors import ( GenericClusterExecutor, SynchronousClusterExecutor, DRMAAExecutor, KubernetesExecutor, TibannaExecutor, ) from snakemake.exceptions import RuleException, WorkflowError, print_exception from snakemake.shell import shell from snakemake.logging import logger from fractions import Fraction def cumsum(iterable, zero=[0]): return list(chain(zero, accumulate(iterable))) _ERROR_MSG_FINAL = ( "Exiting because a job execution failed. " "Look above for error message" ) class DummyRateLimiter(ContextDecorator): def __enter__(self): return self def __exit__(self, *args): return False class JobScheduler: def __init__( self, workflow, dag, cores, local_cores=1, dryrun=False, touch=False, cluster=None, cluster_status=None, cluster_config=None, cluster_sync=None, drmaa=None, drmaa_log_dir=None, kubernetes=None, kubernetes_envvars=None, container_image=None, tibanna=None, tibanna_sfn=None, precommand="", jobname=None, quiet=False, printreason=False, printshellcmds=False, keepgoing=False, max_jobs_per_second=None, max_status_checks_per_second=100, latency_wait=3, greediness=1.0, force_use_threads=False, assume_shared_fs=True, keepincomplete=False, ): """ Create a new instance of KnapsackJobScheduler. """ from ratelimiter import RateLimiter self.cluster = cluster self.cluster_config = cluster_config self.cluster_sync = cluster_sync self.dag = dag self.workflow = workflow self.dryrun = dryrun self.touch = touch self.quiet = quiet self.keepgoing = keepgoing self.running = set() self.failed = set() self.finished_jobs = 0 self.greediness = 1 self.max_jobs_per_second = max_jobs_per_second self.keepincomplete = keepincomplete self.resources = dict(self.workflow.global_resources) use_threads = ( force_use_threads or (os.name != "posix") or cluster or cluster_sync or drmaa ) self._open_jobs = threading.Semaphore(0) self._lock = threading.Lock() self._errors = False self._finished = False self._job_queue = None self._submit_callback = self._noop self._finish_callback = partial( self._proceed, update_dynamic=not self.dryrun, print_progress=not self.quiet and not self.dryrun, ) self._local_executor = None if dryrun: self._executor = DryrunExecutor( workflow, dag, printreason=printreason, quiet=quiet, printshellcmds=printshellcmds, latency_wait=latency_wait, ) elif touch: self._executor = TouchExecutor( workflow, dag, printreason=printreason, quiet=quiet, printshellcmds=printshellcmds, latency_wait=latency_wait, ) elif cluster or cluster_sync or (drmaa is not None): if not workflow.immediate_submit: # No local jobs when using immediate submit! # Otherwise, they will fail due to missing input self._local_executor = CPUExecutor( workflow, dag, local_cores, printreason=printreason, quiet=quiet, printshellcmds=printshellcmds, latency_wait=latency_wait, cores=local_cores, keepincomplete=keepincomplete, ) if cluster or cluster_sync: if cluster_sync: constructor = SynchronousClusterExecutor else: constructor = partial( GenericClusterExecutor, statuscmd=cluster_status, max_status_checks_per_second=max_status_checks_per_second, ) self._executor = constructor( workflow, dag, None, submitcmd=(cluster or cluster_sync), cluster_config=cluster_config, jobname=jobname, printreason=printreason, quiet=quiet, printshellcmds=printshellcmds, latency_wait=latency_wait, assume_shared_fs=assume_shared_fs, keepincomplete=keepincomplete, ) if workflow.immediate_submit: self._submit_callback = partial( self._proceed, update_dynamic=False, print_progress=False, update_resources=False, handle_job_success=False, ) else: self._executor = DRMAAExecutor( workflow, dag, None, drmaa_args=drmaa, drmaa_log_dir=drmaa_log_dir, jobname=jobname, printreason=printreason, quiet=quiet, printshellcmds=printshellcmds, latency_wait=latency_wait, cluster_config=cluster_config, assume_shared_fs=assume_shared_fs, max_status_checks_per_second=max_status_checks_per_second, keepincomplete=keepincomplete, ) elif kubernetes: self._local_executor = CPUExecutor( workflow, dag, local_cores, printreason=printreason, quiet=quiet, printshellcmds=printshellcmds, latency_wait=latency_wait, cores=local_cores, keepincomplete=keepincomplete, ) self._executor = KubernetesExecutor( workflow, dag, kubernetes, kubernetes_envvars, container_image=container_image, printreason=printreason, quiet=quiet, printshellcmds=printshellcmds, latency_wait=latency_wait, cluster_config=cluster_config, keepincomplete=keepincomplete, ) elif tibanna: self._local_executor = CPUExecutor( workflow, dag, local_cores, printreason=printreason, quiet=quiet, printshellcmds=printshellcmds, use_threads=use_threads, latency_wait=latency_wait, cores=local_cores, keepincomplete=keepincomplete, ) self._executor = TibannaExecutor( workflow, dag, cores, tibanna_sfn, precommand=precommand, container_image=container_image, printreason=printreason, quiet=quiet, printshellcmds=printshellcmds, latency_wait=latency_wait, keepincomplete=keepincomplete, ) else: self._executor = CPUExecutor( workflow, dag, cores, printreason=printreason, quiet=quiet, printshellcmds=printshellcmds, use_threads=use_threads, latency_wait=latency_wait, cores=cores, keepincomplete=keepincomplete, ) if self.max_jobs_per_second and not self.dryrun: max_jobs_frac = Fraction(self.max_jobs_per_second).limit_denominator() self.rate_limiter = RateLimiter( max_calls=max_jobs_frac.numerator, period=max_jobs_frac.denominator ) else: # essentially no rate limit self.rate_limiter = DummyRateLimiter() self._user_kill = None signal.signal(signal.SIGTERM, self.exit_gracefully) self._open_jobs.release() @property def stats(self): try: return self._executor.stats except AttributeError: raise TypeError("Executor does not support stats") def candidate(self, job): """ Return whether a job is a candidate to be executed. """ return ( job not in self.running and job not in self.failed and (self.dryrun or (not job.dynamic_input and not self.dag.dynamic(job))) ) @property def open_jobs(self): """ Return open jobs. """ return filter(self.candidate, list(job for job in self.dag.ready_jobs)) def schedule(self): """ Schedule jobs that are ready, maximizing cpu usage. """ try: while True: # work around so that the wait does not prevent keyboard interrupts # while not self._open_jobs.acquire(False): # time.sleep(1) self._open_jobs.acquire() # obtain needrun and running jobs in a thread-safe way with self._lock: needrun = list(self.open_jobs) running = list(self.running) errors = self._errors user_kill = self._user_kill # handle errors if user_kill or (not self.keepgoing and errors): if user_kill == "graceful": logger.info( "Will exit after finishing " "currently running jobs." ) if not running: logger.info("Shutting down, this might take some time.") self._executor.shutdown() if not user_kill: logger.error(_ERROR_MSG_FINAL) return False continue # normal shutdown because all jobs have been finished if not needrun and (not running or self.workflow.immediate_submit): self._executor.shutdown() if errors: logger.error(_ERROR_MSG_FINAL) return not errors # continue if no new job needs to be executed if not needrun: continue # select jobs by solving knapsack problem (omit with dryrun) if self.dryrun: run = needrun else: logger.debug( "Resources before job selection: {}".format(self.resources) ) logger.debug( "Ready jobs ({}):\n\t".format(len(needrun)) + "\n\t".join(map(str, needrun)) ) run = self.job_selector(needrun) logger.debug( "Selected jobs ({}):\n\t".format(len(run)) + "\n\t".join(map(str, run)) ) logger.debug( "Resources after job selection: {}".format(self.resources) ) # update running jobs with self._lock: self.running.update(run) # actually run jobs for job in run: with self.rate_limiter: self.run(job) except (KeyboardInterrupt, SystemExit): logger.info( "Terminating processes on user request, this might take some time." ) self._executor.cancel() return False def get_executor(self, job): if self._local_executor is None: return self._executor else: return self._local_executor if job.is_local else self._executor def run(self, job): self.get_executor(job).run( job, callback=self._finish_callback, submit_callback=self._submit_callback, error_callback=self._error, ) def _noop(self, job): pass def _free_resources(self, job): for name, value in job.resources.items(): if name in self.resources: value = self.calc_resource(name, value) self.resources[name] += value def _proceed( self, job, update_dynamic=True, print_progress=False, update_resources=True, handle_job_success=True, ): """ Do stuff after job is finished. """ with self._lock: if handle_job_success: # by calling this behind the lock, we avoid race conditions try: self.get_executor(job).handle_job_success(job) except (RuleException, WorkflowError) as e: # if an error occurs while processing job output, # we do the same as in case of errors during execution print_exception(e, self.workflow.linemaps) self._handle_error(job) return try: self.dag.finish(job, update_dynamic=update_dynamic) except (RuleException, WorkflowError) as e: # if an error occurs while processing job output, # we do the same as in case of errors during execution print_exception(e, self.workflow.linemaps) self._handle_error(job) return if update_resources: # normal jobs have len=1, group jobs have len>1 self.finished_jobs += len(job) self.running.remove(job) self._free_resources(job) if print_progress: if job.is_group(): for j in job: logger.job_finished(jobid=j.jobid) else: logger.job_finished(jobid=job.jobid) self.progress() if ( any(self.open_jobs) or not self.running or self.workflow.immediate_submit ): # go on scheduling if open jobs are ready or no job is running self._open_jobs.release() def _error(self, job): with self._lock: self._handle_error(job) def _handle_error(self, job): """Clear jobs and stop the workflow. If Snakemake is configured to restart jobs then the job might have "restart_times" left and we just decrement and let the scheduler try to run the job again. """ self.get_executor(job).handle_job_error(job) self.running.remove(job) self._free_resources(job) # attempt starts counting from 1, but the first attempt is not # a restart, hence we subtract 1. if job.restart_times > job.attempt - 1: logger.info("Trying to restart job {}.".format(self.dag.jobid(job))) job.attempt += 1 else: self._errors = True self.failed.add(job) if self.keepgoing: logger.info("Job failed, going on with independent jobs.") self._open_jobs.release() def exit_gracefully(self, *args): with self._lock: self._user_kill = "graceful" self._open_jobs.release() def job_selector(self, jobs): """ Using the greedy heuristic from "A Greedy Algorithm for the General Multidimensional Knapsack Problem", Akcay, Li, Xu, Annals of Operations Research, 2012 Args: jobs (list): list of jobs """ with self._lock: # each job is an item with one copy (0-1 MDKP) n = len(jobs) x = [0] * n # selected jobs E = set(range(n)) # jobs still free to select u = [1] * n a = list(map(self.job_weight, jobs)) # resource usage of jobs c = list(map(self.job_reward, jobs)) # job rewards def calc_reward(): return [c_j * y_j for c_j, y_j in zip(c, y)] b = [ self.resources[name] for name in self.workflow.global_resources ] # resource capacities while True: # Step 2: compute effective capacities y = [ ( min( (min(u[j], b_i // a_j_i) if a_j_i > 0 else u[j]) for b_i, a_j_i in zip(b, a[j]) if a_j_i ) if j in E else 0 ) for j in range(n) ] if not any(y): break y = [ (max(1, int(self.greediness * y_j)) if y_j > 0 else 0) for y_j in y ] # Step 3: compute rewards on cumulative sums reward = calc_reward() j_sel = max(E, key=reward.__getitem__) # argmax # Step 4: batch increment y_sel = y[j_sel] # Step 5: update information x[j_sel] += y_sel b = [b_i - (a_j_i * y_sel) for b_i, a_j_i in zip(b, a[j_sel])] u[j_sel] -= y_sel if not u[j_sel] or self.greediness == 1: E.remove(j_sel) if not E: break solution = [job for job, sel in zip(jobs, x) if sel] # update resources for name, b_i in zip(self.workflow.global_resources, b): self.resources[name] = b_i return solution def calc_resource(self, name, value): gres = self.workflow.global_resources[name] if value > gres: if name == "_cores": name = "threads" raise WorkflowError( "Job needs {name}={res} but only {name}={gres} " "are available. This is likely because two " "jobs are connected via a pipe and have to run " "simultaneously. Consider providing more " "resources (e.g. via --cores).".format(name=name, res=value, gres=gres) ) return value def rule_weight(self, rule): res = rule.resources return [ self.calc_resource(name, res.get(name, 0)) for name in self.workflow.global_resources ] def job_weight(self, job): res = job.resources return [ self.calc_resource(name, res.get(name, 0)) for name in self.workflow.global_resources ] def job_reward(self, job): if self.touch or self.dryrun or self.workflow.immediate_submit: temp_size = 0 input_size = 0 else: temp_size = self.dag.temp_size(job) input_size = job.inputsize # Usually, this should guide the scheduler to first schedule all jobs # that remove the largest temp file, then the second largest and so on. # Since the weight is summed up, it can in theory be that it sometimes # prefers a set of many jobs that all depend on smaller temp files though. # A real solution to the problem is therefore to use dummy jobs that # ensure selection of groups of jobs that together delete the same temp # file. return (job.priority, temp_size, input_size) def progress(self): """ Display the progress. """ logger.progress(done=self.finished_jobs, total=len(self.dag)) snakemake-5.10.0/snakemake/script.py000066400000000000000000000652611361131222100173530ustar00rootroot00000000000000__author__ = "Johannes Köster" __copyright__ = "Copyright 2015-2019, Johannes Köster" __email__ = "koester@jimmy.harvard.edu" __license__ = "MIT" import inspect import itertools import os import tempfile import textwrap import sys import pickle import subprocess import collections import re from abc import ABC, abstractmethod from urllib.request import urlopen, pathname2url from urllib.error import URLError from snakemake.utils import format from snakemake.logging import logger from snakemake.exceptions import WorkflowError from snakemake.shell import shell from snakemake.common import MIN_PY_VERSION, SNAKEMAKE_SEARCHPATH from snakemake.io import git_content, split_git_path from snakemake.deployment import singularity PY_VER_RE = re.compile("Python (?P\d+\.\d+).*") # TODO use this to find the right place for inserting the preamble PY_PREAMBLE_RE = re.compile(r"from( )+__future__( )+import.*?(?P[;\n])") class Snakemake: def __init__( self, input_, output, params, wildcards, threads, resources, log, config, rulename, bench_iteration, scriptdir=None, ): # convert input and output to plain strings as some remote objects cannot # be pickled self.input = input_._plainstrings() self.output = output._plainstrings() self.params = params self.wildcards = wildcards self.threads = threads self.resources = resources self.log = log._plainstrings() self.config = config self.rule = rulename self.bench_iteration = bench_iteration self.scriptdir = scriptdir def log_fmt_shell(self, stdout=True, stderr=True, append=False): """ Return a shell redirection string to be used in `shell()` calls This function allows scripts and wrappers support optional `log` files specified in the calling rule. If no `log` was specified, then an empty string "" is returned, regardless of the values of `stdout`, `stderr`, and `append`. Parameters --------- stdout : bool Send stdout to log stderr : bool Send stderr to log append : bool Do not overwrite the log file. Useful for sending output of multiple commands to the same log. Note however that the log will not be truncated at the start. The following table describes the output: -------- -------- -------- ----- ------------- stdout stderr append log return value -------- -------- -------- ----- ------------ True True True fn >> fn 2>&1 True False True fn >> fn False True True fn 2>> fn True True False fn > fn 2>&1 True False False fn > fn False True False fn 2> fn any any any None "" -------- -------- -------- ----- ----------- """ if not self.log: return "" lookup = { (True, True, True): " >> {0} 2>&1", (True, False, True): " >> {0}", (False, True, True): " 2>> {0}", (True, True, False): " > {0} 2>&1", (True, False, False): " > {0}", (False, True, False): " 2> {0}", } return lookup[(stdout, stderr, append)].format(self.log) class REncoder: """Encoding Pyton data structures into R.""" @classmethod def encode_numeric(cls, value): if value is None: return "as.numeric(NA)" return str(value) @classmethod def encode_value(cls, value): if value is None: return "NULL" elif isinstance(value, str): return repr(value) elif isinstance(value, dict): return cls.encode_dict(value) elif isinstance(value, bool): return "TRUE" if value else "FALSE" elif isinstance(value, int) or isinstance(value, float): return str(value) elif isinstance(value, collections.abc.Iterable): # convert all iterables to vectors return cls.encode_list(value) else: # Try to convert from numpy if numpy is present try: import numpy as np if isinstance(value, np.number): return str(value) except ImportError: pass raise ValueError("Unsupported value for conversion into R: {}".format(value)) @classmethod def encode_list(cls, l): return "c({})".format(", ".join(map(cls.encode_value, l))) @classmethod def encode_items(cls, items): def encode_item(item): name, value = item return '"{}" = {}'.format(name, cls.encode_value(value)) return ", ".join(map(encode_item, items)) @classmethod def encode_dict(cls, d): d = "list({})".format(cls.encode_items(d.items())) return d @classmethod def encode_namedlist(cls, namedlist): positional = ", ".join(map(cls.encode_value, namedlist)) named = cls.encode_items(namedlist.items()) source = "list(" if positional: source += positional if named: source += ", " + named source += ")" return source class JuliaEncoder: """Encoding Pyton data structures into Julia.""" @classmethod def encode_value(cls, value): if value is None: return "nothing" elif isinstance(value, str): return repr(value) elif isinstance(value, dict): return cls.encode_dict(value) elif isinstance(value, bool): return "true" if value else "false" elif isinstance(value, int) or isinstance(value, float): return str(value) elif isinstance(value, collections.abc.Iterable): # convert all iterables to vectors return cls.encode_list(value) else: # Try to convert from numpy if numpy is present try: import numpy as np if isinstance(value, np.number): return str(value) except ImportError: pass raise ValueError( "Unsupported value for conversion into Julia: {}".format(value) ) @classmethod def encode_list(cls, l): return "[{}]".format(", ".join(map(cls.encode_value, l))) @classmethod def encode_items(cls, items): def encode_item(item): name, value = item return '"{}" => {}'.format(name, cls.encode_value(value)) return ", ".join(map(encode_item, items)) @classmethod def encode_positional_items(cls, namedlist): encoded = "" for index, value in enumerate(namedlist): encoded += "{} => {}, ".format(index + 1, cls.encode_value(value)) return encoded @classmethod def encode_dict(cls, d): d = "Dict({})".format(cls.encode_items(d.items())) return d @classmethod def encode_namedlist(cls, namedlist): positional = cls.encode_positional_items(namedlist) named = cls.encode_items(namedlist.items()) source = "Dict(" if positional: source += positional if named: source += named source += ")" return source class ScriptBase(ABC): def __init__( self, path, source, basedir, input_, output, params, wildcards, threads, resources, log, config, rulename, conda_env, singularity_img, singularity_args, env_modules, bench_record, jobid, bench_iteration, cleanup_scripts, shadow_dir, ): self.path = path self.source = source self.basedir = basedir self.input = input_ self.output = output self.params = params self.wildcards = wildcards self.threads = threads self.resources = resources self.log = log self.config = config self.rulename = rulename self.conda_env = conda_env self.singularity_img = singularity_img self.singularity_args = singularity_args self.env_modules = env_modules self.bench_record = bench_record self.jobid = jobid self.bench_iteration = bench_iteration self.cleanup_scripts = cleanup_scripts self.shadow_dir = shadow_dir def evaluate(self): fd = None try: # generate preamble preamble = self.get_preamble() # write script dir_ = ".snakemake/scripts" os.makedirs(dir_, exist_ok=True) with tempfile.NamedTemporaryFile( suffix="." + os.path.basename(self.path), dir=dir_, delete=False ) as fd: self.write_script(preamble, fd) # execute script self.execute_script(fd.name) except URLError as e: raise WorkflowError(e) finally: if fd and self.cleanup_scripts: os.remove(fd.name) else: if fd: logger.warning("Not cleaning up %s" % fd.name) else: # nothing to clean up (TODO: ??) pass @abstractmethod def get_preamble(self): ... @abstractmethod def write_script(self, preamble, fd): ... @abstractmethod def execute_script(self, fname): ... def _execute_cmd(self, cmd, **kwargs): shell( cmd, bench_record=self.bench_record, conda_env=self.conda_env, singularity_img=self.singularity_img, shadow_dir=self.shadow_dir, env_modules=self.env_modules, **kwargs ) class PythonScript(ScriptBase): @staticmethod def generate_preamble( path, source, basedir, input_, output, params, wildcards, threads, resources, log, config, rulename, conda_env, singularity_img, singularity_args, env_modules, bench_record, jobid, bench_iteration, cleanup_scripts, shadow_dir, preamble_addendum="", ): wrapper_path = path[7:] if path.startswith("file://") else path snakemake = Snakemake( input_, output, params, wildcards, threads, resources, log, config, rulename, bench_iteration, os.path.dirname(wrapper_path), ) snakemake = pickle.dumps(snakemake) # Obtain search path for current snakemake module. # The module is needed for unpickling in the script. # We append it at the end (as a fallback). searchpath = SNAKEMAKE_SEARCHPATH if singularity_img is not None: searchpath = singularity.SNAKEMAKE_MOUNTPOINT searchpath = repr(searchpath) # For local scripts, add their location to the path in case they use path-based imports if path.startswith("file://"): searchpath += ", " + repr(os.path.dirname(path[7:])) return textwrap.dedent( """ ######## Snakemake header ######## import sys; sys.path.extend([{searchpath}]); import pickle; snakemake = pickle.loads({snakemake}); from snakemake.logging import logger; logger.printshellcmds = {printshellcmds}; {preamble_addendum} ######## Original script ######### """ ).format( searchpath=searchpath, snakemake=snakemake, printshellcmds=logger.printshellcmds, preamble_addendum=preamble_addendum, ) def get_preamble(self): wrapper_path = self.path[7:] if self.path.startswith("file://") else self.path preamble_addendum = "__real_file__ = __file__; __file__ = {file_override};".format( file_override=repr(os.path.realpath(wrapper_path)) ) return PythonScript.generate_preamble( self.path, self.source, self.basedir, self.input, self.output, self.params, self.wildcards, self.threads, self.resources, self.log, self.config, self.rulename, self.conda_env, self.singularity_img, self.singularity_args, self.env_modules, self.bench_record, self.jobid, self.bench_iteration, self.cleanup_scripts, self.shadow_dir, preamble_addendum=preamble_addendum, ) def write_script(self, preamble, fd): fd.write(preamble.encode()) fd.write(self.source) def execute_script(self, fname): py_exec = sys.executable if self.conda_env is not None: py = os.path.join(self.conda_env, "bin", "python") if os.path.exists(py): out = subprocess.check_output( [py, "--version"], stderr=subprocess.STDOUT, universal_newlines=True ) ver = tuple(map(int, PY_VER_RE.match(out).group("ver_min").split("."))) if ver >= MIN_PY_VERSION: # Python version is new enough, make use of environment # to execute script py_exec = "python" else: logger.warning( "Conda environment defines Python " "version < {0}.{1}. Using Python of the " "master process to execute " "script. Note that this cannot be avoided, " "because the script uses data structures from " "Snakemake which are Python >={0}.{1} " "only.".format(*MIN_PY_VERSION) ) if self.singularity_img is not None: # use python from image py_exec = "python" if self.env_modules is not None: # use python from environment module py_exec = "python" # use the same Python as the running process or the one from the environment self._execute_cmd("{py_exec} {fname:q}", py_exec=py_exec, fname=fname) class RScript(ScriptBase): @staticmethod def generate_preamble( path, source, basedir, input_, output, params, wildcards, threads, resources, log, config, rulename, conda_env, singularity_img, singularity_args, env_modules, bench_record, jobid, bench_iteration, cleanup_scripts, shadow_dir, preamble_addendum="", ): return textwrap.dedent( """ ######## Snakemake header ######## library(methods) Snakemake <- setClass( "Snakemake", slots = c( input = "list", output = "list", params = "list", wildcards = "list", threads = "numeric", log = "list", resources = "list", config = "list", rule = "character", bench_iteration = "numeric", scriptdir = "character", source = "function" ) ) snakemake <- Snakemake( input = {}, output = {}, params = {}, wildcards = {}, threads = {}, log = {}, resources = {}, config = {}, rule = {}, bench_iteration = {}, scriptdir = {}, source = function(...){{ wd <- getwd() setwd(snakemake@scriptdir) source(...) setwd(wd) }} ) {preamble_addendum} ######## Original script ######### """ ).format( REncoder.encode_namedlist(input_), REncoder.encode_namedlist(output), REncoder.encode_namedlist(params), REncoder.encode_namedlist(wildcards), threads, REncoder.encode_namedlist(log), REncoder.encode_namedlist( { name: value for name, value in resources.items() if name != "_cores" and name != "_nodes" } ), REncoder.encode_dict(config), REncoder.encode_value(rulename), REncoder.encode_numeric(bench_iteration), REncoder.encode_value( os.path.dirname(path[7:]) if path.startswith("file://") else os.path.dirname(path) ), preamble_addendum=preamble_addendum, ) def get_preamble(self): return RScript.generate_preamble( self.path, self.source, self.basedir, self.input, self.output, self.params, self.wildcards, self.threads, self.resources, self.log, self.config, self.rulename, self.conda_env, self.singularity_img, self.singularity_args, self.env_modules, self.bench_record, self.jobid, self.bench_iteration, self.cleanup_scripts, self.shadow_dir, ) def write_script(self, preamble, fd): fd.write(preamble.encode()) fd.write(self.source) def execute_script(self, fname): if self.conda_env is not None and "R_LIBS" in os.environ: logger.warning( "R script job uses conda environment but " "R_LIBS environment variable is set. This " "is likely not intended, as R_LIBS can " "interfere with R packages deployed via " "conda. Consider running `unset R_LIBS` or " "remove it entirely before executing " "Snakemake." ) self._execute_cmd("Rscript --vanilla {fname:q}", fname=fname) class RMarkdown(ScriptBase): def get_preamble(self): return textwrap.dedent( """ ######## Snakemake header ######## library(methods) Snakemake <- setClass( "Snakemake", slots = c( input = "list", output = "list", params = "list", wildcards = "list", threads = "numeric", log = "list", resources = "list", config = "list", rule = "character", bench_iteration = "numeric", scriptdir = "character", source = "function" ) ) snakemake <- Snakemake( input = {}, output = {}, params = {}, wildcards = {}, threads = {}, log = {}, resources = {}, config = {}, rule = {}, bench_iteration = {}, scriptdir = {}, source = function(...){{ wd <- getwd() setwd(snakemake@scriptdir) source(...) setwd(wd) }} ) ######## Original script ######### """ ).format( REncoder.encode_namedlist(self.input), REncoder.encode_namedlist(self.output), REncoder.encode_namedlist(self.params), REncoder.encode_namedlist(self.wildcards), self.threads, REncoder.encode_namedlist(self.log), REncoder.encode_namedlist( { name: value for name, value in self.resources.items() if name != "_cores" and name != "_nodes" } ), REncoder.encode_dict(self.config), REncoder.encode_value(self.rulename), REncoder.encode_numeric(self.bench_iteration), REncoder.encode_value( os.path.dirname(self.path[7:]) if self.path.startswith("file://") else os.path.dirname(self.path) ), ) def write_script(self, preamble, fd): # Insert Snakemake object after the RMarkdown header code = self.source.decode() pos = next(itertools.islice(re.finditer(r"---\n", code), 1, 2)).start() + 3 fd.write(str.encode(code[:pos])) preamble = textwrap.dedent( """ ```{r, echo=FALSE, message=FALSE, warning=FALSE} %s ``` """ % preamble ) fd.write(preamble.encode()) fd.write(str.encode(code[pos:])) def execute_script(self, fname): if len(self.output) != 1: raise WorkflowError( "RMarkdown scripts (.Rmd) may only have a single output file." ) out = os.path.abspath(self.output[0]) self._execute_cmd( 'Rscript --vanilla -e \'rmarkdown::render("{fname}", output_file="{out}", quiet=TRUE, knit_root_dir = "{workdir}", params = list(rmd="{fname}"))\'', fname=fname, out=out, workdir=os.getcwd(), ) class JuliaScript(ScriptBase): def get_preamble(self): return textwrap.dedent( """ ######## Snakemake header ######## struct Snakemake input::Dict output::Dict params::Dict wildcards::Dict threads::Int64 log::Dict resources::Dict config::Dict rule::String bench_iteration scriptdir::String #source::Any end snakemake = Snakemake( {}, #input::Dict {}, #output::Dict {}, #params::Dict {}, #wildcards::Dict {}, #threads::Int64 {}, #log::Dict {}, #resources::Dict {}, #config::Dict {}, #rule::String {}, #bench_iteration::Int64 {}, #scriptdir::String #, #source::Any ) ######## Original script ######### """.format( JuliaEncoder.encode_namedlist(self.input), JuliaEncoder.encode_namedlist(self.output), JuliaEncoder.encode_namedlist(self.params), JuliaEncoder.encode_namedlist(self.wildcards), JuliaEncoder.encode_value(self.threads), JuliaEncoder.encode_namedlist(self.log), JuliaEncoder.encode_namedlist( { name: value for name, value in self.resources.items() if name != "_cores" and name != "_nodes" } ), JuliaEncoder.encode_dict(self.config), JuliaEncoder.encode_value(self.rulename), JuliaEncoder.encode_value(self.bench_iteration), JuliaEncoder.encode_value( os.path.dirname(self.path[7:]) if self.path.startswith("file://") else os.path.dirname(self.path) ), ).replace( "'", '"' ) ) def write_script(self, preamble, fd): fd.write(preamble.encode()) fd.write(self.source) def execute_script(self, fname): self._execute_cmd("julia {fname:q}", fname=fname) def get_source(path, basedir="."): import nbformat source = None if not path.startswith("http") and not path.startswith("git+file"): if path.startswith("file://"): path = path[7:] elif path.startswith("file:"): path = path[5:] if not os.path.isabs(path): path = os.path.abspath(os.path.join(basedir, path)) path = "file://" + path path = format(path, stepout=1) if path.startswith("file://"): sourceurl = "file:" + pathname2url(path[7:]) elif path.startswith("git+file"): source = git_content(path) (root_path, file_path, version) = split_git_path(path) path = path.rstrip("@" + version) else: sourceurl = path if source is None: with urlopen(sourceurl) as source: source = source.read() language = None if path.endswith(".py"): language = "python" elif path.endswith(".ipynb"): language = "jupyter" elif path.endswith(".R"): language = "r" elif path.endswith(".Rmd"): language = "rmarkdown" elif path.endswith(".jl"): language = "julia" # detect kernel language for Jupyter Notebooks if language == "jupyter": nb = nbformat.reads(source, as_version=nbformat.NO_CONVERT) kernel_language = nb["metadata"]["language_info"]["name"] language += "_" + kernel_language.lower() return path, source, language def script( path, basedir, input, output, params, wildcards, threads, resources, log, config, rulename, conda_env, singularity_img, singularity_args, env_modules, bench_record, jobid, bench_iteration, cleanup_scripts, shadow_dir, ): """ Load a script from the given basedir + path and execute it. """ path, source, language = get_source(path, basedir) ExecClass = { "python": PythonScript, "r": RScript, "rmarkdown": RMarkdown, "julia": JuliaScript, }.get(language, None) if ExecClass is None: raise ValueError( "Unsupported script: Expecting either Python (.py), R (.R), RMarkdown (.Rmd) or Julia (.jl) script." ) executor = ExecClass( path, source, basedir, input, output, params, wildcards, threads, resources, log, config, rulename, conda_env, singularity_img, singularity_args, env_modules, bench_record, jobid, bench_iteration, cleanup_scripts, shadow_dir, ) executor.evaluate() snakemake-5.10.0/snakemake/shell.py000066400000000000000000000130001361131222100171360ustar00rootroot00000000000000__author__ = "Johannes Köster" __copyright__ = "Copyright 2015-2019, Johannes Köster" __email__ = "koester@jimmy.harvard.edu" __license__ = "MIT" import _io import sys import os import subprocess as sp import inspect import shutil import threading from snakemake.utils import format from snakemake.logging import logger from snakemake.deployment import singularity from snakemake.deployment.conda import Conda import snakemake __author__ = "Johannes Köster" STDOUT = sys.stdout if not isinstance(sys.stdout, _io.TextIOWrapper): # workaround for nosetest since it overwrites sys.stdout # in a strange way that does not work with Popen STDOUT = None class shell: _process_args = {} _process_prefix = "" _process_suffix = "" _lock = threading.Lock() _processes = {} @classmethod def get_executable(cls): return cls._process_args.get("executable", None) @classmethod def check_output(cls, cmd, **kwargs): return sp.check_output( cmd, shell=True, executable=cls.get_executable(), **kwargs ) @classmethod def executable(cls, cmd): if os.name == "posix" and not os.path.isabs(cmd): # always enforce absolute path cmd = shutil.which(cmd) if not cmd: raise WorkflowError( "Cannot set default shell {} because it " "is not available in your " "PATH.".format(cmd) ) if os.path.split(cmd)[-1] == "bash": cls._process_prefix = "set -euo pipefail; " cls._process_args["executable"] = cmd @classmethod def prefix(cls, prefix): cls._process_prefix = format(prefix, stepout=2) @classmethod def suffix(cls, suffix): cls._process_suffix = format(suffix, stepout=2) @classmethod def kill(cls, jobid): with cls._lock: if jobid in cls._processes: cls._processes[jobid].kill() del cls._processes[jobid] @classmethod def cleanup(cls): with cls._lock: cls._processes.clear() def __new__( cls, cmd, *args, iterable=False, read=False, bench_record=None, **kwargs ): if "stepout" in kwargs: raise KeyError("Argument stepout is not allowed in shell command.") cmd = format(cmd, *args, stepout=2, **kwargs) context = inspect.currentframe().f_back.f_locals # add kwargs to context (overwriting the locals of the caller) context.update(kwargs) stdout = sp.PIPE if iterable or read else STDOUT close_fds = sys.platform != "win32" jobid = context.get("jobid") if not context.get("is_shell"): logger.shellcmd(cmd) env_prefix = "" conda_env = context.get("conda_env", None) singularity_img = context.get("singularity_img", None) env_modules = context.get("env_modules", None) shadow_dir = context.get("shadow_dir", None) cmd = "{} {} {}".format( cls._process_prefix, cmd.strip(), cls._process_suffix ).strip() if env_modules: cmd = env_modules.shellcmd(cmd) logger.info("Activating environment modules: {}".format(env_modules)) if conda_env: cmd = Conda(singularity_img).shellcmd(conda_env, cmd) if singularity_img: args = context.get("singularity_args", "") cmd = singularity.shellcmd( singularity_img, cmd, args, shell_executable=cls._process_args["executable"], container_workdir=shadow_dir, ) logger.info("Activating singularity image {}".format(singularity_img)) if conda_env: logger.info("Activating conda environment: {}".format(conda_env)) proc = sp.Popen( cmd, bufsize=-1, shell=True, stdout=stdout, universal_newlines=iterable or None, close_fds=close_fds, **cls._process_args ) if jobid is not None: with cls._lock: cls._processes[jobid] = proc ret = None if iterable: return cls.iter_stdout(proc, cmd) if read: ret = proc.stdout.read() if bench_record is not None: from snakemake.benchmark import benchmarked with benchmarked(proc.pid, bench_record): retcode = proc.wait() else: retcode = proc.wait() if jobid is not None: with cls._lock: del cls._processes[jobid] if retcode: raise sp.CalledProcessError(retcode, cmd) return ret @staticmethod def iter_stdout(proc, cmd): for l in proc.stdout: yield l[:-1] retcode = proc.wait() if retcode: raise sp.CalledProcessError(retcode, cmd) # set bash as default shell on posix compatible OS if os.name == "posix": if not shutil.which("bash"): logger.warning( "Cannot set bash as default shell because it is not " "available in your PATH. Falling back to sh." ) if not shutil.which("sh"): logger.warning( "Cannot fall back to sh since it seems to be not " "available on this system. Using whatever is " "defined as default." ) else: shell.executable("sh") else: shell.executable("bash") snakemake-5.10.0/snakemake/stats.py000066400000000000000000000050351361131222100171760ustar00rootroot00000000000000__author__ = "Johannes Köster" __copyright__ = "Copyright 2015-2019, Johannes Köster" __email__ = "koester@jimmy.harvard.edu" __license__ = "MIT" import time import csv import json from collections import defaultdict import snakemake.jobs fmt_time = time.ctime class Stats: def __init__(self): self.starttime = dict() self.endtime = dict() def report_job_start(self, job): if job.is_group(): for j in job: self.starttime[j] = time.time() else: self.starttime[job] = time.time() def report_job_end(self, job): if job.is_group(): for j in job: self.endtime[j] = time.time() else: self.endtime[job] = time.time() @property def rule_stats(self): runtimes = defaultdict(list) for job, t in self.starttime.items(): runtimes[job.rule].append(self.endtime[job] - t) for rule, runtimes in runtimes.items(): yield (rule, sum(runtimes) / len(runtimes), min(runtimes), max(runtimes)) @property def file_stats(self): for job, t in self.starttime.items(): for f in job.expanded_output: start, stop = t, self.endtime[job] yield f, fmt_time(start), fmt_time(stop), stop - start, job @property def overall_runtime(self): if self.starttime and self.endtime: return max(self.endtime.values()) - min(self.starttime.values()) else: return 0 def to_json(self, path): rule_stats = { rule.name: { "mean-runtime": mean_runtime, "min-runtime": min_runtime, "max-runtime": max_runtime, } for rule, mean_runtime, min_runtime, max_runtime in self.rule_stats } file_stats = { f: { "start-time": start, "stop-time": stop, "duration": duration, "priority": job.priority if job.priority != snakemake.jobs.Job.HIGHEST_PRIORITY else "highest", "resources": dict(job.resources.items()), } for f, start, stop, duration, job in self.file_stats } with open(path, "w") as f: json.dump( { "total_runtime": self.overall_runtime, "rules": rule_stats, "files": file_stats, }, f, indent=4, ) snakemake-5.10.0/snakemake/utils.py000066400000000000000000000442761361131222100172120ustar00rootroot00000000000000__author__ = "Johannes Köster" __copyright__ = "Copyright 2015-2019, Johannes Köster" __email__ = "koester@jimmy.harvard.edu" __license__ = "MIT" import os import json import re import inspect import textwrap import platform from itertools import chain import collections import multiprocessing import string import shlex import sys from urllib.parse import urljoin from snakemake.io import regex, Namedlist, Wildcards, _load_configfile from snakemake.logging import logger from snakemake.exceptions import WorkflowError import snakemake def validate(data, schema, set_default=True): """Validate data with JSON schema at given path. Args: data (object): data to validate. Can be a config dict or a pandas data frame. schema (str): Path to JSON schema used for validation. The schema can also be in YAML format. If validating a pandas data frame, the schema has to describe a row record (i.e., a dict with column names as keys pointing to row values). See http://json-schema.org. The path is interpreted relative to the Snakefile when this function is called. set_default (bool): set default values defined in schema. See http://python-jsonschema.readthedocs.io/en/latest/faq/ for more information """ try: import jsonschema from jsonschema import validators, RefResolver except ImportError: raise WorkflowError( "The Python 3 package jsonschema must be installed " "in order to use the validate directive." ) if not os.path.isabs(schema): frame = inspect.currentframe().f_back # if workflow object is not available this has not been started from a workflow if "workflow" in frame.f_globals: workflow = frame.f_globals["workflow"] schema = os.path.join(workflow.current_basedir, schema) schemafile = schema schema = _load_configfile(schema, filetype="Schema") resolver = RefResolver( urljoin("file:", schemafile), schema, handlers={"file": lambda uri: _load_configfile(re.sub("^file://", "", uri))}, ) # Taken from http://python-jsonschema.readthedocs.io/en/latest/faq/ def extend_with_default(validator_class): validate_properties = validator_class.VALIDATORS["properties"] def set_defaults(validator, properties, instance, schema): for property, subschema in properties.items(): if "default" in subschema: instance.setdefault(property, subschema["default"]) for error in validate_properties(validator, properties, instance, schema): yield error return validators.extend(validator_class, {"properties": set_defaults}) Validator = validators.validator_for(schema) if Validator.META_SCHEMA["$schema"] != schema["$schema"]: logger.warning( "No validator found for JSON Schema version identifier '{}'".format( schema["$schema"] ) ) logger.warning( "Defaulting to validator for JSON Schema version '{}'".format( Validator.META_SCHEMA["$schema"] ) ) logger.warning("Note that schema file may not be validated correctly.") DefaultValidator = extend_with_default(Validator) if not isinstance(data, dict): try: import pandas as pd recordlist = [] if isinstance(data, pd.DataFrame): for i, record in enumerate(data.to_dict("records")): record = {k: v for k, v in record.items() if not pd.isnull(v)} try: if set_default: DefaultValidator(schema, resolver=resolver).validate(record) recordlist.append(record) else: jsonschema.validate(record, schema, resolver=resolver) except jsonschema.exceptions.ValidationError as e: raise WorkflowError( "Error validating row {} of data frame.".format(i), e ) if set_default: newdata = pd.DataFrame(recordlist, data.index) newcol = ~newdata.columns.isin(data.columns) n = len(data.columns) for col in newdata.loc[:, newcol].columns: data.insert(n, col, newdata.loc[:, col]) n = n + 1 return except ImportError: pass raise WorkflowError("Unsupported data type for validation.") else: try: if set_default: DefaultValidator(schema, resolver=resolver).validate(data) else: jsonschema.validate(data, schema, resolver=resolver) except jsonschema.exceptions.ValidationError as e: raise WorkflowError("Error validating config file.", e) def simplify_path(path): """Return a simplified version of the given path.""" relpath = os.path.relpath(path) if relpath.startswith("../../"): return path else: return relpath def linecount(filename): """Return the number of lines of given file. Args: filename (str): the path to the file """ with open(filename) as f: return sum(1 for l in f) def listfiles(pattern, restriction=None, omit_value=None): """Yield a tuple of existing filepaths for the given pattern. Wildcard values are yielded as the second tuple item. Args: pattern (str): a filepattern. Wildcards are specified in snakemake syntax, e.g. "{id}.txt" restriction (dict): restrict to wildcard values given in this dictionary omit_value (str): wildcard value to omit Yields: tuple: The next file matching the pattern, and the corresponding wildcards object """ pattern = os.path.normpath(pattern) first_wildcard = re.search("{[^{]", pattern) if first_wildcard: dirname = os.path.dirname(pattern[: first_wildcard.start()]) if not dirname: dirname = "." else: dirname = os.path.dirname(pattern) pattern = re.compile(regex(pattern)) for dirpath, dirnames, filenames in os.walk(dirname): for f in chain(filenames, dirnames): if dirpath != ".": f = os.path.normpath(os.path.join(dirpath, f)) match = re.match(pattern, f) if match: wildcards = Namedlist(fromdict=match.groupdict()) if restriction is not None: invalid = any( omit_value not in v and v != wildcards[k] for k, v in restriction.items() ) if not invalid: yield f, wildcards else: yield f, wildcards def makedirs(dirnames): """Recursively create the given directory or directories without reporting errors if they are present. """ if isinstance(dirnames, str): dirnames = [dirnames] for dirname in dirnames: os.makedirs(dirname, exist_ok=True) def report( text, path, stylesheet=None, defaultenc="utf8", template=None, metadata=None, **files ): """Create an HTML report using python docutils. This is deprecated in favor of the --report flag. Attention: This function needs Python docutils to be installed for the python installation you use with Snakemake. All keywords not listed below are intepreted as paths to files that shall be embedded into the document. They keywords will be available as link targets in the text. E.g. append a file as keyword arg via F1=input[0] and put a download link in the text like this: .. code:: python report(''' ============== Report for ... ============== Some text. A link to an embedded file: F1_. Further text. ''', outputpath, F1=input[0]) Instead of specifying each file as a keyword arg, you can also expand the input of your rule if it is completely named, e.g.: report(''' Some text... ''', outputpath, **input) Args: text (str): The "restructured text" as it is expected by python docutils. path (str): The path to the desired output file stylesheet (str): An optional path to a css file that defines the style of the document. This defaults to /report.css. Use the default to get a hint how to create your own. defaultenc (str): The encoding that is reported to the browser for embedded text files, defaults to utf8. template (str): An optional path to a docutils HTML template. metadata (str): E.g. an optional author name or email address. """ if stylesheet is None: os.path.join(os.path.dirname(__file__), "report.css") try: import snakemake.report except ImportError: raise WorkflowError( "Python 3 package docutils needs to be installed to use the report function." ) snakemake.report.report( text, path, stylesheet=stylesheet, defaultenc=defaultenc, template=template, metadata=metadata, **files ) def R(code): """Execute R code. This is deprecated in favor of the ``script`` directive. This function executes the R code given as a string. The function requires rpy2 to be installed. Args: code (str): R code to be executed """ try: import rpy2.robjects as robjects except ImportError: raise ValueError( "Python 3 package rpy2 needs to be installed to use the R function." ) robjects.r(format(textwrap.dedent(code), stepout=2)) class SequenceFormatter(string.Formatter): """string.Formatter subclass with special behavior for sequences. This class delegates formatting of individual elements to another formatter object. Non-list objects are formatted by calling the delegate formatter's "format_field" method. List-like objects (list, tuple, set, frozenset) are formatted by formatting each element of the list according to the specified format spec using the delegate formatter and then joining the resulting strings with a separator (space by default). """ def __init__( self, separator=" ", element_formatter=string.Formatter(), *args, **kwargs ): self.separator = separator self.element_formatter = element_formatter def format_element(self, elem, format_spec): """Format a single element For sequences, this is called once for each element in a sequence. For anything else, it is called on the entire object. It is intended to be overridden in subclases. """ return self.element_formatter.format_field(elem, format_spec) def format_field(self, value, format_spec): if isinstance(value, Wildcards): return ",".join( "{}={}".format(name, value) for name, value in sorted(value.items(), key=lambda item: item[0]) ) if isinstance(value, (list, tuple, set, frozenset)): return self.separator.join( self.format_element(v, format_spec) for v in value ) else: return self.format_element(value, format_spec) class QuotedFormatter(string.Formatter): """Subclass of string.Formatter that supports quoting. Using this formatter, any field can be quoted after formatting by appending "q" to its format string. By default, shell quoting is performed using "shlex.quote", but you can pass a different quote_func to the constructor. The quote_func simply has to take a string argument and return a new string representing the quoted form of the input string. Note that if an element after formatting is the empty string, it will not be quoted. """ def __init__(self, quote_func=None, *args, **kwargs): if quote_func is None: quote_func = shlex.quote if not ON_WINDOWS else argvquote self.quote_func = quote_func super().__init__(*args, **kwargs) def format_field(self, value, format_spec): do_quote = format_spec.endswith("q") if do_quote: format_spec = format_spec[:-1] formatted = super().format_field(value, format_spec) if do_quote and formatted != "": formatted = self.quote_func(formatted) return formatted class AlwaysQuotedFormatter(QuotedFormatter): """Subclass of QuotedFormatter that always quotes. Usage is identical to QuotedFormatter, except that it *always* acts like "q" was appended to the format spec. """ def format_field(self, value, format_spec): if not format_spec.endswith("q"): format_spec += "q" return super().format_field(value, format_spec) def format(_pattern, *args, stepout=1, _quote_all=False, **kwargs): """Format a pattern in Snakemake style. This means that keywords embedded in braces are replaced by any variable values that are available in the current namespace. """ frame = inspect.currentframe().f_back while stepout > 1: if not frame.f_back: break frame = frame.f_back stepout -= 1 variables = dict(frame.f_globals) # add local variables from calling rule/function variables.update(frame.f_locals) if "self" in variables and sys.version_info < (3, 5): # self is the first arg of fmt.format as well. Not removing it would # cause a multiple values error on Python <=3.4.2. del variables["self"] variables.update(kwargs) fmt = SequenceFormatter(separator=" ") if _quote_all: fmt.element_formatter = AlwaysQuotedFormatter() else: fmt.element_formatter = QuotedFormatter() try: return fmt.format(_pattern, *args, **variables) except KeyError as ex: raise NameError( "The name {} is unknown in this context. Please " "make sure that you defined that variable. " "Also note that braces not used for variable access " "have to be escaped by repeating them, " "i.e. {{{{print $1}}}}".format(str(ex)) ) class Unformattable: def __init__(self, errormsg="This cannot be used for formatting"): self.errormsg = errormsg def __str__(self): raise ValueError(self.errormsg) def read_job_properties( jobscript, prefix="# properties", pattern=re.compile("# properties = (.*)") ): """Read the job properties defined in a snakemake jobscript. This function is a helper for writing custom wrappers for the snakemake --cluster functionality. Applying this function to a jobscript will return a dict containing information about the job. """ with open(jobscript) as jobscript: for m in map(pattern.match, jobscript): if m: return json.loads(m.group(1)) def min_version(version): """Require minimum snakemake version, raise workflow error if not met.""" import pkg_resources if pkg_resources.parse_version(snakemake.__version__) < pkg_resources.parse_version( version ): raise WorkflowError("Expecting Snakemake version {} or higher.".format(version)) def update_config(config, overwrite_config): """Recursively update dictionary config with overwrite_config. See http://stackoverflow.com/questions/3232943/update-value-of-a-nested-dictionary-of-varying-depth for details. Args: config (dict): dictionary to update overwrite_config (dict): dictionary whose items will overwrite those in config """ def _update(d, u): for (key, value) in u.items(): if isinstance(value, collections.abc.Mapping): d[key] = _update(d.get(key, {}), value) else: d[key] = value return d _update(config, overwrite_config) def available_cpu_count(): """ Return the number of available virtual or physical CPUs on this system. The number of available CPUs can be smaller than the total number of CPUs when the cpuset(7) mechanism is in use, as is the case on some cluster systems. Adapted from http://stackoverflow.com/a/1006301/715090 """ try: with open("/proc/self/status") as f: status = f.read() m = re.search(r"(?m)^Cpus_allowed:\s*(.*)$", status) if m: res = bin(int(m.group(1).replace(",", ""), 16)).count("1") if res > 0: return min(res, multiprocessing.cpu_count()) except IOError: pass return multiprocessing.cpu_count() def argvquote(arg, force=True): """ Returns an argument quoted in such a way that that CommandLineToArgvW on Windows will return the argument string unchanged. This is the same thing Popen does when supplied with an list of arguments. Arguments in a command line should be separated by spaces; this function does not add these spaces. This implementation follows the suggestions outlined here: https://blogs.msdn.microsoft.com/twistylittlepassagesallalike/2011/04/23/everyone-quotes-command-line-arguments-the-wrong-way/ """ if not force and len(arg) != 0 and not any([c in arg for c in ' \t\n\v"']): return arg else: n_backslashes = 0 cmdline = '"' for c in arg: if c == "\\": # first count the number of current backslashes n_backslashes += 1 continue if c == '"': # Escape all backslashes and the following double quotation mark cmdline += (n_backslashes * 2 + 1) * "\\" else: # backslashes are not special here cmdline += n_backslashes * "\\" n_backslashes = 0 cmdline += c # Escape all backslashes, but let the terminating # double quotation mark we add below be interpreted # as a metacharacter cmdline += +n_backslashes * 2 * "\\" + '"' return cmdline ON_WINDOWS = platform.system() == "Windows" snakemake-5.10.0/snakemake/workflow.py000066400000000000000000001350511361131222100177140ustar00rootroot00000000000000__author__ = "Johannes Köster" __copyright__ = "Copyright 2015-2019, Johannes Köster" __email__ = "koester@jimmy.harvard.edu" __license__ = "MIT" import re import os import sys import signal import json import urllib from collections import OrderedDict from itertools import filterfalse, chain from functools import partial from operator import attrgetter import copy import subprocess from pathlib import Path from snakemake.logging import logger, format_resources, format_resource_names from snakemake.rules import Rule, Ruleorder, RuleProxy from snakemake.exceptions import ( RuleException, CreateRuleException, UnknownRuleException, NoRulesException, print_exception, WorkflowError, ) from snakemake.shell import shell from snakemake.dag import DAG from snakemake.scheduler import JobScheduler from snakemake.parser import parse import snakemake.io from snakemake.io import ( protected, temp, temporary, ancient, directory, expand, dynamic, glob_wildcards, flag, not_iterable, touch, unpack, local, pipe, repeat, report, multiext, IOFile, ) from snakemake.persistence import Persistence from snakemake.utils import update_config from snakemake.script import script from snakemake.notebook import notebook from snakemake.wrapper import wrapper from snakemake.cwl import cwl import snakemake.wrapper from snakemake.common import Mode from snakemake.utils import simplify_path from snakemake.checkpoints import Checkpoint, Checkpoints from snakemake.resources import DefaultResources from snakemake.caching.local import OutputFileCache as LocalOutputFileCache from snakemake.caching.remote import OutputFileCache as RemoteOutputFileCache class Workflow: def __init__( self, snakefile=None, jobscript=None, overwrite_shellcmd=None, overwrite_config=dict(), overwrite_workdir=None, overwrite_configfiles=None, overwrite_clusterconfig=dict(), overwrite_threads=dict(), config_args=None, debug=False, verbose=False, use_conda=False, conda_prefix=None, use_singularity=False, use_env_modules=False, singularity_prefix=None, singularity_args="", shadow_prefix=None, mode=Mode.default, wrapper_prefix=None, printshellcmds=False, restart_times=None, attempt=1, default_remote_provider=None, default_remote_prefix="", run_local=True, default_resources=None, cache=None, nodes=1, cores=1, resources=None, ): """ Create the controller. """ self.global_resources = dict() if resources is None else resources self.global_resources["_cores"] = cores self.global_resources["_nodes"] = nodes self._rules = OrderedDict() self.first_rule = None self._workdir = None self.overwrite_workdir = overwrite_workdir self.workdir_init = os.path.abspath(os.curdir) self._ruleorder = Ruleorder() self._localrules = set() self.linemaps = dict() self.rule_count = 0 self.basedir = os.path.dirname(snakefile) self.snakefile = os.path.abspath(snakefile) self.included = [] self.included_stack = [] self.jobscript = jobscript self.persistence = None self.globals = globals() self._subworkflows = dict() self.overwrite_shellcmd = overwrite_shellcmd self.overwrite_config = overwrite_config self.overwrite_configfiles = overwrite_configfiles self.overwrite_clusterconfig = overwrite_clusterconfig self.overwrite_threads = overwrite_threads self.config_args = config_args self.immediate_submit = None self._onsuccess = lambda log: None self._onerror = lambda log: None self._onstart = lambda log: None self._wildcard_constraints = dict() self.debug = debug self.verbose = verbose self._rulecount = 0 self.use_conda = use_conda self.conda_prefix = conda_prefix self.use_singularity = use_singularity self.use_env_modules = use_env_modules self.singularity_prefix = singularity_prefix self.singularity_args = singularity_args self.shadow_prefix = shadow_prefix self.global_singularity_img = None self.mode = mode self.wrapper_prefix = wrapper_prefix self.printshellcmds = printshellcmds self.restart_times = restart_times self.attempt = attempt self.default_remote_provider = default_remote_provider self.default_remote_prefix = default_remote_prefix self.configfiles = [] self.run_local = run_local self.report_text = None if cache is not None: self.cache_rules = set(cache) if self.default_remote_provider is not None: self.output_file_cache = RemoteOutputFileCache( self.default_remote_provider ) else: self.output_file_cache = LocalOutputFileCache() else: self.output_file_cache = None self.cache_rules = set() if default_resources is not None: self.default_resources = default_resources else: # only _cores and _nodes self.default_resources = DefaultResources() self.iocache = snakemake.io.IOCache() global config config = copy.deepcopy(self.overwrite_config) global cluster_config cluster_config = copy.deepcopy(self.overwrite_clusterconfig) global rules rules = Rules() global checkpoints checkpoints = Checkpoints() def is_cached_rule(self, rule: Rule): return rule.name in self.cache_rules def get_sources(self): files = set() def norm_rule_relpath(f, rule): if not os.path.isabs(f): f = os.path.join(rule.basedir, f) return os.path.relpath(f) # get registered sources for f in self.included: files.add(os.path.relpath(f)) for rule in self.rules: script_path = rule.script or rule.notebook if script_path: script_path = norm_rule_relpath(script_path, rule) files.add(script_path) script_dir = os.path.dirname(script_path) files.update( os.path.join(dirpath, f) for dirpath, _, files in os.walk(script_dir) for f in files ) if rule.conda_env: env_path = norm_rule_relpath(rule.conda_env, rule) files.add(env_path) for f in self.configfiles: files.add(f) # get git-managed files # TODO allow a manifest file as alternative try: out = subprocess.check_output( ["git", "ls-files", "."], stderr=subprocess.PIPE ) for f in out.decode().split("\n"): if f: files.add(os.path.relpath(f)) except subprocess.CalledProcessError as e: if "fatal: not a git repository" in e.stderr.decode().lower(): logger.warning( "Unable to retrieve additional files from git. " "This is not a git repository." ) else: raise WorkflowError( "Error executing git:\n{}".format(e.stderr.decode()) ) return files @property def subworkflows(self): return self._subworkflows.values() @property def rules(self): return self._rules.values() @property def cores(self): return self.global_resources["_cores"] @property def nodes(self): return self.global_resources["_nodes"] @property def concrete_files(self): return ( file for rule in self.rules for file in chain(rule.input, rule.output) if not callable(file) and not file.contains_wildcard() ) def check(self): for clause in self._ruleorder: for rulename in clause: if not self.is_rule(rulename): raise UnknownRuleException( rulename, prefix="Error in ruleorder definition." ) def add_rule(self, name=None, lineno=None, snakefile=None, checkpoint=False): """ Add a rule. """ if name is None: name = str(len(self._rules) + 1) if self.is_rule(name): raise CreateRuleException( "The name {} is already used by another rule".format(name) ) rule = Rule(name, self, lineno=lineno, snakefile=snakefile) self._rules[rule.name] = rule self.rule_count += 1 if not self.first_rule: self.first_rule = rule.name return name def is_rule(self, name): """ Return True if name is the name of a rule. Arguments name -- a name """ return name in self._rules def get_rule(self, name): """ Get rule by name. Arguments name -- the name of the rule """ if not self._rules: raise NoRulesException() if not name in self._rules: raise UnknownRuleException(name) return self._rules[name] def list_rules(self, only_targets=False): rules = self.rules if only_targets: rules = filterfalse(Rule.has_wildcards, rules) for rule in rules: logger.rule_info(name=rule.name, docstring=rule.docstring) def list_resources(self): for resource in set( resource for rule in self.rules for resource in rule.resources ): if resource not in "_cores _nodes".split(): logger.info(resource) def is_local(self, rule): return rule.group is None and (rule.name in self._localrules or rule.norun) def check_localrules(self): undefined = self._localrules - set(rule.name for rule in self.rules) if undefined: logger.warning( "localrules directive specifies rules that are not " "present in the Snakefile:\n{}\n".format( "\n".join(map("\t{}".format, undefined)) ) ) def inputfile(self, path): """Mark file as being an input file of the workflow. This also means that eventual --default-remote-provider/prefix settings will be applied to this file. The file is returned as _IOFile object, such that it can e.g. be transparently opened with _IOFile.open(). """ if isinstance(path, Path): path = str(path) if self.default_remote_provider is not None: path = self.apply_default_remote(path) return IOFile(path) def apply_default_remote(self, path): """Apply the defined default remote provider to the given path and return the updated _IOFile. Asserts that default remote provider is defined. """ assert ( self.default_remote_provider is not None ), "No default remote provider is defined, calling this anyway is a bug" path = "{}/{}".format(self.default_remote_prefix, path) path = os.path.normpath(path) return self.default_remote_provider.remote(path) def execute( self, targets=None, dryrun=False, touch=False, local_cores=1, forcetargets=False, forceall=False, forcerun=None, until=[], omit_from=[], prioritytargets=None, quiet=False, keepgoing=False, printshellcmds=False, printreason=False, printdag=False, cluster=None, cluster_sync=None, jobname=None, immediate_submit=False, ignore_ambiguity=False, printrulegraph=False, printfilegraph=False, printd3dag=False, drmaa=None, drmaa_log_dir=None, kubernetes=None, kubernetes_envvars=None, tibanna=None, tibanna_sfn=None, precommand="", container_image=None, stats=None, force_incomplete=False, ignore_incomplete=False, list_version_changes=False, list_code_changes=False, list_input_changes=False, list_params_changes=False, list_untracked=False, list_conda_envs=False, summary=False, archive=None, delete_all_output=False, delete_temp_output=False, detailed_summary=False, latency_wait=3, wait_for_files=None, nolock=False, unlock=False, notemp=False, nodeps=False, cleanup_metadata=None, cleanup_conda=False, cleanup_shadow=False, cleanup_scripts=True, subsnakemake=None, updated_files=None, keep_target_files=False, keep_shadow=False, keep_remote_local=False, allowed_rules=None, max_jobs_per_second=None, max_status_checks_per_second=None, greediness=1.0, no_hooks=False, force_use_threads=False, create_envs_only=False, assume_shared_fs=True, cluster_status=None, report=None, export_cwl=False, batch=None, keepincomplete=False, ): self.check_localrules() self.immediate_submit = immediate_submit self.cleanup_scripts = cleanup_scripts def rules(items): return map(self._rules.__getitem__, filter(self.is_rule, items)) if keep_target_files: def files(items): return filterfalse(self.is_rule, items) else: def files(items): relpath = lambda f: f if os.path.isabs(f) else os.path.relpath(f) return map(relpath, filterfalse(self.is_rule, items)) if not targets: targets = [self.first_rule] if self.first_rule is not None else list() if prioritytargets is None: prioritytargets = list() if forcerun is None: forcerun = list() if until is None: until = list() if omit_from is None: omit_from = list() priorityrules = set(rules(prioritytargets)) priorityfiles = set(files(prioritytargets)) forcerules = set(rules(forcerun)) forcefiles = set(files(forcerun)) untilrules = set(rules(until)) untilfiles = set(files(until)) omitrules = set(rules(omit_from)) omitfiles = set(files(omit_from)) targetrules = set( chain( rules(targets), filterfalse(Rule.has_wildcards, priorityrules), filterfalse(Rule.has_wildcards, forcerules), filterfalse(Rule.has_wildcards, untilrules), ) ) targetfiles = set(chain(files(targets), priorityfiles, forcefiles, untilfiles)) if forcetargets: forcefiles.update(targetfiles) forcerules.update(targetrules) rules = self.rules if allowed_rules: rules = [rule for rule in rules if rule.name in set(allowed_rules)] if wait_for_files is not None: try: snakemake.io.wait_for_files(wait_for_files, latency_wait=latency_wait) except IOError as e: logger.error(str(e)) return False dag = DAG( self, rules, dryrun=dryrun, targetfiles=targetfiles, targetrules=targetrules, # when cleaning up conda, we should enforce all possible jobs # since their envs shall not be deleted forceall=forceall or cleanup_conda, forcefiles=forcefiles, forcerules=forcerules, priorityfiles=priorityfiles, priorityrules=priorityrules, untilfiles=untilfiles, untilrules=untilrules, omitfiles=omitfiles, omitrules=omitrules, ignore_ambiguity=ignore_ambiguity, force_incomplete=force_incomplete, ignore_incomplete=ignore_incomplete or printdag or printrulegraph or printfilegraph, notemp=notemp, keep_remote_local=keep_remote_local, batch=batch, ) self.persistence = Persistence( nolock=nolock, dag=dag, conda_prefix=self.conda_prefix, singularity_prefix=self.singularity_prefix, shadow_prefix=self.shadow_prefix, warn_only=dryrun or printrulegraph or printfilegraph or printdag or summary or archive or list_version_changes or list_code_changes or list_input_changes or list_params_changes or list_untracked or delete_all_output or delete_temp_output, ) if cleanup_metadata: for f in cleanup_metadata: self.persistence.cleanup_metadata(f) return True logger.info("Building DAG of jobs...") dag.init() dag.update_checkpoint_dependencies() # check incomplete has to run BEFORE any call to postprocess dag.check_incomplete() dag.check_dynamic() if unlock: try: self.persistence.cleanup_locks() logger.info("Unlocking working directory.") return True except IOError: logger.error( "Error: Unlocking the directory {} failed. Maybe " "you don't have the permissions?" ) return False try: self.persistence.lock() except IOError: logger.error( "Error: Directory cannot be locked. Please make " "sure that no other Snakemake process is trying to create " "the same files in the following directory:\n{}\n" "If you are sure that no other " "instances of snakemake are running on this directory, " "the remaining lock was likely caused by a kill signal or " "a power loss. It can be removed with " "the --unlock argument.".format(os.getcwd()) ) return False if cleanup_shadow: self.persistence.cleanup_shadow() return True if ( self.subworkflows and not printdag and not printrulegraph and not printfilegraph ): # backup globals globals_backup = dict(self.globals) # execute subworkflows for subworkflow in self.subworkflows: subworkflow_targets = subworkflow.targets(dag) logger.debug( "Files requested from subworkflow:\n {}".format( "\n ".join(subworkflow_targets) ) ) updated = list() if subworkflow_targets: logger.info("Executing subworkflow {}.".format(subworkflow.name)) if not subsnakemake( subworkflow.snakefile, workdir=subworkflow.workdir, targets=subworkflow_targets, configfiles=[subworkflow.configfile], updated_files=updated, ): return False dag.updated_subworkflow_files.update( subworkflow.target(f) for f in updated ) else: logger.info( "Subworkflow {}: Nothing to be done.".format(subworkflow.name) ) if self.subworkflows: logger.info("Executing main workflow.") # rescue globals self.globals.update(globals_backup) dag.postprocess() # deactivate IOCache such that from now on we always get updated # size, existence and mtime information # ATTENTION: this may never be removed without really good reason. # Otherwise weird things may happen. self.iocache.deactivate() # clear and deactivate persistence cache, from now on we want to see updates self.persistence.deactivate_cache() if nodeps: missing_input = [ f for job in dag.targetjobs for f in job.input if dag.needrun(job) and not os.path.exists(f) ] if missing_input: logger.error( "Dependency resolution disabled (--nodeps) " "but missing input " "files detected. If this happens on a cluster, please make sure " "that you handle the dependencies yourself or turn off " "--immediate-submit. Missing input files:\n{}".format( "\n".join(missing_input) ) ) return False updated_files.extend(f for job in dag.needrun_jobs for f in job.output) if export_cwl: from snakemake.cwl import dag_to_cwl import json with open(export_cwl, "w") as cwl: json.dump(dag_to_cwl(dag), cwl, indent=4) return True elif report: from snakemake.report import auto_report auto_report(dag, report) return True elif printd3dag: dag.d3dag() return True elif printdag: print(dag) return True elif printrulegraph: print(dag.rule_dot()) return True elif printfilegraph: print(dag.filegraph_dot()) return True elif summary: print("\n".join(dag.summary(detailed=False))) return True elif detailed_summary: print("\n".join(dag.summary(detailed=True))) return True elif archive: dag.archive(archive) return True elif delete_all_output: dag.clean(only_temp=False, dryrun=dryrun) return True elif delete_temp_output: dag.clean(only_temp=True, dryrun=dryrun) return True elif list_version_changes: items = list(chain(*map(self.persistence.version_changed, dag.jobs))) if items: print(*items, sep="\n") return True elif list_code_changes: items = list(chain(*map(self.persistence.code_changed, dag.jobs))) for j in dag.jobs: items.extend(list(j.outputs_older_than_script_or_notebook())) if items: print(*items, sep="\n") return True elif list_input_changes: items = list(chain(*map(self.persistence.input_changed, dag.jobs))) if items: print(*items, sep="\n") return True elif list_params_changes: items = list(chain(*map(self.persistence.params_changed, dag.jobs))) if items: print(*items, sep="\n") return True elif list_untracked: dag.list_untracked() return True if self.use_singularity: if assume_shared_fs: dag.pull_singularity_imgs( dryrun=dryrun or list_conda_envs, quiet=list_conda_envs ) if self.use_conda: if assume_shared_fs: dag.create_conda_envs( dryrun=dryrun or list_conda_envs or cleanup_conda, quiet=list_conda_envs, ) if create_envs_only: return True if list_conda_envs: print("environment", "container", "location", sep="\t") for env in set(job.conda_env for job in dag.jobs): if env: print( simplify_path(env.file), env.singularity_img_url or "", simplify_path(env.path), sep="\t", ) return True if cleanup_conda: self.persistence.cleanup_conda() return True scheduler = JobScheduler( self, dag, self.cores, local_cores=local_cores, dryrun=dryrun, touch=touch, cluster=cluster, cluster_status=cluster_status, cluster_config=cluster_config, cluster_sync=cluster_sync, jobname=jobname, max_jobs_per_second=max_jobs_per_second, max_status_checks_per_second=max_status_checks_per_second, quiet=quiet, keepgoing=keepgoing, drmaa=drmaa, drmaa_log_dir=drmaa_log_dir, kubernetes=kubernetes, kubernetes_envvars=kubernetes_envvars, tibanna=tibanna, tibanna_sfn=tibanna_sfn, precommand=precommand, container_image=container_image, printreason=printreason, printshellcmds=printshellcmds, latency_wait=latency_wait, greediness=greediness, force_use_threads=force_use_threads, assume_shared_fs=assume_shared_fs, keepincomplete=keepincomplete, ) if not dryrun: if len(dag): shell_exec = shell.get_executable() if shell_exec is not None: logger.info("Using shell: {}".format(shell_exec)) if cluster or cluster_sync or drmaa: logger.resources_info( "Provided cluster nodes: {}".format(self.nodes) ) else: warning = ( "" if self.cores > 1 else " (use --cores to define parallelism)" ) logger.resources_info( "Provided cores: {}{}".format(self.cores, warning) ) logger.resources_info( "Rules claiming more threads " "will be scaled down." ) provided_resources = format_resources(self.global_resources) if provided_resources: logger.resources_info("Provided resources: " + provided_resources) if self.run_local and any(rule.group for rule in self.rules): logger.info("Group jobs: inactive (local execution)") if not self.use_conda and any(rule.conda_env for rule in self.rules): logger.info("Conda environments: ignored") if not self.use_singularity and any( rule.singularity_img for rule in self.rules ): logger.info("Singularity containers: ignored") logger.run_info("\n".join(dag.stats())) else: logger.info("Nothing to be done.") else: # the dryrun case if len(dag): logger.run_info("\n".join(dag.stats())) else: logger.info("Nothing to be done.") return True if quiet: # in case of dryrun and quiet, just print above info and exit return True if not dryrun and not no_hooks: self._onstart(logger.get_logfile()) success = scheduler.schedule() if success: if dryrun: if len(dag): logger.run_info("\n".join(dag.stats())) logger.info( "This was a dry-run (flag -n). The order of jobs " "does not reflect the order of execution." ) logger.remove_logfile() else: if stats: scheduler.stats.to_json(stats) logger.logfile_hint() if not dryrun and not no_hooks: self._onsuccess(logger.get_logfile()) return True else: if not dryrun and not no_hooks: self._onerror(logger.get_logfile()) logger.logfile_hint() return False @property def current_basedir(self): """Basedir of currently parsed Snakefile.""" assert self.included_stack return os.path.abspath(os.path.dirname(self.included_stack[-1])) def include( self, snakefile, overwrite_first_rule=False, print_compilation=False, overwrite_shellcmd=None, ): """ Include a snakefile. """ # check if snakefile is a path to the filesystem if not urllib.parse.urlparse(snakefile).scheme: if not os.path.isabs(snakefile) and self.included_stack: snakefile = os.path.join(self.current_basedir, snakefile) # Could still be an url if relative import was used if not urllib.parse.urlparse(snakefile).scheme: snakefile = os.path.abspath(snakefile) # else it could be an url. # at least we don't want to modify the path for clarity. if snakefile in self.included: logger.info("Multiple include of {} ignored".format(snakefile)) return self.included.append(snakefile) self.included_stack.append(snakefile) global workflow workflow = self first_rule = self.first_rule code, linemap, rulecount = parse( snakefile, overwrite_shellcmd=self.overwrite_shellcmd, rulecount=self._rulecount, ) self._rulecount = rulecount if print_compilation: print(code) # insert the current directory into sys.path # this allows to import modules from the workflow directory sys.path.insert(0, os.path.dirname(snakefile)) self.linemaps[snakefile] = linemap exec(compile(code, snakefile, "exec"), self.globals) if not overwrite_first_rule: self.first_rule = first_rule self.included_stack.pop() def onstart(self, func): """Register onstart function.""" self._onstart = func def onsuccess(self, func): """Register onsuccess function.""" self._onsuccess = func def onerror(self, func): """Register onerror function.""" self._onerror = func def global_wildcard_constraints(self, **content): """Register global wildcard constraints.""" self._wildcard_constraints.update(content) # update all rules so far for rule in self.rules: rule.update_wildcard_constraints() def workdir(self, workdir): """Register workdir.""" if self.overwrite_workdir is None: os.makedirs(workdir, exist_ok=True) self._workdir = workdir os.chdir(workdir) def configfile(self, fp): """ Update the global config with data from the given file. """ global config self.configfiles.append(fp) c = snakemake.io.load_configfile(fp) update_config(config, c) update_config(config, self.overwrite_config) def report(self, path): """ Define a global report description in .rst format.""" self.report_text = os.path.join(self.current_basedir, path) @property def config(self): global config return config def ruleorder(self, *rulenames): self._ruleorder.add(*rulenames) def subworkflow(self, name, snakefile=None, workdir=None, configfile=None): # Take absolute path of config file, because it is relative to current # workdir, which could be changed for the subworkflow. if configfile: configfile = os.path.abspath(configfile) sw = Subworkflow(self, name, snakefile, workdir, configfile) self._subworkflows[name] = sw self.globals[name] = sw.target def localrules(self, *rulenames): self._localrules.update(rulenames) def rule(self, name=None, lineno=None, snakefile=None, checkpoint=False): name = self.add_rule(name, lineno, snakefile, checkpoint) rule = self.get_rule(name) rule.is_checkpoint = checkpoint def decorate(ruleinfo): if ruleinfo.wildcard_constraints: rule.set_wildcard_constraints( *ruleinfo.wildcard_constraints[0], **ruleinfo.wildcard_constraints[1] ) if ruleinfo.input: rule.set_input(*ruleinfo.input[0], **ruleinfo.input[1]) if ruleinfo.output: rule.set_output(*ruleinfo.output[0], **ruleinfo.output[1]) if ruleinfo.params: rule.set_params(*ruleinfo.params[0], **ruleinfo.params[1]) # handle default resources if self.default_resources is not None: rule.resources = copy.deepcopy(self.default_resources.parsed) if ruleinfo.threads is not None: if ( not isinstance(ruleinfo.threads, int) and not isinstance(ruleinfo.threads, float) and not callable(ruleinfo.threads) ): raise RuleException( "Threads value has to be an integer, float, or a callable.", rule=rule, ) if name in self.overwrite_threads: rule.resources["_cores"] = self.overwrite_threads[name] else: rule.resources["_cores"] = int(ruleinfo.threads) if ruleinfo.shadow_depth: if ruleinfo.shadow_depth not in (True, "shallow", "full", "minimal"): raise RuleException( "Shadow must either be 'minimal', 'shallow', 'full', " "or True (equivalent to 'full')", rule=rule, ) if ruleinfo.shadow_depth is True: rule.shadow_depth = "full" logger.warning( "Shadow is set to True in rule {} (equivalent to 'full'). It's encouraged to use the more explicit options 'minimal|shallow|full' instead.".format( rule ) ) else: rule.shadow_depth = ruleinfo.shadow_depth if ruleinfo.resources: args, resources = ruleinfo.resources if args: raise RuleException("Resources have to be named.") if not all( map(lambda r: isinstance(r, int) or callable(r), resources.values()) ): raise RuleException( "Resources values have to be integers or callables", rule=rule ) rule.resources.update(resources) if ruleinfo.priority: if not isinstance(ruleinfo.priority, int) and not isinstance( ruleinfo.priority, float ): raise RuleException( "Priority values have to be numeric.", rule=rule ) rule.priority = ruleinfo.priority if ruleinfo.version: rule.version = ruleinfo.version if ruleinfo.log: rule.set_log(*ruleinfo.log[0], **ruleinfo.log[1]) if ruleinfo.message: rule.message = ruleinfo.message if ruleinfo.benchmark: rule.benchmark = ruleinfo.benchmark if not self.run_local and ruleinfo.group is not None: rule.group = ruleinfo.group if ruleinfo.wrapper: if self.use_conda: rule.conda_env = snakemake.wrapper.get_conda_env( ruleinfo.wrapper, prefix=self.wrapper_prefix ) # TODO retrieve suitable singularity image if self.use_env_modules and ruleinfo.env_modules: # If using environment modules and they are defined for the rule, # ignore conda and singularity directive below. # The reason is that this is likely intended in order to use # a software stack specifically compiled for a particular # HPC cluster. invalid_rule = not ( ruleinfo.script or ruleinfo.wrapper or ruleinfo.shellcmd or ruleinfo.notebook ) if invalid_rule: raise RuleException( "Modules directive is only allowed with " "shell, script, notebook, or wrapper directives (not with run)", rule=rule, ) from snakemake.deployment.env_modules import EnvModules rule.env_modules = EnvModules(*ruleinfo.env_modules) else: if ruleinfo.conda_env and self.use_conda: if not ( ruleinfo.script or ruleinfo.wrapper or ruleinfo.shellcmd or ruleinfo.notebook ): raise RuleException( "Conda environments are only allowed " "with shell, script, notebook, or wrapper directives " "(not with run).", rule=rule, ) if not ( urllib.parse.urlparse(ruleinfo.conda_env).scheme or os.path.isabs(ruleinfo.conda_env) ): ruleinfo.conda_env = os.path.join( self.current_basedir, ruleinfo.conda_env ) rule.conda_env = ruleinfo.conda_env if self.use_singularity: invalid_rule = not ( ruleinfo.script or ruleinfo.wrapper or ruleinfo.shellcmd or ruleinfo.notebook ) if ruleinfo.singularity_img: if invalid_rule: raise RuleException( "Singularity directive is only allowed " "with shell, script, notebook or wrapper directives " "(not with run).", rule=rule, ) rule.singularity_img = ruleinfo.singularity_img elif self.global_singularity_img: if not invalid_rule: # skip rules with run directive rule.singularity_img = self.global_singularity_img rule.norun = ruleinfo.norun rule.docstring = ruleinfo.docstring rule.run_func = ruleinfo.func rule.shellcmd = ruleinfo.shellcmd rule.script = ruleinfo.script rule.notebook = ruleinfo.notebook rule.wrapper = ruleinfo.wrapper rule.cwl = ruleinfo.cwl rule.restart_times = self.restart_times rule.basedir = self.current_basedir ruleinfo.func.__name__ = "__{}".format(rule.name) self.globals[ruleinfo.func.__name__] = ruleinfo.func setattr(rules, rule.name, RuleProxy(rule)) if checkpoint: checkpoints.register(rule) return ruleinfo.func return decorate def docstring(self, string): def decorate(ruleinfo): ruleinfo.docstring = string return ruleinfo return decorate def input(self, *paths, **kwpaths): def decorate(ruleinfo): ruleinfo.input = (paths, kwpaths) return ruleinfo return decorate def output(self, *paths, **kwpaths): def decorate(ruleinfo): ruleinfo.output = (paths, kwpaths) return ruleinfo return decorate def params(self, *params, **kwparams): def decorate(ruleinfo): ruleinfo.params = (params, kwparams) return ruleinfo return decorate def wildcard_constraints(self, *wildcard_constraints, **kwwildcard_constraints): def decorate(ruleinfo): ruleinfo.wildcard_constraints = ( wildcard_constraints, kwwildcard_constraints, ) return ruleinfo return decorate def message(self, message): def decorate(ruleinfo): ruleinfo.message = message return ruleinfo return decorate def benchmark(self, benchmark): def decorate(ruleinfo): ruleinfo.benchmark = benchmark return ruleinfo return decorate def conda(self, conda_env): def decorate(ruleinfo): ruleinfo.conda_env = conda_env return ruleinfo return decorate def singularity(self, singularity_img): def decorate(ruleinfo): ruleinfo.singularity_img = singularity_img return ruleinfo return decorate def envmodules(self, *env_modules): def decorate(ruleinfo): ruleinfo.env_modules = env_modules return ruleinfo return decorate def global_singularity(self, singularity_img): self.global_singularity_img = singularity_img def threads(self, threads): def decorate(ruleinfo): ruleinfo.threads = threads return ruleinfo return decorate def shadow(self, shadow_depth): def decorate(ruleinfo): ruleinfo.shadow_depth = shadow_depth return ruleinfo return decorate def resources(self, *args, **resources): def decorate(ruleinfo): ruleinfo.resources = (args, resources) return ruleinfo return decorate def priority(self, priority): def decorate(ruleinfo): ruleinfo.priority = priority return ruleinfo return decorate def version(self, version): def decorate(ruleinfo): ruleinfo.version = version return ruleinfo return decorate def group(self, group): def decorate(ruleinfo): ruleinfo.group = group return ruleinfo return decorate def log(self, *logs, **kwlogs): def decorate(ruleinfo): ruleinfo.log = (logs, kwlogs) return ruleinfo return decorate def shellcmd(self, cmd): def decorate(ruleinfo): ruleinfo.shellcmd = cmd return ruleinfo return decorate def script(self, script): def decorate(ruleinfo): ruleinfo.script = script return ruleinfo return decorate def notebook(self, notebook): def decorate(ruleinfo): ruleinfo.notebook = notebook return ruleinfo return decorate def wrapper(self, wrapper): def decorate(ruleinfo): ruleinfo.wrapper = wrapper return ruleinfo return decorate def cwl(self, cwl): def decorate(ruleinfo): ruleinfo.cwl = cwl return ruleinfo return decorate def norun(self): def decorate(ruleinfo): ruleinfo.norun = True return ruleinfo return decorate def run(self, func): return RuleInfo(func) @staticmethod def _empty_decorator(f): return f class RuleInfo: def __init__(self, func): self.func = func self.shellcmd = None self.norun = False self.input = None self.output = None self.params = None self.message = None self.benchmark = None self.conda_env = None self.singularity_img = None self.env_modules = None self.wildcard_constraints = None self.threads = None self.shadow_depth = None self.resources = None self.priority = None self.version = None self.log = None self.docstring = None self.group = None self.script = None self.notebook = None self.wrapper = None self.cwl = None class Subworkflow: def __init__(self, workflow, name, snakefile, workdir, configfile): self.workflow = workflow self.name = name self._snakefile = snakefile self._workdir = workdir self.configfile = configfile @property def snakefile(self): if self._snakefile is None: return os.path.abspath(os.path.join(self.workdir, "Snakefile")) if not os.path.isabs(self._snakefile): return os.path.abspath(os.path.join(self.workflow.basedir, self._snakefile)) return self._snakefile @property def workdir(self): workdir = "." if self._workdir is None else self._workdir if not os.path.isabs(workdir): return os.path.abspath(os.path.join(self.workflow.basedir, workdir)) return workdir def target(self, paths): if not_iterable(paths): path = paths path = path if os.path.isabs(path) else os.path.join(self.workdir, path) return flag(path, "subworkflow", self) return [self.target(path) for path in paths] def targets(self, dag): def relpath(f): if f.startswith(self.workdir): return os.path.relpath(f, start=self.workdir) # do not adjust absolute targets outside of workdir return f return [ relpath(f) for job in dag.jobs for f in job.subworkflow_input if job.subworkflow_input[f] is self ] class Rules: """ A namespace for rules so that they can be accessed via dot notation. """ pass def srcdir(path): """Return the absolute path, relative to the source directory of the current Snakefile.""" if not workflow.included_stack: return None return os.path.join(os.path.dirname(workflow.included_stack[-1]), path) snakemake-5.10.0/snakemake/wrapper.py000066400000000000000000000063621361131222100175240ustar00rootroot00000000000000__author__ = "Johannes Köster" __copyright__ = "Copyright 2016-2019, Johannes Köster" __email__ = "koester@jimmy.harvard.edu" __license__ = "MIT" import os import posixpath from urllib.error import URLError from urllib.request import urlopen from snakemake.exceptions import WorkflowError from snakemake.script import script def is_script(path): return ( path.endswith("wrapper.py") or path.endswith("wrapper.R") or path.endswith("wrapper.jl") ) def get_path(path, prefix=None): if not ( path.startswith("http") or path.startswith("file:") or path.startswith("git+file") ): if prefix is None: prefix = "https://github.com/snakemake/snakemake-wrappers/raw/" elif prefix.startswith("git+file"): parts = path.split("/") path = "/" + "/".join(parts[1:]) + "@" + parts[0] path = prefix + path return path def is_local(path): return path.startswith("file:") def is_git_path(path): return path.startswith("git+file:") def find_extension(path, extensions=[".py", ".R", ".Rmd", ".jl"]): for ext in extensions: if path.endswith("wrapper{}".format(ext)): return path for ext in extensions: script = "/wrapper{}".format(ext) if is_local(path): if path.startswith("file://"): p = path[7:] elif path.startswith("file:"): p = path[5:] if os.path.exists(p + script): return path + script else: try: urlopen(path + script) return path + script except URLError: continue if is_git_path(path): path, version = path.split("@") return os.path.join(path, "wrapper.py") + "@" + version else: return path + "/wrapper.py" # default case def get_script(path, prefix=None): path = get_path(path, prefix=prefix) return find_extension(path) def get_conda_env(path, prefix=None): path = get_path(path, prefix=prefix) if is_script(path): # URLs and posixpaths share the same separator. Hence use posixpath here. path = posixpath.dirname(path) if is_git_path(path): path, version = path.split("@") return os.path.join(path, "environment.yaml") + "@" + version return path + "/environment.yaml" def wrapper( path, input, output, params, wildcards, threads, resources, log, config, rulename, conda_env, singularity_img, singularity_args, env_modules, bench_record, prefix, jobid, bench_iteration, cleanup_scripts, shadow_dir, ): """ Load a wrapper from https://github.com/snakemake/snakemake-wrappers under the given path + wrapper.(py|R|Rmd) and execute it. """ path = get_script(path, prefix=prefix) script( path, "", input, output, params, wildcards, threads, resources, log, config, rulename, conda_env, singularity_img, singularity_args, env_modules, bench_record, jobid, bench_iteration, cleanup_scripts, shadow_dir, ) snakemake-5.10.0/test-environment.yml000066400000000000000000000014261361131222100175730ustar00rootroot00000000000000channels: - conda-forge - bioconda dependencies: - python >=3.5 - datrie - boto3 - moto - httpretty - wrapt - pyyaml - pytest - pytest-cov - ftputil - pysftp - requests - dropbox - numpy - appdirs - pytools - docutils - pygments - pandoc <2.0 # pandoc has changed the CLI API so that it is no longer compatible with the version of r-markdown below - xorg-libxrender - xorg-libxext - xorg-libxau - xorg-libxdmcp - xorg-libsm - psutil - google-cloud-storage - azure-storage - azure-storage-common - ratelimiter - configargparse - appdirs - python-irodsclient - cwltool - jsonschema - pandas - networkx - pygraphviz - python-kubernetes - gitpython - tibanna - environment-modules - nbformat - toposort snakemake-5.10.0/tests/000077500000000000000000000000001361131222100146665ustar00rootroot00000000000000snakemake-5.10.0/tests/__init__.py000066400000000000000000000000001361131222100167650ustar00rootroot00000000000000snakemake-5.10.0/tests/knapsack/000077500000000000000000000000001361131222100164615ustar00rootroot00000000000000snakemake-5.10.0/tests/knapsack/1.txt000066400000000000000000000000001361131222100173500ustar00rootroot00000000000000snakemake-5.10.0/tests/knapsack/2.txt000066400000000000000000000000001361131222100173510ustar00rootroot00000000000000snakemake-5.10.0/tests/knapsack/3.txt000066400000000000000000000000001361131222100173520ustar00rootroot00000000000000snakemake-5.10.0/tests/knapsack/Snakefile000066400000000000000000000007431361131222100203110ustar00rootroot00000000000000# kate: syntax python; DATASETS = '1 2 3'.split() rule mapmature_all: input: '{ds}.bam'.format(ds=ds) for ds in DATASETS rule gzip: output: '{file}.gz' input: '{file}' shell: 'gzip < {input} > {output}' rule cutadapt: output: fastq=temp('{ds}.fastq') input: '{ds}.txt' shell: 'echo hello > {output.fastq}' rule bwa_mature: output: bam='{ds}.bam' input: reads='{ds}.fastq.gz' threads: 4 shell: 'echo starting with {threads} threads; sleep 10; touch {output.bam}' snakemake-5.10.0/tests/profile/000077500000000000000000000000001361131222100163265ustar00rootroot00000000000000snakemake-5.10.0/tests/profile/Snakefile000066400000000000000000000005461361131222100201570ustar00rootroot00000000000000 rule all: input: expand("{name}.d", name=range(1000)) rule: output: "{name}.a" shell: "touch {output}" rule: input: "{name}.a" output: "{name}.b" shell: "touch {output}" rule: input: "{name}.b" output: "{name}.c" shell: "touch {output}" rule: input: "{name}.c" output: "{name}.d" shell: "touch {output}" snakemake-5.10.0/tests/test (with parenthese's)/000077500000000000000000000000001361131222100212735ustar00rootroot00000000000000snakemake-5.10.0/tests/test (with parenthese's)/Snakefile000066400000000000000000000003321361131222100231150ustar00rootroot00000000000000 rule: input: "test.in" output: "test.out" run: test = shell("echo 42;", read=True) assert int(test) == 42 with open(output[0], "w") as f: for l in shell("cat {input}", iterable=True): print(l, file=f) snakemake-5.10.0/tests/test (with parenthese's)/expected-results/000077500000000000000000000000001361131222100245735ustar00rootroot00000000000000snakemake-5.10.0/tests/test (with parenthese's)/expected-results/test.out000066400000000000000000000000101361131222100262720ustar00rootroot00000000000000foo bar snakemake-5.10.0/tests/test (with parenthese's)/test.in000066400000000000000000000000101361131222100225710ustar00rootroot00000000000000foo bar snakemake-5.10.0/tests/test01/000077500000000000000000000000001361131222100160065ustar00rootroot00000000000000snakemake-5.10.0/tests/test01/Snakefile000066400000000000000000000023501361131222100176320ustar00rootroot00000000000000from snakemake.utils import min_version from snakemake import __version__ print(__version__, file=sys.stderr) shell.prefix("source ~/.bashrc; ") #min_version("2.1") TEST = "abc" onstart: print("Workflow starting") print("Log:") print(log) onsuccess: print("Workflow finished") print("Log:") print(log) onerror: print("Workflow failed") print("Log:") print(log) ruleorder: rule2 > rule4 def testin(wildcards): return "test.in" def version(): return "3.3" rule rule1: # This rule creates an intermediate file. input: 'test.inter' output: 'dir/test.out' log: a='log/logfile.log' version: version() threads: 3 shell: 'if [ {threads} -ne 3 ]; then echo "This test has to be run with -j3 in order to succeed!"; exit 1; fi; ' \ 'echo {TEST}; echo {version}; cp {input[0]} {output[0]}; ' # append a comment 'echo test > {log.a}' rule rule2: input: testin output: 'test.inter' message: 'Copying {input[0]} to {output[0]}' shell: ''' cp {input[0]} {output[0]} ''' rule rule4: input: "test.in" output: "test.inter" shell: "cp {input} {output}" # this should be ignored since test.in is present rule rule3: input: "dir/{a}.out" output: "{a}.in" shell: "cp {input} {output}" snakemake-5.10.0/tests/test01/expected-results/000077500000000000000000000000001361131222100213065ustar00rootroot00000000000000snakemake-5.10.0/tests/test01/expected-results/dir/000077500000000000000000000000001361131222100220645ustar00rootroot00000000000000snakemake-5.10.0/tests/test01/expected-results/dir/test.out000066400000000000000000000000101361131222100235630ustar00rootroot00000000000000testz0r snakemake-5.10.0/tests/test01/expected-results/test.inter000066400000000000000000000000101361131222100233170ustar00rootroot00000000000000testz0r snakemake-5.10.0/tests/test01/test.in000066400000000000000000000000101361131222100173040ustar00rootroot00000000000000testz0r snakemake-5.10.0/tests/test02/000077500000000000000000000000001361131222100160075ustar00rootroot00000000000000snakemake-5.10.0/tests/test02/Snakefile000066400000000000000000000005471361131222100176410ustar00rootroot00000000000000rule all: input: 'test.out' rule rule1: input: '{name}.in' output: '{name}.inter' #message: 'Copying {input[0]} to {output[0]}' log: "logs/{name}.log" shell: 'echo test > {log}; cp {input[0]} {output[0]}' rule rule2: input: '{name}.inter' output: '{name}.out' #message: 'Copying {input[0]} to {output[0]}' shell: 'cp {input[0]} {output[0]}' snakemake-5.10.0/tests/test02/expected-results/000077500000000000000000000000001361131222100213075ustar00rootroot00000000000000snakemake-5.10.0/tests/test02/expected-results/test.out000066400000000000000000000000101361131222100230060ustar00rootroot00000000000000testz0r snakemake-5.10.0/tests/test02/test.in000066400000000000000000000000101361131222100173050ustar00rootroot00000000000000testz0r snakemake-5.10.0/tests/test03/000077500000000000000000000000001361131222100160105ustar00rootroot00000000000000snakemake-5.10.0/tests/test03/Snakefile000066400000000000000000000002121361131222100176270ustar00rootroot00000000000000rule rule1: input: '{name}.in' output: '{name}.out' message: 'Copying {input[0]} to {output[0]}' shell: 'cp {input[0]} {output[0]}' snakemake-5.10.0/tests/test03/expected-results/000077500000000000000000000000001361131222100213105ustar00rootroot00000000000000snakemake-5.10.0/tests/test03/expected-results/test.out000066400000000000000000000000101361131222100230070ustar00rootroot00000000000000testz0r snakemake-5.10.0/tests/test03/params000066400000000000000000000000111361131222100172060ustar00rootroot00000000000000test.out snakemake-5.10.0/tests/test03/test.in000066400000000000000000000000101361131222100173060ustar00rootroot00000000000000testz0r snakemake-5.10.0/tests/test04/000077500000000000000000000000001361131222100160115ustar00rootroot00000000000000snakemake-5.10.0/tests/test04/Snakefile000066400000000000000000000006701361131222100176400ustar00rootroot00000000000000rule rule1: input: '{name}.bogus.in' output: '{name}.out' message: 'Writing junk to {output[0]}' shell: 'echo "junk" > {output[0]}; cat {input}' rule rule2: input: '{name}.in' output: '{name}.out' message: 'Copying {input[0]} to {output[0]}' shell: 'cp {input[0]} {output[0]}' rule rule3: input: '{name}.more.bogus.in' output: '{name}.out' message: 'Writing junk to {output[0]}' shell: 'echo "junk" > {output[0]}; cat{input}' snakemake-5.10.0/tests/test04/expected-results/000077500000000000000000000000001361131222100213115ustar00rootroot00000000000000snakemake-5.10.0/tests/test04/expected-results/test.out000066400000000000000000000000101361131222100230100ustar00rootroot00000000000000testz0r snakemake-5.10.0/tests/test04/params000066400000000000000000000000111361131222100172070ustar00rootroot00000000000000test.out snakemake-5.10.0/tests/test04/test.in000066400000000000000000000000101361131222100173070ustar00rootroot00000000000000testz0r snakemake-5.10.0/tests/test05/000077500000000000000000000000001361131222100160125ustar00rootroot00000000000000snakemake-5.10.0/tests/test05/Snakefile000066400000000000000000000014621361131222100176410ustar00rootroot00000000000000from snakemake import shell chromosomes = [1,2,3] #shell('rm test.*.inter 2> /dev/null | true') rule all: input: 'test.predictions' rule compute1: input: '{name}.in' output: inter=expand('{{name}}.{chr}.inter', chr=chromosomes) resources: gpu=1 run: assert len(output.inter) > 0 print(output.inter) for out in output: shell('(cat {input[0]} && echo "Part {out}") > {out}') rule compute2: input: '{name}.{chromosome}.inter', 'other.txt' output: '{name}.{chromosome}.inter2' threads: 2 resources: io=1 shell: 'cp {input[0]} {output[0]}' rule gather: input: ['{name}.%s.inter2'%c for c in chromosomes] output: '{name}.predictions' run: shell('cat {} > {}'.format(' '.join(input), output[0])) rule other: output: 'other.txt' priority: 50 resources: gpu=1 shell: 'touch other.txt' snakemake-5.10.0/tests/test05/expected-results/000077500000000000000000000000001361131222100213125ustar00rootroot00000000000000snakemake-5.10.0/tests/test05/expected-results/test.1.inter000066400000000000000000000000321361131222100234660ustar00rootroot00000000000000testz0r Part test.1.inter snakemake-5.10.0/tests/test05/expected-results/test.1.inter2000066400000000000000000000000321361131222100235500ustar00rootroot00000000000000testz0r Part test.1.inter snakemake-5.10.0/tests/test05/expected-results/test.2.inter000066400000000000000000000000321361131222100234670ustar00rootroot00000000000000testz0r Part test.2.inter snakemake-5.10.0/tests/test05/expected-results/test.2.inter2000066400000000000000000000000321361131222100235510ustar00rootroot00000000000000testz0r Part test.2.inter snakemake-5.10.0/tests/test05/expected-results/test.3.inter000066400000000000000000000000321361131222100234700ustar00rootroot00000000000000testz0r Part test.3.inter snakemake-5.10.0/tests/test05/expected-results/test.3.inter2000066400000000000000000000000321361131222100235520ustar00rootroot00000000000000testz0r Part test.3.inter snakemake-5.10.0/tests/test05/expected-results/test.predictions000066400000000000000000000001161361131222100245340ustar00rootroot00000000000000testz0r Part test.1.inter testz0r Part test.2.inter testz0r Part test.3.inter snakemake-5.10.0/tests/test05/test.in000066400000000000000000000000101361131222100173100ustar00rootroot00000000000000testz0r snakemake-5.10.0/tests/test06/000077500000000000000000000000001361131222100160135ustar00rootroot00000000000000snakemake-5.10.0/tests/test06/Snakefile000066400000000000000000000003061361131222100176360ustar00rootroot00000000000000rule all: input: 'test.bla.out' rule wildcards: input: 'test.in' output: 'test.{xyz}.out' message: 'Creating file {output[0]}, xyz={wildcards.xyz}' shell: 'echo {wildcards.xyz} > {output[0]}' snakemake-5.10.0/tests/test06/expected-results/000077500000000000000000000000001361131222100213135ustar00rootroot00000000000000snakemake-5.10.0/tests/test06/expected-results/test.bla.out000066400000000000000000000000041361131222100235520ustar00rootroot00000000000000bla snakemake-5.10.0/tests/test06/test.in000066400000000000000000000000101361131222100173110ustar00rootroot00000000000000testz0r snakemake-5.10.0/tests/test07/000077500000000000000000000000001361131222100160145ustar00rootroot00000000000000snakemake-5.10.0/tests/test07/Snakefile000066400000000000000000000002501361131222100176350ustar00rootroot00000000000000 rule rule1: input: 'test.in' output: 'test.out' shell: 'cp {input} {output}' rule rule2: input: 'test.in' output: 'test2.out' shell: 'cp {input} {output}' snakemake-5.10.0/tests/test07/expected-results/000077500000000000000000000000001361131222100213145ustar00rootroot00000000000000snakemake-5.10.0/tests/test07/expected-results/test.out000066400000000000000000000000101361131222100230130ustar00rootroot00000000000000testz0r snakemake-5.10.0/tests/test07/expected-results/test2.out000066400000000000000000000000101361131222100230750ustar00rootroot00000000000000testz0r snakemake-5.10.0/tests/test07/test.in000066400000000000000000000000101361131222100173120ustar00rootroot00000000000000testz0r snakemake-5.10.0/tests/test08/000077500000000000000000000000001361131222100160155ustar00rootroot00000000000000snakemake-5.10.0/tests/test08/Snakefile000066400000000000000000000002641361131222100176430ustar00rootroot00000000000000rule rule1: input: '{file}.in' output: '{file}.inter' shell: 'cp {input} {output}' rule rule2: input: '{file}.inter' output: '{file}.out' shell: 'cp {input} {output}' snakemake-5.10.0/tests/test08/expected-results/000077500000000000000000000000001361131222100213155ustar00rootroot00000000000000snakemake-5.10.0/tests/test08/expected-results/test.out000066400000000000000000000000101361131222100230140ustar00rootroot00000000000000testz0r snakemake-5.10.0/tests/test08/expected-results/test2.out000066400000000000000000000000041361131222100231010ustar00rootroot00000000000000Hoi snakemake-5.10.0/tests/test08/test.in000066400000000000000000000000101361131222100173130ustar00rootroot00000000000000testz0r snakemake-5.10.0/tests/test08/test2.in000066400000000000000000000000041361131222100174000ustar00rootroot00000000000000Hoi snakemake-5.10.0/tests/test09/000077500000000000000000000000001361131222100160165ustar00rootroot00000000000000snakemake-5.10.0/tests/test09/Snakefile000066400000000000000000000005541361131222100176460ustar00rootroot00000000000000from snakemake import shell def fail(input, output): shell("false && cp {input} {output}") def x(input, output): fail(input, output) rule rule2: input: 'test.inter' output: 'test.out' shell: 'cp {input} {output}' rule rule1: input: 'test.in' output: 'test.inter' log: "logs/test.log" shell: "touch {log} && false && cp {input} {output}" snakemake-5.10.0/tests/test09/expected-results/000077500000000000000000000000001361131222100213165ustar00rootroot00000000000000snakemake-5.10.0/tests/test09/expected-results/.gitignore000066400000000000000000000000001361131222100232740ustar00rootroot00000000000000snakemake-5.10.0/tests/test09/test.in000066400000000000000000000000101361131222100173140ustar00rootroot00000000000000testz0r snakemake-5.10.0/tests/test10/000077500000000000000000000000001361131222100160065ustar00rootroot00000000000000snakemake-5.10.0/tests/test10/Snakefile000066400000000000000000000001271361131222100176320ustar00rootroot00000000000000rule rule1: input: 'test.in' output: 'test.out' run: shell('cp {input} {output}') snakemake-5.10.0/tests/test10/expected-results/000077500000000000000000000000001361131222100213065ustar00rootroot00000000000000snakemake-5.10.0/tests/test10/expected-results/test.out000066400000000000000000000000101361131222100230050ustar00rootroot00000000000000testz0r snakemake-5.10.0/tests/test10/test.in000066400000000000000000000000101361131222100173040ustar00rootroot00000000000000testz0r snakemake-5.10.0/tests/test11/000077500000000000000000000000001361131222100160075ustar00rootroot00000000000000snakemake-5.10.0/tests/test11/Snakefile000066400000000000000000000001551361131222100176340ustar00rootroot00000000000000include: "import.snakefile" rule: input: 'test.inter' output: 'test.out' shell: 'cp {input} {output}' snakemake-5.10.0/tests/test11/expected-results/000077500000000000000000000000001361131222100213075ustar00rootroot00000000000000snakemake-5.10.0/tests/test11/expected-results/test.inter000066400000000000000000000000101361131222100233200ustar00rootroot00000000000000testz0r snakemake-5.10.0/tests/test11/expected-results/test.out000066400000000000000000000000101361131222100230060ustar00rootroot00000000000000testz0r snakemake-5.10.0/tests/test11/import.snakefile000066400000000000000000000001171361131222100212030ustar00rootroot00000000000000rule: input: 'test.in' output: 'test.inter' shell: 'cp {input} {output}' snakemake-5.10.0/tests/test11/test.in000066400000000000000000000000101361131222100173050ustar00rootroot00000000000000testz0r snakemake-5.10.0/tests/test12/000077500000000000000000000000001361131222100160105ustar00rootroot00000000000000snakemake-5.10.0/tests/test12/Snakefile000066400000000000000000000004341361131222100176350ustar00rootroot00000000000000 rule rule1: input: 'test.inter' output: 'test.out' #message: 'Copying {input[0]} to {output[0]}' shell: 'cp {input[0]} {output[0]}' rule rule2: input: 'test.in' output: temp('test.inter') #message: 'Copying {input[0]} to {output[0]}' shell: 'cp {input[0]} {output[0]}' snakemake-5.10.0/tests/test12/expected-results/000077500000000000000000000000001361131222100213105ustar00rootroot00000000000000snakemake-5.10.0/tests/test12/expected-results/test.out000066400000000000000000000000101361131222100230070ustar00rootroot00000000000000testz0r snakemake-5.10.0/tests/test12/test.in000066400000000000000000000000101361131222100173060ustar00rootroot00000000000000testz0r snakemake-5.10.0/tests/test13/000077500000000000000000000000001361131222100160115ustar00rootroot00000000000000snakemake-5.10.0/tests/test13/Snakefile000066400000000000000000000005411361131222100176350ustar00rootroot00000000000000 rule all: input: 'test.algo1-p7-improved.out' rule run_algo1: input: '{dataset}.in' output: '{dataset}.algo1-p{param,[0-9]+}.out' shell: 'echo "algo1 / {wildcards.param}" > {output}' rule postprocess: input: '{dataset}.{algorithm}.out' output: '{dataset}.{algorithm}-improved.out' shell: 'cp {input} {output} && (echo "IMPROVED" >> {output})' snakemake-5.10.0/tests/test13/expected-results/000077500000000000000000000000001361131222100213115ustar00rootroot00000000000000snakemake-5.10.0/tests/test13/expected-results/test.algo1-p7-improved.out000066400000000000000000000000231361131222100261650ustar00rootroot00000000000000algo1 / 7 IMPROVED snakemake-5.10.0/tests/test13/expected-results/test.algo1-p7.out000066400000000000000000000000121361131222100243400ustar00rootroot00000000000000algo1 / 7 snakemake-5.10.0/tests/test13/test.in000066400000000000000000000000101361131222100173070ustar00rootroot00000000000000testz0r snakemake-5.10.0/tests/test14/000077500000000000000000000000001361131222100160125ustar00rootroot00000000000000snakemake-5.10.0/tests/test14/Snakefile.nonstandard000066400000000000000000000011531361131222100221500ustar00rootroot00000000000000from snakemake import shell chromosomes = [1,2,3,4,5] localrules: all rule all: input: 'test.predictions', 'test.2.inter2' rule compute1: input: '{name}.in' output: ['{name}.%s.inter'%c for c in chromosomes] run: for out in output: shell('(cat {input[0]} && echo "Part {out}") > {out}') rule compute2: input: '{name}.{chromosome}.inter' output: '{name}.{chromosome}.inter2' params: test="a=b" shell: 'echo copy; cp {input[0]} {output[0]}' rule gather: input: ['{name}.%s.inter2'%c for c in chromosomes] output: '{name}.predictions' run: shell('cat {} > {}'.format(' '.join(input), output[0])) snakemake-5.10.0/tests/test14/expected-results/000077500000000000000000000000001361131222100213125ustar00rootroot00000000000000snakemake-5.10.0/tests/test14/expected-results/test.1.inter000066400000000000000000000000321361131222100234660ustar00rootroot00000000000000testz0r Part test.1.inter snakemake-5.10.0/tests/test14/expected-results/test.1.inter2000066400000000000000000000000321361131222100235500ustar00rootroot00000000000000testz0r Part test.1.inter snakemake-5.10.0/tests/test14/expected-results/test.2.inter000066400000000000000000000000321361131222100234670ustar00rootroot00000000000000testz0r Part test.2.inter snakemake-5.10.0/tests/test14/expected-results/test.2.inter2000066400000000000000000000000321361131222100235510ustar00rootroot00000000000000testz0r Part test.2.inter snakemake-5.10.0/tests/test14/expected-results/test.3.inter000066400000000000000000000000321361131222100234700ustar00rootroot00000000000000testz0r Part test.3.inter snakemake-5.10.0/tests/test14/expected-results/test.3.inter2000066400000000000000000000000321361131222100235520ustar00rootroot00000000000000testz0r Part test.3.inter snakemake-5.10.0/tests/test14/expected-results/test.predictions000066400000000000000000000002021361131222100245300ustar00rootroot00000000000000testz0r Part test.1.inter testz0r Part test.2.inter testz0r Part test.3.inter testz0r Part test.4.inter testz0r Part test.5.inter snakemake-5.10.0/tests/test14/qsub000077500000000000000000000002231361131222100167070ustar00rootroot00000000000000#!/bin/bash echo `date` >> qsub.log tail -n1 $1 >> qsub.log # simulate printing of job id by a random number echo $RANDOM cat $1 >> qsub.log sh $1 snakemake-5.10.0/tests/test14/qsub.py000077500000000000000000000004771361131222100173510ustar00rootroot00000000000000#!/usr/bin/env python3 import sys import os import random from snakemake.utils import read_job_properties jobscript = sys.argv[1] job_properties = read_job_properties(jobscript) with open("qsub.log", "a") as log: print(job_properties, file=log) print(random.randint(1, 100)) os.system("sh {}".format(jobscript)) snakemake-5.10.0/tests/test14/test.in000066400000000000000000000000101361131222100173100ustar00rootroot00000000000000testz0r snakemake-5.10.0/tests/test15/000077500000000000000000000000001361131222100160135ustar00rootroot00000000000000snakemake-5.10.0/tests/test15/Snakefile000066400000000000000000000002331361131222100176350ustar00rootroot00000000000000 rule a: input: test = lambda wildcards: "test2.in" if os.path.exists("test2.in") else "test.in" output: "test.out" shell: "cp {input.test} {output}" snakemake-5.10.0/tests/test15/expected-results/000077500000000000000000000000001361131222100213135ustar00rootroot00000000000000snakemake-5.10.0/tests/test15/expected-results/test.out000066400000000000000000000000101361131222100230120ustar00rootroot00000000000000testz0r snakemake-5.10.0/tests/test15/test.in000066400000000000000000000000101361131222100173110ustar00rootroot00000000000000testz0r snakemake-5.10.0/tests/testHighWorkload/000077500000000000000000000000001361131222100201505ustar00rootroot00000000000000snakemake-5.10.0/tests/testHighWorkload/Snakefile000066400000000000000000000012121361131222100217700ustar00rootroot00000000000000import os.path import sys instances = [os.path.basename(s[:len(s)-4]) for s in os.listdir('mfa') if s.endswith('.mfa')] rule all: input: ['fisher/%s.pairs.gz'%s for s in instances] + ['ph/%s.ph'%s for s in instances] rule extract_mismatch_counts: input: 'mfa/{instance}.mfa' output: 'fisher/{instance}.pairs.gz' message: 'Extracting number mismatches for each pair of sequences from {input}' shell: 'sleep 2; touch {output}' rule create_tree: input: 'mfa/{instance}.mfa' output: 'ph/{instance}.ph', 'ph/{instance}.ph.log' message: 'Running CLUSTALW to compute NJ tree from {input}' shell: "sleep 2; touch {output[0]}; touch {output[1]}" snakemake-5.10.0/tests/testHighWorkload/mfa/000077500000000000000000000000001361131222100207135ustar00rootroot00000000000000snakemake-5.10.0/tests/testHighWorkload/mfa/00.mfa000066400000000000000000000000001361131222100216050ustar00rootroot00000000000000snakemake-5.10.0/tests/testHighWorkload/mfa/01.mfa000066400000000000000000000000001361131222100216060ustar00rootroot00000000000000snakemake-5.10.0/tests/testHighWorkload/mfa/02.mfa000066400000000000000000000000001361131222100216070ustar00rootroot00000000000000snakemake-5.10.0/tests/testHighWorkload/mfa/03.mfa000066400000000000000000000000001361131222100216100ustar00rootroot00000000000000snakemake-5.10.0/tests/testHighWorkload/mfa/04.mfa000066400000000000000000000000001361131222100216110ustar00rootroot00000000000000snakemake-5.10.0/tests/testHighWorkload/mfa/05.mfa000066400000000000000000000000001361131222100216120ustar00rootroot00000000000000snakemake-5.10.0/tests/testHighWorkload/mfa/06.mfa000066400000000000000000000000001361131222100216130ustar00rootroot00000000000000snakemake-5.10.0/tests/testHighWorkload/mfa/07.mfa000066400000000000000000000000001361131222100216140ustar00rootroot00000000000000snakemake-5.10.0/tests/testHighWorkload/mfa/08.mfa000066400000000000000000000000001361131222100216150ustar00rootroot00000000000000snakemake-5.10.0/tests/testHighWorkload/mfa/09.mfa000066400000000000000000000000001361131222100216160ustar00rootroot00000000000000snakemake-5.10.0/tests/testHighWorkload/mfa/10.mfa000066400000000000000000000000001361131222100216060ustar00rootroot00000000000000snakemake-5.10.0/tests/test_ancient/000077500000000000000000000000001361131222100173465ustar00rootroot00000000000000snakemake-5.10.0/tests/test_ancient/Snakefile000066400000000000000000000022311361131222100211700ustar00rootroot00000000000000from snakemake.remote.HTTP import RemoteProvider as HTTPRemoteProvider HTTP = HTTPRemoteProvider() shell("touch C && sleep 1 && touch B && sleep 1 && touch A && touch D && \ mkdir -p github.com/snakemake/snakemake/raw/master/tests/test_remote_http/expected-results && \ touch github.com/snakemake/snakemake/raw/master/tests/test_remote_http/expected-results/landsat-data.txt && \ touch -t 200101010101 old_file") #Will not be executed even though A is newer rule a: input: ancient("A") output: "B" shell: "echo \"B recreated\" > {output}" #Will be executed because B is newer rule b: input: "B" output: "C" shell: "echo \"C recreated\" > {output}" #Will be executed because C was updated in rule b rule c: input: ancient("C") output: "D" shell: "echo \"D recreated\" > {output}" # This should not run even though output is older than input rule remote_ancient: input: ancient(HTTP.remote("github.com/snakemake/snakemake/raw/master/tests/test_remote_http/expected-results/landsat-data.txt")) output: "old_file" shell: "cp {input} {output}" snakemake-5.10.0/tests/test_ancient/expected-results/000077500000000000000000000000001361131222100226465ustar00rootroot00000000000000snakemake-5.10.0/tests/test_ancient/expected-results/A000066400000000000000000000000001361131222100227370ustar00rootroot00000000000000snakemake-5.10.0/tests/test_ancient/expected-results/B000066400000000000000000000000001361131222100227400ustar00rootroot00000000000000snakemake-5.10.0/tests/test_ancient/expected-results/C000066400000000000000000000000141361131222100227460ustar00rootroot00000000000000C recreated snakemake-5.10.0/tests/test_ancient/expected-results/D000066400000000000000000000000141361131222100227470ustar00rootroot00000000000000D recreated snakemake-5.10.0/tests/test_ancient/expected-results/old_file000066400000000000000000000000001361131222100243340ustar00rootroot00000000000000snakemake-5.10.0/tests/test_archive/000077500000000000000000000000001361131222100173465ustar00rootroot00000000000000snakemake-5.10.0/tests/test_archive/Snakefile000066400000000000000000000001561361131222100211740ustar00rootroot00000000000000rule a: output: "test.out" conda: "test-env.yaml" shell: "touch {output}" snakemake-5.10.0/tests/test_archive/expected-results/000077500000000000000000000000001361131222100226465ustar00rootroot00000000000000snakemake-5.10.0/tests/test_archive/expected-results/.gitignore000066400000000000000000000000001361131222100246240ustar00rootroot00000000000000snakemake-5.10.0/tests/test_archive/test-env.yaml000066400000000000000000000001051361131222100217730ustar00rootroot00000000000000channels: - bioconda - conda-forge dependencies: - bwa =0.7.17 snakemake-5.10.0/tests/test_bash/000077500000000000000000000000001361131222100166425ustar00rootroot00000000000000snakemake-5.10.0/tests/test_bash/Snakefile000066400000000000000000000001271361131222100204660ustar00rootroot00000000000000 rule a: output: "test.out" shell: "basename $BASH > {output}" snakemake-5.10.0/tests/test_bash/expected-results/000077500000000000000000000000001361131222100221425ustar00rootroot00000000000000snakemake-5.10.0/tests/test_bash/expected-results/test.out000066400000000000000000000000051361131222100236450ustar00rootroot00000000000000bash snakemake-5.10.0/tests/test_batch/000077500000000000000000000000001361131222100170065ustar00rootroot00000000000000snakemake-5.10.0/tests/test_batch/Snakefile000066400000000000000000000006371361131222100206400ustar00rootroot00000000000000SAMPLES = ["a", "b", "c"] rule all: input: "foo.txt", "bar.txt" rule aggregate: input: expand("{sample}.inter.txt", sample=SAMPLES) output: "foo.txt" shell: "touch {output}" rule feed: output: temp("{sample}.inter.txt") shell: "touch {output}" rule independent: output: "bar.txt" shell: "touch {output}" snakemake-5.10.0/tests/test_batch/expected-results/000077500000000000000000000000001361131222100223065ustar00rootroot00000000000000snakemake-5.10.0/tests/test_batch/expected-results/a.inter.txt000066400000000000000000000000001361131222100243750ustar00rootroot00000000000000snakemake-5.10.0/tests/test_batch/expected-results/bar.txt000066400000000000000000000000001361131222100236010ustar00rootroot00000000000000snakemake-5.10.0/tests/test_batch_final/000077500000000000000000000000001361131222100201575ustar00rootroot00000000000000snakemake-5.10.0/tests/test_batch_final/Snakefile000066400000000000000000000006371361131222100220110ustar00rootroot00000000000000SAMPLES = ["a", "b", "c"] rule all: input: "foo.txt", "bar.txt" rule aggregate: input: expand("{sample}.inter.txt", sample=SAMPLES) output: "foo.txt" shell: "touch {output}" rule feed: output: temp("{sample}.inter.txt") shell: "touch {output}" rule independent: output: "bar.txt" shell: "touch {output}" snakemake-5.10.0/tests/test_batch_final/expected-results/000077500000000000000000000000001361131222100234575ustar00rootroot00000000000000snakemake-5.10.0/tests/test_batch_final/expected-results/bar.txt000066400000000000000000000000001361131222100247520ustar00rootroot00000000000000snakemake-5.10.0/tests/test_batch_final/expected-results/foo.txt000066400000000000000000000000001361131222100247710ustar00rootroot00000000000000snakemake-5.10.0/tests/test_benchmark/000077500000000000000000000000001361131222100176575ustar00rootroot00000000000000snakemake-5.10.0/tests/test_benchmark/Snakefile000066400000000000000000000011771361131222100215110ustar00rootroot00000000000000import time rule all: input: "test.benchmark_shell.txt", "test.benchmark_script.txt", "test.benchmark_run.txt", "test.benchmark_run_shell.txt", rule bench_shell: benchmark: repeat("test.benchmark_shell.txt", 2) threads: 2 shell: "stress --cpu {threads} --timeout 10" rule bench_script: benchmark: "test.benchmark_script.txt" script: 'script.py' rule bench_run: benchmark: "test.benchmark_run.txt" run: time.sleep(1) rule bench_run_shell: benchmark: "test.benchmark_run_shell.txt" run: shell("sleep 1") snakemake-5.10.0/tests/test_benchmark/expected-results/000077500000000000000000000000001361131222100231575ustar00rootroot00000000000000snakemake-5.10.0/tests/test_benchmark/expected-results/test.benchmark_run.txt000066400000000000000000000000001361131222100275020ustar00rootroot00000000000000snakemake-5.10.0/tests/test_benchmark/expected-results/test.benchmark_run_shell.txt000066400000000000000000000000001361131222100306710ustar00rootroot00000000000000snakemake-5.10.0/tests/test_benchmark/expected-results/test.benchmark_script.txt000066400000000000000000000000001361131222100302020ustar00rootroot00000000000000snakemake-5.10.0/tests/test_benchmark/expected-results/test.benchmark_shell.txt000066400000000000000000000000001361131222100300050ustar00rootroot00000000000000snakemake-5.10.0/tests/test_benchmark/script.py000077500000000000000000000001451361131222100215400ustar00rootroot00000000000000#!/usr/bin/env python3 import sys import time print('Hello World!', file=sys.stderr) time.sleep(1) snakemake-5.10.0/tests/test_checkpoints/000077500000000000000000000000001361131222100202375ustar00rootroot00000000000000snakemake-5.10.0/tests/test_checkpoints/Snakefile000066400000000000000000000017451361131222100220720ustar00rootroot00000000000000 rule all: input: "aggregated/a.txt", "aggregated/b.txt" checkpoint somestep: input: "samples/{sample}.txt" output: "somestep/{sample}.txt" shell: # simulate some output vale "echo {wildcards.sample} > somestep/{wildcards.sample}.txt" rule intermediate: input: "somestep/{sample}.txt" output: "post/{sample}.txt" shell: "touch {output}" rule alt_intermediate: input: "somestep/{sample}.txt" output: "alt/{sample}.txt" shell: "touch {output}" def aggregate_input(wildcards): # decision based on content of output file with checkpoints.somestep.get(**wildcards).output[0].open() as f: if f.read().strip() == "a": return "post/{sample}.txt" else: return "alt/{sample}.txt" rule aggregate: input: aggregate_input output: "aggregated/{sample}.txt" shell: "touch {output}" snakemake-5.10.0/tests/test_checkpoints/expected-results/000077500000000000000000000000001361131222100235375ustar00rootroot00000000000000snakemake-5.10.0/tests/test_checkpoints/expected-results/aggregated/000077500000000000000000000000001361131222100256315ustar00rootroot00000000000000snakemake-5.10.0/tests/test_checkpoints/expected-results/aggregated/a.txt000066400000000000000000000000001361131222100266000ustar00rootroot00000000000000snakemake-5.10.0/tests/test_checkpoints/samples/000077500000000000000000000000001361131222100217035ustar00rootroot00000000000000snakemake-5.10.0/tests/test_checkpoints/samples/a.txt000066400000000000000000000000001361131222100226520ustar00rootroot00000000000000snakemake-5.10.0/tests/test_checkpoints/samples/b.txt000066400000000000000000000000001361131222100226530ustar00rootroot00000000000000snakemake-5.10.0/tests/test_checkpoints_dir/000077500000000000000000000000001361131222100210755ustar00rootroot00000000000000snakemake-5.10.0/tests/test_checkpoints_dir/Snakefile000066400000000000000000000015421361131222100227230ustar00rootroot00000000000000 rule all: input: "aggregated/a.txt", "aggregated/b.txt" checkpoint clustering: input: "samples/{sample}.txt" output: clusters=directory("clustering/{sample}") shell: "mkdir clustering/{wildcards.sample}; " "for i in 1 2 3; do echo $i > clustering/{wildcards.sample}/$i.txt; done" rule intermediate: input: "clustering/{sample}/{i}.txt" output: "post/{sample}/{i}.txt" shell: "cp {input} {output}" def aggregate_input(wildcards): return expand("post/{sample}/{i}.txt", sample=wildcards.sample, i=glob_wildcards(os.path.join(checkpoints.clustering.get(**wildcards).output[0], "{i}.txt")).i) rule aggregate: input: aggregate_input output: "aggregated/{sample}.txt" shell: "cat {input} > {output}" snakemake-5.10.0/tests/test_checkpoints_dir/expected-results/000077500000000000000000000000001361131222100243755ustar00rootroot00000000000000snakemake-5.10.0/tests/test_checkpoints_dir/expected-results/aggregated/000077500000000000000000000000001361131222100264675ustar00rootroot00000000000000snakemake-5.10.0/tests/test_checkpoints_dir/expected-results/aggregated/a.txt000066400000000000000000000000061361131222100274440ustar00rootroot000000000000002 1 3 snakemake-5.10.0/tests/test_checkpoints_dir/expected-results/aggregated/b.txt000066400000000000000000000000061361131222100274450ustar00rootroot000000000000002 1 3 snakemake-5.10.0/tests/test_checkpoints_dir/samples/000077500000000000000000000000001361131222100225415ustar00rootroot00000000000000snakemake-5.10.0/tests/test_checkpoints_dir/samples/a.txt000066400000000000000000000000001361131222100235100ustar00rootroot00000000000000snakemake-5.10.0/tests/test_checkpoints_dir/samples/b.txt000066400000000000000000000000001361131222100235110ustar00rootroot00000000000000snakemake-5.10.0/tests/test_conda/000077500000000000000000000000001361131222100170115ustar00rootroot00000000000000snakemake-5.10.0/tests/test_conda/Snakefile000066400000000000000000000005311361131222100206340ustar00rootroot00000000000000rule all: input: expand("test{i}.out2", i=range(3)) rule a: output: "test{i}.out" conda: "test-env.yaml" shell: "bwa 2> {output} || true" rule b: input: "test{i}.out" output: "test{i}.out2" conda: "test-env.yaml" shell: "bwa 2> {output} || true" snakemake-5.10.0/tests/test_conda/expected-results/000077500000000000000000000000001361131222100223115ustar00rootroot00000000000000snakemake-5.10.0/tests/test_conda/expected-results/test0.out000066400000000000000000000022341361131222100241020ustar00rootroot00000000000000 Program: bwa (alignment via Burrows-Wheeler transformation) Version: 0.7.17-r1188 Contact: Heng Li Usage: bwa [options] Command: index index sequences in the FASTA format mem BWA-MEM algorithm fastmap identify super-maximal exact matches pemerge merge overlapping paired ends (EXPERIMENTAL) aln gapped/ungapped alignment samse generate alignment (single ended) sampe generate alignment (paired ended) bwasw BWA-SW for long queries shm manage indices in shared memory fa2pac convert FASTA to PAC format pac2bwt generate BWT from PAC pac2bwtgen alternative algorithm for generating BWT bwtupdate update .bwt to the new format bwt2sa generate SA from BWT and Occ Note: To use BWA, you need to first index the genome with `bwa index'. There are three alignment algorithms in BWA: `mem', `bwasw', and `aln/samse/sampe'. If you are not sure which to use, try `bwa mem' first. Please `man ./bwa.1' for the manual. snakemake-5.10.0/tests/test_conda/expected-results/test1.out000066400000000000000000000022341361131222100241030ustar00rootroot00000000000000 Program: bwa (alignment via Burrows-Wheeler transformation) Version: 0.7.17-r1188 Contact: Heng Li Usage: bwa [options] Command: index index sequences in the FASTA format mem BWA-MEM algorithm fastmap identify super-maximal exact matches pemerge merge overlapping paired ends (EXPERIMENTAL) aln gapped/ungapped alignment samse generate alignment (single ended) sampe generate alignment (paired ended) bwasw BWA-SW for long queries shm manage indices in shared memory fa2pac convert FASTA to PAC format pac2bwt generate BWT from PAC pac2bwtgen alternative algorithm for generating BWT bwtupdate update .bwt to the new format bwt2sa generate SA from BWT and Occ Note: To use BWA, you need to first index the genome with `bwa index'. There are three alignment algorithms in BWA: `mem', `bwasw', and `aln/samse/sampe'. If you are not sure which to use, try `bwa mem' first. Please `man ./bwa.1' for the manual. snakemake-5.10.0/tests/test_conda/expected-results/test2.out000066400000000000000000000022341361131222100241040ustar00rootroot00000000000000 Program: bwa (alignment via Burrows-Wheeler transformation) Version: 0.7.17-r1188 Contact: Heng Li Usage: bwa [options] Command: index index sequences in the FASTA format mem BWA-MEM algorithm fastmap identify super-maximal exact matches pemerge merge overlapping paired ends (EXPERIMENTAL) aln gapped/ungapped alignment samse generate alignment (single ended) sampe generate alignment (paired ended) bwasw BWA-SW for long queries shm manage indices in shared memory fa2pac convert FASTA to PAC format pac2bwt generate BWT from PAC pac2bwtgen alternative algorithm for generating BWT bwtupdate update .bwt to the new format bwt2sa generate SA from BWT and Occ Note: To use BWA, you need to first index the genome with `bwa index'. There are three alignment algorithms in BWA: `mem', `bwasw', and `aln/samse/sampe'. If you are not sure which to use, try `bwa mem' first. Please `man ./bwa.1' for the manual. snakemake-5.10.0/tests/test_conda/test-env.yaml000066400000000000000000000001061361131222100214370ustar00rootroot00000000000000channels: - bioconda - conda-forge dependencies: - bwa ==0.7.17 snakemake-5.10.0/tests/test_conda_custom_prefix/000077500000000000000000000000001361131222100217605ustar00rootroot00000000000000snakemake-5.10.0/tests/test_conda_custom_prefix/Snakefile000066400000000000000000000003561361131222100236100ustar00rootroot00000000000000rule all: input: expand("test{i}.out", i=range(3)) rule a: output: "test{i}.out" conda: "test-env.yaml" shell: "test -e custom/*/bin/snakemake && " "snakemake --version > {output}" snakemake-5.10.0/tests/test_conda_custom_prefix/expected-results/000077500000000000000000000000001361131222100252605ustar00rootroot00000000000000snakemake-5.10.0/tests/test_conda_custom_prefix/expected-results/test0.out000066400000000000000000000000061361131222100270440ustar00rootroot000000000000005.7.1 snakemake-5.10.0/tests/test_conda_custom_prefix/expected-results/test1.out000066400000000000000000000000061361131222100270450ustar00rootroot000000000000005.7.1 snakemake-5.10.0/tests/test_conda_custom_prefix/expected-results/test2.out000066400000000000000000000000061361131222100270460ustar00rootroot000000000000005.7.1 snakemake-5.10.0/tests/test_conda_custom_prefix/test-env.yaml000066400000000000000000000001231361131222100244050ustar00rootroot00000000000000channels: - conda-forge - bioconda dependencies: - snakemake-minimal ==5.7.1 snakemake-5.10.0/tests/test_conditional/000077500000000000000000000000001361131222100202305ustar00rootroot00000000000000snakemake-5.10.0/tests/test_conditional/Snakefile000066400000000000000000000006621361131222100220600ustar00rootroot00000000000000 CONDITION = False if CONDITION: rule: output: "test.out" shell: "echo bla; exit 1" else: rule: output: "test.out" shell: "touch {output}" # the following is bad style and just for testing. You should rather write a rule that collects test{i}.out as input files and have ONE rule that generates any of the files with a wildcard. for i in range(3): rule: output: "test.{i}.out".format(i=i) shell: "touch {output}" snakemake-5.10.0/tests/test_conditional/expected-results/000077500000000000000000000000001361131222100235305ustar00rootroot00000000000000snakemake-5.10.0/tests/test_conditional/expected-results/test.0.out000066400000000000000000000000001361131222100253640ustar00rootroot00000000000000snakemake-5.10.0/tests/test_conditional/expected-results/test.1.out000066400000000000000000000000001361131222100253650ustar00rootroot00000000000000snakemake-5.10.0/tests/test_conditional/expected-results/test.2.out000066400000000000000000000000001361131222100253660ustar00rootroot00000000000000snakemake-5.10.0/tests/test_conditional/expected-results/test.out000066400000000000000000000000001361131222100252260ustar00rootroot00000000000000snakemake-5.10.0/tests/test_config/000077500000000000000000000000001361131222100171725ustar00rootroot00000000000000snakemake-5.10.0/tests/test_config/Snakefile000066400000000000000000000002041361131222100210120ustar00rootroot00000000000000 include: "test.rules" configfile: "test.json" rule: output: config["outfile"] shell: "touch {output}" snakemake-5.10.0/tests/test_config/expected-results/000077500000000000000000000000001361131222100224725ustar00rootroot00000000000000snakemake-5.10.0/tests/test_config/expected-results/test.out000066400000000000000000000000001361131222100241700ustar00rootroot00000000000000snakemake-5.10.0/tests/test_config/test.json000066400000000000000000000000361361131222100210430ustar00rootroot00000000000000{ "outfile": "test.out" } snakemake-5.10.0/tests/test_config/test.rules000066400000000000000000000000311361131222100212170ustar00rootroot00000000000000configfile: "test2.json" snakemake-5.10.0/tests/test_config/test2.json000066400000000000000000000000371361131222100211260ustar00rootroot00000000000000{ "outfile": "test2.out" } snakemake-5.10.0/tests/test_config/test3.json000066400000000000000000000000371361131222100211270ustar00rootroot00000000000000{ "outfile": "test3.out" } snakemake-5.10.0/tests/test_convert_to_cwl/000077500000000000000000000000001361131222100207545ustar00rootroot00000000000000snakemake-5.10.0/tests/test_convert_to_cwl/Snakefile000066400000000000000000000017371361131222100226100ustar00rootroot00000000000000import os print(os.listdir(".")) print(os.getcwd()) TEST = "abc" onstart: print("Workflow starting") print("Log:") print(log) onsuccess: print("Workflow finished") print("Log:") print(log) onerror: print("Workflow failed") print("Log:") print(log) ruleorder: rule2 > rule4 def testin(wildcards): return "test.in" def version(): return "3.3" rule rule1: # This rule creates an intermediate file. input: 'dir/a/test.inter' output: 'dir/test.out' log: a='log/logfile.log' version: version() shell: 'echo {TEST}; echo {version}; cp {input[0]} {output[0]}; ' # append a comment 'echo test > {log.a}' rule rule2: input: testin output: 'dir/a/test.inter' shell: ''' cp {input[0]} {output[0]} ''' rule rule4: input: "test.in" output: "dir/a/test.inter" shell: "cp {input} {output}" # this should be ignored since test.in is present rule rule3: input: "dir/{a}.out" output: "{a}.in" shell: "cp {input} {output}" snakemake-5.10.0/tests/test_convert_to_cwl/test.in000066400000000000000000000000101361131222100222520ustar00rootroot00000000000000testz0r snakemake-5.10.0/tests/test_core_dependent_threads/000077500000000000000000000000001361131222100224155ustar00rootroot00000000000000snakemake-5.10.0/tests/test_core_dependent_threads/Snakefile000066400000000000000000000001711361131222100242400ustar00rootroot00000000000000rule a: output: "test.out" threads: workflow.cores * 0.75 shell: "echo {threads} > {output}" snakemake-5.10.0/tests/test_core_dependent_threads/expected-results/000077500000000000000000000000001361131222100257155ustar00rootroot00000000000000snakemake-5.10.0/tests/test_core_dependent_threads/expected-results/test.out000066400000000000000000000000021361131222100274150ustar00rootroot000000000000002 snakemake-5.10.0/tests/test_cwl/000077500000000000000000000000001361131222100165125ustar00rootroot00000000000000snakemake-5.10.0/tests/test_cwl/Snakefile000066400000000000000000000003351361131222100203370ustar00rootroot00000000000000rule a: input: input=["test.txt"] output: output="sorted.txt" params: key=["2"] cwl: "https://github.com/common-workflow-language/workflows/raw/master/tools/linux-sort.cwl" snakemake-5.10.0/tests/test_cwl/expected-results/000077500000000000000000000000001361131222100220125ustar00rootroot00000000000000snakemake-5.10.0/tests/test_cwl/expected-results/sorted.txt000066400000000000000000000000141361131222100240460ustar00rootroot00000000000000b 1 a 2 c 3 snakemake-5.10.0/tests/test_cwl/test.txt000066400000000000000000000000141361131222100202250ustar00rootroot00000000000000c 3 a 2 b 1 snakemake-5.10.0/tests/test_default_remote/000077500000000000000000000000001361131222100207245ustar00rootroot00000000000000snakemake-5.10.0/tests/test_default_remote/Snakefile000066400000000000000000000032401361131222100225470ustar00rootroot00000000000000rule all: input: "test.3.txt", 'test.4.txt', 'test.5.txt', 'test.6.txt' def check_remote(f): if not f.startswith("test-remote-bucket/"): raise ValueError("Input and output are not remote files.") def list_function(wildcards): return ["test.2.txt", "test.txt"] def dict_function(wildcards): return {'a': "test.2.txt", 'b': "test.txt"} rule a: input: "test.txt" output: "{sample}.2.txt" run: check_remote(input[0]) check_remote(output[0]) shell("cp {input} {output}") rule b: input: list_function output: "test.3.txt" run: for e in input: check_remote(e) check_remote(output[0]) shell("cp {input[0]} {output}") rule c: input: **dict_function(None) output: "test.4.txt" run: for e in input: check_remote(e) check_remote(output[0]) shell("cp {input.a} {output}") rule d: input: unpack(dict_function) output: "test.5.txt" run: for e in input: check_remote(e) check_remote(output[0]) shell("cp {input.a} {output}") rule e: input: rules.a.output[0] output: "{sample}.6.txt" run: for e in input: check_remote(e) check_remote(output[0]) shell("cp {input} {output}") # after we finish, we need to remove the pickle storing # the local moto "buckets" so we are starting fresh # next time this test is run. This file is created by # the moto wrapper defined in S3Mocked.py onsuccess: shell("rm ./motoState.p") onerror: shell("rm ./motoState.p") snakemake-5.10.0/tests/test_default_remote/expected-results/000077500000000000000000000000001361131222100242245ustar00rootroot00000000000000snakemake-5.10.0/tests/test_default_remote/expected-results/.gitignore000066400000000000000000000000001361131222100262020ustar00rootroot00000000000000snakemake-5.10.0/tests/test_default_remote/test.txt000066400000000000000000000000051361131222100224370ustar00rootroot00000000000000test snakemake-5.10.0/tests/test_default_resources/000077500000000000000000000000001361131222100214435ustar00rootroot00000000000000snakemake-5.10.0/tests/test_default_resources/Snakefile000066400000000000000000000007061361131222100232720ustar00rootroot00000000000000from snakemake.remote.S3Mocked import RemoteProvider as S3RemoteProvider s3 = S3RemoteProvider() rule a: input: s3.remote("test-remote-bucket/test.in") output: "test.out" group: "test" shell: "[[ '{resources.mem_mb}' == '1000' ]] && touch {output}" rule b: output: s3.remote("test-remote-bucket/test.in") group: "test" shell: "[[ '{resources.mem_mb}' == '1000' ]] && touch {output}" snakemake-5.10.0/tests/test_default_resources/expected-results/000077500000000000000000000000001361131222100247435ustar00rootroot00000000000000snakemake-5.10.0/tests/test_default_resources/expected-results/test.out000066400000000000000000000000001361131222100264410ustar00rootroot00000000000000snakemake-5.10.0/tests/test_default_resources/test.txt000066400000000000000000000000051361131222100231560ustar00rootroot00000000000000test snakemake-5.10.0/tests/test_deferred_func_eval/000077500000000000000000000000001361131222100215275ustar00rootroot00000000000000snakemake-5.10.0/tests/test_deferred_func_eval/Snakefile000066400000000000000000000006561361131222100233620ustar00rootroot00000000000000import os def get_mem_gb(wildcards, input): size = 0 if os.path.exists(input[0]): size = int(os.path.getsize(input[0]) / (1024 ** 3)) return max(size, 1) rule a: input: "test1.in", "test2.in" output: "test.out" params: a=lambda wildcards, input, resources: "+".join(input) resources: mem_gb=get_mem_gb shell: "echo {params.a} > {output}" snakemake-5.10.0/tests/test_deferred_func_eval/expected-results/000077500000000000000000000000001361131222100250275ustar00rootroot00000000000000snakemake-5.10.0/tests/test_deferred_func_eval/expected-results/test.out000066400000000000000000000000221361131222100265310ustar00rootroot00000000000000test1.in+test2.in snakemake-5.10.0/tests/test_deferred_func_eval/test1.in000066400000000000000000000000001361131222100231050ustar00rootroot00000000000000snakemake-5.10.0/tests/test_deferred_func_eval/test2.in000066400000000000000000000000001361131222100231060ustar00rootroot00000000000000snakemake-5.10.0/tests/test_delete_all_output/000077500000000000000000000000001361131222100214375ustar00rootroot00000000000000snakemake-5.10.0/tests/test_delete_all_output/Snakefile000066400000000000000000000016221361131222100232640ustar00rootroot00000000000000rule all: input: "delete_all_output", "delete_temp_output" output: touch("all_ok") rule delete_all_output: output: touch("delete_all_output") shell: """ echo $PATH ls python -m snakemake -s Snakefile_inner all && \ rm nothere && \ python -m snakemake -s Snakefile_inner --delete-all-output all && \ test -f infile && test ! -f intermediate && test ! -f somedir/final && \ test ! -d empty_dir && test ! -L dangling && test ! -d full_dir """ rule delete_temp_output: output: touch("delete_temp_output") shell: """ python -m snakemake -s Snakefile_inner --notemp temp && \ python -m snakemake -s Snakefile_inner --delete-temp-output temp && \ test -f infile && test ! -f temp_intermediate && \ test ! -d temp_empty_dir && test ! -d temp_full_dir && test -f temp_keep """ snakemake-5.10.0/tests/test_delete_all_output/Snakefile_inner000066400000000000000000000017061361131222100244620ustar00rootroot00000000000000rule all: input: "some_dir/final", "empty_dir", "full_dir" rule a: input: "infile" output: "intermediate", "dangling", touch(protected("protected")) shell: "ln -s {input} {output[0]} && touch nothere && ln -s nothere {output[1]}" rule b: input: "intermediate" output: touch("some_dir/final") rule c: output: directory("empty_dir") shell: "mkdir empty_dir" rule d: output: directory("full_dir") shell: "mkdir full_dir && touch full_dir/somefile" rule e: input: "infile" output: temp("temp_intermediate") shell: "touch {output}" rule f: input: "temp_intermediate" output: directory(temp("temp_empty_dir")) shell: "mkdir temp_empty_dir" rule g: input: "temp_intermediate" output: directory(temp("temp_full_dir")) shell: "mkdir temp_full_dir && touch temp_full_dir/somefile" rule temp: input: "temp_empty_dir", "temp_full_dir" output: touch("temp_keep") snakemake-5.10.0/tests/test_delete_all_output/expected-results/000077500000000000000000000000001361131222100247375ustar00rootroot00000000000000snakemake-5.10.0/tests/test_delete_all_output/expected-results/all_ok000066400000000000000000000000001361131222100261110ustar00rootroot00000000000000snakemake-5.10.0/tests/test_delete_all_output/infile000066400000000000000000000000001361131222100226160ustar00rootroot00000000000000snakemake-5.10.0/tests/test_delete_output/000077500000000000000000000000001361131222100206075ustar00rootroot00000000000000snakemake-5.10.0/tests/test_delete_output/Snakefile000066400000000000000000000040341361131222100224340ustar00rootroot00000000000000# See bug #300. This tests that output files really are cleaned up # before running a rule, and touched afterwards. # # The output should be deleted before the job starts. # (The output should be deleted on the the head node for cluster jobs.) # The path to the output should be created # The output should be touch'd on the head node to always be new. # # Additionally this should work for directories, symlinks and symlinks # to directories. # # TODO - consider adding a cluster-based test for point 2 above. # Setup - touch a mock input file and an out-of-date output file. shell("touch -t 201604010000 output.file") shell("touch input.file") # An empty directory shell("mkdir -p output.dir ; touch -ch -t 201604010000 output.dir") # A dangling symlink shell("ln -fs nosuchfile output.link ; touch -ch -t 201604010000 output.link") # A symlink to an empty directory shell("mkdir -p an_empty_dir; ln -fs an_empty_dir output.dirlink ; touch -ch -t 201604010000 an_empty_dir output.dirlink") rule main: input: "output.file", "output.dir", "output.link", "output.dirlink" rule make_the_file: output: "output.file", "foo/output.foo.file" input: "input.file" # Rule fails if any output.file is already present run: shell("test ! -e output.file") shell("test -d foo") shell("test ! -e foo/*") shell("touch -t 201604010000 output.file") shell("touch foo/output.foo.file") rule make_the_dir: output: directory("output.dir") input: "input.file" #mkdir fails if the dir is already present run: shell("mkdir output.dir") shell("touch output.dir/foo") rule make_the_links: output: "output.link", directory("output.dirlink") input: "input.file" # Both links should be gone, but an_empty_dir should not have been removed # as it's not a direct target of the rule. run: shell("touch arealfile") shell("ln -s arealfile output.link") shell("test -d an_empty_dir") shell("mkdir empty_dir2") shell("ln -s empty_dir2 output.dirlink") snakemake-5.10.0/tests/test_delete_output/expected-results/000077500000000000000000000000001361131222100241075ustar00rootroot00000000000000snakemake-5.10.0/tests/test_delete_output/expected-results/foo/000077500000000000000000000000001361131222100246725ustar00rootroot00000000000000snakemake-5.10.0/tests/test_delete_output/expected-results/foo/output.foo.file000066400000000000000000000000001361131222100276430ustar00rootroot00000000000000snakemake-5.10.0/tests/test_delete_output/expected-results/output.file000066400000000000000000000000001361131222100262760ustar00rootroot00000000000000snakemake-5.10.0/tests/test_delete_output/nosuchfile000066400000000000000000000000001361131222100226570ustar00rootroot00000000000000snakemake-5.10.0/tests/test_directory/000077500000000000000000000000001361131222100177315ustar00rootroot00000000000000snakemake-5.10.0/tests/test_directory/Snakefile000066400000000000000000000024711361131222100215610ustar00rootroot00000000000000shell("mkdir -p input_dir && touch input_dir/child") rule downstream: input: "some/dir" output: touch(directory("some/other_dir")) rule normal: input: "input_dir" output: directory("some/dir") shell: "mkdir -p {output} && touch some/dir/some_file" rule symlinked_output: output: directory("symlinked_dir") shell: "mkdir dir_to_link_to && ln -s dir_to_link_to symlinked_dir" rule symlinked_input: input: "symlinked_dir" # Check that there is an error if the output isn't a directory rule file_expecting_dir: output: directory("not_a_dir") shell: "touch not_a_dir" # Check that there is an error if an output directory isn't flagged with directory() rule dir_expecting_file: output: "is_a_dir" shell: "mkdir is_a_dir" # Should fail due to being a child to some/dir rule child_to_other: input: "some/other_dir" output: touch("some/dir/child") # Shouldn't fail, even though some/dir is a shared prefix rule not_child_to_other: input: "some/other_dir" output: touch("some/dir-child") # Shouldn't fail since children to inputs are currently allowed. rule child_to_input: input: "input_dir/child" output: touch("child_to_input") rule shadow: input: "some/dir" output: directory("some/shadow") shadow: "shallow" shell: "mkdir -p {output}" snakemake-5.10.0/tests/test_directory/expected-results/000077500000000000000000000000001361131222100232315ustar00rootroot00000000000000snakemake-5.10.0/tests/test_directory/expected-results/child_to_input000066400000000000000000000000001361131222100261460ustar00rootroot00000000000000snakemake-5.10.0/tests/test_directory/expected-results/dir_to_link_to/000077500000000000000000000000001361131222100262305ustar00rootroot00000000000000snakemake-5.10.0/tests/test_directory/expected-results/dir_to_link_to/.snakemake_timestamp000066400000000000000000000000001361131222100322410ustar00rootroot00000000000000snakemake-5.10.0/tests/test_directory/expected-results/some/000077500000000000000000000000001361131222100241745ustar00rootroot00000000000000snakemake-5.10.0/tests/test_directory/expected-results/some/dir-child000066400000000000000000000000001361131222100257440ustar00rootroot00000000000000snakemake-5.10.0/tests/test_directory/expected-results/some/shadow/000077500000000000000000000000001361131222100254615ustar00rootroot00000000000000snakemake-5.10.0/tests/test_directory/expected-results/some/shadow/.snakemake_timestamp000066400000000000000000000000001361131222100314720ustar00rootroot00000000000000snakemake-5.10.0/tests/test_directory/expected-results/some_other_dir/000077500000000000000000000000001361131222100262335ustar00rootroot00000000000000snakemake-5.10.0/tests/test_directory/expected-results/some_other_dir/.snakemake_timestamp000066400000000000000000000000001361131222100322440ustar00rootroot00000000000000snakemake-5.10.0/tests/test_dup_out_patterns/000077500000000000000000000000001361131222100213245ustar00rootroot00000000000000snakemake-5.10.0/tests/test_dup_out_patterns/Snakefile000066400000000000000000000002551361131222100231520ustar00rootroot00000000000000rule default: input: "out.txt" rule my_rule: output: "{name}.txt", "{name}.txt", shell: r""" touch {output} """ snakemake-5.10.0/tests/test_dup_out_patterns/expected-results/000077500000000000000000000000001361131222100246245ustar00rootroot00000000000000snakemake-5.10.0/tests/test_dup_out_patterns/expected-results/.gitkeep000066400000000000000000000000001361131222100262430ustar00rootroot00000000000000snakemake-5.10.0/tests/test_dynamic/000077500000000000000000000000001361131222100173515ustar00rootroot00000000000000snakemake-5.10.0/tests/test_dynamic/Snakefile000066400000000000000000000010511361131222100211720ustar00rootroot00000000000000# snakemake rule all: input: a=dynamic("test.{n}.{bla}.out"), b=dynamic("test.{n}.{bla}.csv") run: print(input.b) rule inter: input: "test.{n}.{bla}.inter" output: "test.{n}.{bla}.out" shell: "cp {input} {output}" rule dynoutput: input: "test.xy.in" output: dynamic("test.{n}.{bla}.inter") shell: "for i in {{0..2}}; do touch test.0$i.xy.inter; done" rule: input: "test.{n}.{bla}.inter" output: "test.{n}.{bla}.txt" shell: "touch {output}" rule: input: "test.{n}.{bla}.txt" output: "test.{n}.{bla}.csv" shell: "cp {input} {output}" snakemake-5.10.0/tests/test_dynamic/expected-results/000077500000000000000000000000001361131222100226515ustar00rootroot00000000000000snakemake-5.10.0/tests/test_dynamic/expected-results/test.00.xy.csv000066400000000000000000000000001361131222100252100ustar00rootroot00000000000000snakemake-5.10.0/tests/test_dynamic/expected-results/test.00.xy.out000066400000000000000000000000001361131222100252240ustar00rootroot00000000000000snakemake-5.10.0/tests/test_dynamic/expected-results/test.01.xy.csv000066400000000000000000000000001361131222100252110ustar00rootroot00000000000000snakemake-5.10.0/tests/test_dynamic/expected-results/test.01.xy.out000066400000000000000000000000001361131222100252250ustar00rootroot00000000000000snakemake-5.10.0/tests/test_dynamic/expected-results/test.02.xy.csv000066400000000000000000000000001361131222100252120ustar00rootroot00000000000000snakemake-5.10.0/tests/test_dynamic/expected-results/test.02.xy.out000066400000000000000000000000001361131222100252260ustar00rootroot00000000000000snakemake-5.10.0/tests/test_dynamic/test.xy.in000066400000000000000000000000001361131222100213050ustar00rootroot00000000000000snakemake-5.10.0/tests/test_dynamic_temp/000077500000000000000000000000001361131222100203765ustar00rootroot00000000000000snakemake-5.10.0/tests/test_dynamic_temp/Snakefile000066400000000000000000000014021361131222100222170ustar00rootroot00000000000000# Snakefile # each input is 8 lines SCRATCH = 'test' rule all: input: 'out.txt' run: if os.listdir('test'): raise ValueError('not all temp files have been deleted') rule gather: input: dynamic('{}/split_1.{{id}}'.format(SCRATCH)), dynamic('{}/split_2.{{id}}'.format(SCRATCH)) output: 'out.txt' shell: 'touch {output}' rule scatter: input: 'test1.txt', 'test2.txt' output: temp(dynamic('{}/split_1.{{id}}'.format(SCRATCH))), temp(dynamic('{}/split_2.{{id}}'.format(SCRATCH))) shell: ('cat {{input[0]}} | head -8 | split -a 4 -l 4 - {}/split_1.; ' 'cat {{input[1]}} | head -8 | split -a 4 -l 4 - {}/split_2.' .format(SCRATCH, SCRATCH)) snakemake-5.10.0/tests/test_dynamic_temp/expected-results/000077500000000000000000000000001361131222100236765ustar00rootroot00000000000000snakemake-5.10.0/tests/test_dynamic_temp/expected-results/out.txt000066400000000000000000000000001361131222100252340ustar00rootroot00000000000000snakemake-5.10.0/tests/test_dynamic_temp/test1.txt000066400000000000000000000000201361131222100221670ustar00rootroot000000000000001 2 3 4 5 6 7 8 snakemake-5.10.0/tests/test_dynamic_temp/test2.txt000066400000000000000000000000201361131222100221700ustar00rootroot000000000000001 2 3 4 5 6 7 8 snakemake-5.10.0/tests/test_empty_include/000077500000000000000000000000001361131222100205665ustar00rootroot00000000000000snakemake-5.10.0/tests/test_empty_include/Snakefile000066400000000000000000000000311361131222100224040ustar00rootroot00000000000000include: "include.rules" snakemake-5.10.0/tests/test_empty_include/expected-results/000077500000000000000000000000001361131222100240665ustar00rootroot00000000000000snakemake-5.10.0/tests/test_empty_include/expected-results/.gitignore000066400000000000000000000000001361131222100260440ustar00rootroot00000000000000snakemake-5.10.0/tests/test_empty_include/include.rules000066400000000000000000000000001361131222100232530ustar00rootroot00000000000000snakemake-5.10.0/tests/test_env_modules/000077500000000000000000000000001361131222100202455ustar00rootroot00000000000000snakemake-5.10.0/tests/test_env_modules/Snakefile000066400000000000000000000001671361131222100220750ustar00rootroot00000000000000rule a: output: "test.out" envmodules: "dot" shell: "test-env-modules.sh {output}" snakemake-5.10.0/tests/test_env_modules/expected-results/000077500000000000000000000000001361131222100235455ustar00rootroot00000000000000snakemake-5.10.0/tests/test_env_modules/expected-results/test.out000066400000000000000000000000051361131222100252500ustar00rootroot00000000000000test snakemake-5.10.0/tests/test_env_modules/test-env-modules.sh000077500000000000000000000000171361131222100240150ustar00rootroot00000000000000echo test > $1 snakemake-5.10.0/tests/test_expand.py000066400000000000000000000043471361131222100175660ustar00rootroot00000000000000from snakemake.io import expand from snakemake.exceptions import WildcardError import pytest def test_simple_expand(): # single filepattern assert expand("{a}.out", a="test") == ["test.out"] # multiple filepatterns assert expand(["{a}.out", "{b}.out"], a="a", b="b") == ["a.out", "b.out"] # multiple wildcards assert expand("{a}.out", a=["1", "2", "3"]) == ["1.out", "2.out", "3.out"] # multiple wildcards and patterns assert expand(["{a}_{b}.ab", "{b}.b"], a="1 2".split(), b="3 4".split()) == [ "1_3.ab", "1_4.ab", "2_3.ab", "2_4.ab", "3.b", "4.b", ] # replace product assert expand(["{a}_{b}.ab", "{b}.b"], zip, a="1 2".split(), b="3 4".split()) == [ "1_3.ab", "2_4.ab", "3.b", "4.b", ] def test_allow_missing(): # single filepattern assert expand("{a}_{b}.out", allow_missing=True) == ["{a}_{b}.out"] assert expand("{a}_{b}.out", a="test", allow_missing=True) == ["test_{b}.out"] # none missing assert expand("{a}.out", a="test", allow_missing=True) == ["test.out"] # wildcard is allow_missing assert expand("{allow_missing}.out", allow_missing=True) == ["True.out"] # allow_missing not True assert expand("{a}.out", a="test", allow_missing="test2") == ["test.out"] with pytest.raises(WildcardError) as e: expand("{a}.out", allow_missing="test2") assert str(e.value) == "No values given for wildcard 'a'." # multiple filepatterns assert expand(["{a}.out", "{b}.out"], allow_missing=True) == ["{a}.out", "{b}.out"] # multiple wildcards assert expand("{a}_{b}.out", a=["1", "2", "3"], allow_missing=True) == [ "1_{b}.out", "2_{b}.out", "3_{b}.out", ] # multiple wildcards and patterns assert expand( ["{a}_{b}_{C}.ab", "{b}_{c}.b"], a="1 2".split(), b="3 4".split(), allow_missing=True, ) == ["1_3_{C}.ab", "1_4_{C}.ab", "2_3_{C}.ab", "2_4_{C}.ab", "3_{c}.b", "4_{c}.b"] # replace product assert expand( ["{a}_{b}_{C}.ab", "{b}_{c}.b"], zip, a="1 2".split(), b="3 4".split(), allow_missing=True, ) == ["1_3_{C}.ab", "2_4_{C}.ab", "3_{c}.b", "4_{c}.b"] snakemake-5.10.0/tests/test_expand_flag/000077500000000000000000000000001361131222100201755ustar00rootroot00000000000000snakemake-5.10.0/tests/test_expand_flag/Snakefile000066400000000000000000000001601361131222100220160ustar00rootroot00000000000000rule a: output: expand(directory("{sample}/dir"), sample=["a"]) shell: "mkdir {output}" snakemake-5.10.0/tests/test_expand_flag/expected-results/000077500000000000000000000000001361131222100234755ustar00rootroot00000000000000snakemake-5.10.0/tests/test_expand_flag/expected-results/.gitignore000066400000000000000000000000001361131222100254530ustar00rootroot00000000000000snakemake-5.10.0/tests/test_filegraph/000077500000000000000000000000001361131222100176665ustar00rootroot00000000000000snakemake-5.10.0/tests/test_filegraph/Snakefile000066400000000000000000000007061361131222100215150ustar00rootroot00000000000000import os rule all: input: expand("folder/file_{v1}_{v2}.dat", v1=[1, 2], v2=["a", "b"]), expand("visualization_of_1_a.pdf", v1=[1, 2]) rule data: output: "folder/file_{v1}_{v2}.dat" shell: "touch {output}" rule visualization: input: "folder/file_1_a.dat", lambda x: os.path.join("scripts", "vis.py"), output: "visualization_of_1_a.pdf" shell: "touch {output}" snakemake-5.10.0/tests/test_filegraph/scripts/000077500000000000000000000000001361131222100213555ustar00rootroot00000000000000snakemake-5.10.0/tests/test_filegraph/scripts/vis.py000066400000000000000000000000001361131222100225160ustar00rootroot00000000000000snakemake-5.10.0/tests/test_format_params/000077500000000000000000000000001361131222100205605ustar00rootroot00000000000000snakemake-5.10.0/tests/test_format_params/Snakefile000066400000000000000000000001461361131222100224050ustar00rootroot00000000000000rule a: output: "test.out" params: [1, 2, 3] shell: "echo {params[0]} > {output}" snakemake-5.10.0/tests/test_format_params/expected-results/000077500000000000000000000000001361131222100240605ustar00rootroot00000000000000snakemake-5.10.0/tests/test_format_params/expected-results/test.out000066400000000000000000000000061361131222100255640ustar00rootroot000000000000001 2 3 snakemake-5.10.0/tests/test_format_wildcards/000077500000000000000000000000001361131222100212515ustar00rootroot00000000000000snakemake-5.10.0/tests/test_format_wildcards/Snakefile000066400000000000000000000002111361131222100230670ustar00rootroot00000000000000rule all: input: "foo.txt" rule a: output: "{test}.txt" shell: "echo {rule} {wildcards} > {output}" snakemake-5.10.0/tests/test_format_wildcards/expected-results/000077500000000000000000000000001361131222100245515ustar00rootroot00000000000000snakemake-5.10.0/tests/test_format_wildcards/expected-results/foo.txt000066400000000000000000000000131361131222100260670ustar00rootroot00000000000000a test=foo snakemake-5.10.0/tests/test_ftp_immediate_close/000077500000000000000000000000001361131222100217215ustar00rootroot00000000000000snakemake-5.10.0/tests/test_ftp_immediate_close/Snakefile000066400000000000000000000004401361131222100235430ustar00rootroot00000000000000from snakemake.remote.FTP import RemoteProvider FTP = RemoteProvider() rule a: input: FTP.remote("ftp://ftp.sra.ebi.ac.uk/vol1/ERA651/ERA651425/fastq/RAG16_R1.fastq.gz", immediate_close=True) output: "size.txt" run: shell("du -h {input} > {output}") snakemake-5.10.0/tests/test_ftp_immediate_close/expected-results/000077500000000000000000000000001361131222100252215ustar00rootroot00000000000000snakemake-5.10.0/tests/test_ftp_immediate_close/expected-results/size.txt000066400000000000000000000001051361131222100267300ustar00rootroot000000000000009.9M ftp.sra.ebi.ac.uk/vol1/ERA651/ERA651425/fastq/RAG16_R1.fastq.gz snakemake-5.10.0/tests/test_get_log_both/000077500000000000000000000000001361131222100203615ustar00rootroot00000000000000snakemake-5.10.0/tests/test_get_log_both/Snakefile000066400000000000000000000001571361131222100222100ustar00rootroot00000000000000rule: input: "test.in" output: "test.out" log: "test.log" wrapper: 'file://wrapper.py' snakemake-5.10.0/tests/test_get_log_both/expected-results/000077500000000000000000000000001361131222100236615ustar00rootroot00000000000000snakemake-5.10.0/tests/test_get_log_both/expected-results/test.log000066400000000000000000000000421361131222100253370ustar00rootroot00000000000000a stderr message a stdout message snakemake-5.10.0/tests/test_get_log_both/expected-results/test.out000066400000000000000000000000101361131222100253600ustar00rootroot00000000000000foo bar snakemake-5.10.0/tests/test_get_log_both/test.in000066400000000000000000000000101361131222100216570ustar00rootroot00000000000000foo bar snakemake-5.10.0/tests/test_get_log_both/wrapper.py000066400000000000000000000003431361131222100224130ustar00rootroot00000000000000from snakemake.shell import shell log = snakemake.log_fmt_shell(append=True) shell(''' cat {snakemake.input} > {snakemake.output} (>&2 echo "a stderr message") {log} (echo "a stdout message") {log} ''') snakemake-5.10.0/tests/test_get_log_complex/000077500000000000000000000000001361131222100210745ustar00rootroot00000000000000snakemake-5.10.0/tests/test_get_log_complex/Snakefile000066400000000000000000000001571361131222100227230ustar00rootroot00000000000000rule: input: "test.in" output: "test.out" log: "test.log" wrapper: 'file://wrapper.py' snakemake-5.10.0/tests/test_get_log_complex/expected-results/000077500000000000000000000000001361131222100243745ustar00rootroot00000000000000snakemake-5.10.0/tests/test_get_log_complex/expected-results/test.log000066400000000000000000000000551361131222100260560ustar00rootroot00000000000000first line a stderr message a stdout message snakemake-5.10.0/tests/test_get_log_complex/expected-results/test.out000066400000000000000000000000101361131222100260730ustar00rootroot00000000000000foo bar snakemake-5.10.0/tests/test_get_log_complex/test.in000066400000000000000000000000101361131222100223720ustar00rootroot00000000000000foo bar snakemake-5.10.0/tests/test_get_log_complex/wrapper.py000066400000000000000000000007331361131222100231310ustar00rootroot00000000000000from snakemake.shell import shell initial_log = snakemake.log_fmt_shell() stdout_log = snakemake.log_fmt_shell(stderr=False, append=True) stderr_log = snakemake.log_fmt_shell(stdout=False, append=True) shell(''' cat {snakemake.input} > {snakemake.output} echo "should not appear since next line truncates" {initial_log} echo "first line" {initial_log} (>&2 echo "a stderr message") {stderr_log} (echo "a stdout message") {stdout_log} ''') snakemake-5.10.0/tests/test_get_log_none/000077500000000000000000000000001361131222100203645ustar00rootroot00000000000000snakemake-5.10.0/tests/test_get_log_none/Snakefile000066400000000000000000000001311361131222100222030ustar00rootroot00000000000000rule: input: "test.in" output: "test.out" wrapper: 'file:wrapper.py' snakemake-5.10.0/tests/test_get_log_none/expected-results/000077500000000000000000000000001361131222100236645ustar00rootroot00000000000000snakemake-5.10.0/tests/test_get_log_none/expected-results/test.out000066400000000000000000000000101361131222100253630ustar00rootroot00000000000000foo bar snakemake-5.10.0/tests/test_get_log_none/test.in000066400000000000000000000000101361131222100216620ustar00rootroot00000000000000foo bar snakemake-5.10.0/tests/test_get_log_none/wrapper.py000066400000000000000000000003441361131222100224170ustar00rootroot00000000000000from snakemake.shell import shell log = snakemake.log_fmt_shell(stdout=False) shell(''' cat {snakemake.input} > {snakemake.output} (>&2 echo "a stderr message") {log} (echo "a stdout message") {log} ''') snakemake-5.10.0/tests/test_get_log_stderr/000077500000000000000000000000001361131222100207305ustar00rootroot00000000000000snakemake-5.10.0/tests/test_get_log_stderr/Snakefile000066400000000000000000000001571361131222100225570ustar00rootroot00000000000000rule: input: "test.in" output: "test.out" log: "test.log" wrapper: 'file://wrapper.py' snakemake-5.10.0/tests/test_get_log_stderr/expected-results/000077500000000000000000000000001361131222100242305ustar00rootroot00000000000000snakemake-5.10.0/tests/test_get_log_stderr/expected-results/test.log000066400000000000000000000000211361131222100257030ustar00rootroot00000000000000a stderr message snakemake-5.10.0/tests/test_get_log_stderr/expected-results/test.out000066400000000000000000000000101361131222100257270ustar00rootroot00000000000000foo bar snakemake-5.10.0/tests/test_get_log_stderr/test.in000066400000000000000000000000101361131222100222260ustar00rootroot00000000000000foo bar snakemake-5.10.0/tests/test_get_log_stderr/wrapper.py000066400000000000000000000003611361131222100227620ustar00rootroot00000000000000from snakemake.shell import shell log = snakemake.log_fmt_shell(stdout=False, append=True) shell(''' cat {snakemake.input} > {snakemake.output} (>&2 echo "a stderr message") {log} (echo "a stdout message") {log} ''') snakemake-5.10.0/tests/test_get_log_stdout/000077500000000000000000000000001361131222100207475ustar00rootroot00000000000000snakemake-5.10.0/tests/test_get_log_stdout/Snakefile000066400000000000000000000001571361131222100225760ustar00rootroot00000000000000rule: input: "test.in" output: "test.out" log: "test.log" wrapper: 'file://wrapper.py' snakemake-5.10.0/tests/test_get_log_stdout/expected-results/000077500000000000000000000000001361131222100242475ustar00rootroot00000000000000snakemake-5.10.0/tests/test_get_log_stdout/expected-results/test.log000066400000000000000000000000211361131222100257220ustar00rootroot00000000000000a stdout message snakemake-5.10.0/tests/test_get_log_stdout/expected-results/test.out000066400000000000000000000000101361131222100257460ustar00rootroot00000000000000foo bar snakemake-5.10.0/tests/test_get_log_stdout/test.in000066400000000000000000000000101361131222100222450ustar00rootroot00000000000000foo bar snakemake-5.10.0/tests/test_get_log_stdout/wrapper.py000066400000000000000000000003611361131222100230010ustar00rootroot00000000000000from snakemake.shell import shell log = snakemake.log_fmt_shell(stderr=False, append=True) shell(''' cat {snakemake.input} > {snakemake.output} (>&2 echo "a stderr message") {log} (echo "a stdout message") {log} ''') snakemake-5.10.0/tests/test_github_issue105/000077500000000000000000000000001361131222100206455ustar00rootroot00000000000000snakemake-5.10.0/tests/test_github_issue105/Snakefile000066400000000000000000000005611361131222100224730ustar00rootroot00000000000000rule all: input: "b.txt" checkpoint a: output: "a.txt" shell: "touch {output}" def aggregate(wildcards): # files = {'inp1': "Snakefile"} files = {'inp1': checkpoints.a.get(**wildcards).output[0]} return files rule b: input: unpack(aggregate) output: "b.txt" shell: "touch {output}" snakemake-5.10.0/tests/test_github_issue105/expected-results/000077500000000000000000000000001361131222100241455ustar00rootroot00000000000000snakemake-5.10.0/tests/test_github_issue105/expected-results/a.txt000066400000000000000000000000001361131222100251140ustar00rootroot00000000000000snakemake-5.10.0/tests/test_github_issue105/expected-results/b.txt000066400000000000000000000000001361131222100251150ustar00rootroot00000000000000snakemake-5.10.0/tests/test_github_issue52/000077500000000000000000000000001361131222100205665ustar00rootroot00000000000000snakemake-5.10.0/tests/test_github_issue52/B000066400000000000000000000000001361131222100206600ustar00rootroot00000000000000snakemake-5.10.0/tests/test_github_issue52/Snakefile000066400000000000000000000003751361131222100224170ustar00rootroot00000000000000rule All: input: "C" rule A: output: "outputA/A1", "outputA/A2", directory("outputA") shell: "mkdir -p outputA; touch outputA/A1; touch outputA/A2" rule C: input: test="outputA/A1", testb="B" output: "C" shell: "cp {input.test} C" snakemake-5.10.0/tests/test_github_issue52/expected-results/000077500000000000000000000000001361131222100240665ustar00rootroot00000000000000snakemake-5.10.0/tests/test_github_issue52/expected-results/.gitkeep000066400000000000000000000000001361131222100255050ustar00rootroot00000000000000snakemake-5.10.0/tests/test_github_issue52/other.smk000066400000000000000000000005001361131222100224160ustar00rootroot00000000000000rule All: input: "C" rule A: output: "outputA/A1", "outputA/A2", directory("outputA") shell: "mkdir -p outputA; touch outputA/A1; touch outputA/A2" rule B: input: "outputA" output: "B" shell: "touch B" rule C: input: test="outputA/A1", testb="B" output: "C" shell: "cp {input.test} C" snakemake-5.10.0/tests/test_github_issue78/000077500000000000000000000000001361131222100205765ustar00rootroot00000000000000snakemake-5.10.0/tests/test_github_issue78/Snakefile000066400000000000000000000015111361131222100224200ustar00rootroot00000000000000rule all: input: "test.out" rule singularity_ok: input: "test_a.out", "test_b.out", "test_c.out" output: touch("test.out") shell: """ test ! -f junk_a.out test ! -f junk_b.out test ! -f junk_c.out """ rule a: output: "test_a.out" singularity: "docker://bash" shadow: "minimal" shell: 'echo 1 > junk_a.out; echo "test" > {output}' rule b: output: "test_b.out" shadow: "minimal" shell: 'echo 1 > junk_b.out; echo "test" > {output}' rule c: output: "test_c.out" shadow: "minimal" run: with open(output[0], 'w') as fp: print("test", file=fp) with open('junk_c.out', 'w') as fp: print("junk", file=fp) snakemake-5.10.0/tests/test_github_issue78/expected-results/000077500000000000000000000000001361131222100240765ustar00rootroot00000000000000snakemake-5.10.0/tests/test_github_issue78/expected-results/test.out000066400000000000000000000000001361131222100255740ustar00rootroot00000000000000snakemake-5.10.0/tests/test_github_issue78/expected-results/test_a.out000066400000000000000000000000051361131222100261010ustar00rootroot00000000000000test snakemake-5.10.0/tests/test_github_issue78/expected-results/test_b.out000066400000000000000000000000051361131222100261020ustar00rootroot00000000000000test snakemake-5.10.0/tests/test_github_issue78/expected-results/test_c.out000066400000000000000000000000051361131222100261030ustar00rootroot00000000000000test snakemake-5.10.0/tests/test_github_issue_14/000077500000000000000000000000001361131222100207235ustar00rootroot00000000000000snakemake-5.10.0/tests/test_github_issue_14/Snakefile000066400000000000000000000001631361131222100225470ustar00rootroot00000000000000rule all: input: "pythonTest" rule test_github_issue_14: output: "pythonTest" script: "pythonTest.py" snakemake-5.10.0/tests/test_github_issue_14/expected-results/000077500000000000000000000000001361131222100242235ustar00rootroot00000000000000snakemake-5.10.0/tests/test_github_issue_14/expected-results/pythonTest000066400000000000000000000000451361131222100263260ustar00rootroot00000000000000local_script.contents blah blah blah snakemake-5.10.0/tests/test_github_issue_14/local_script.py000066400000000000000000000000341361131222100237500ustar00rootroot00000000000000contents = "blah blah blah" snakemake-5.10.0/tests/test_github_issue_14/pythonTest.py000066400000000000000000000007111361131222100234550ustar00rootroot00000000000000#!/usr/bin/env python import sys import os import local_script # Ensure that the __real_file__ path ends in .snakemake dname = os.path.dirname(__real_file__) print(dname) if not dname.endswith(os.path.join(".snakemake", "scripts")): sys.exit("We're not being written in the output directory!\n") # Write out script to indicte success. of = open(snakemake.output[0], "w") of.write("local_script.contents {}\n".format(local_script.contents)) of.close() snakemake-5.10.0/tests/test_globwildcards/000077500000000000000000000000001361131222100205455ustar00rootroot00000000000000snakemake-5.10.0/tests/test_globwildcards/Snakefile000066400000000000000000000002551361131222100223730ustar00rootroot00000000000000 IDS, = glob_wildcards("test.{id}.txt") rule all: input: expand("test.{id}.out", id=IDS) rule: input: "test.{id}.txt" output: "test.{id}.out" shell: "touch {output}" snakemake-5.10.0/tests/test_globwildcards/expected-results/000077500000000000000000000000001361131222100240455ustar00rootroot00000000000000snakemake-5.10.0/tests/test_globwildcards/expected-results/test.0.out000066400000000000000000000000001361131222100257010ustar00rootroot00000000000000snakemake-5.10.0/tests/test_globwildcards/expected-results/test.1.out000066400000000000000000000000001361131222100257020ustar00rootroot00000000000000snakemake-5.10.0/tests/test_globwildcards/expected-results/test.2.out000066400000000000000000000000001361131222100257030ustar00rootroot00000000000000snakemake-5.10.0/tests/test_globwildcards/test.0.txt000066400000000000000000000000001361131222100224110ustar00rootroot00000000000000snakemake-5.10.0/tests/test_globwildcards/test.1.txt000066400000000000000000000000001361131222100224120ustar00rootroot00000000000000snakemake-5.10.0/tests/test_globwildcards/test.2.txt000066400000000000000000000000001361131222100224130ustar00rootroot00000000000000snakemake-5.10.0/tests/test_group_job_fail/000077500000000000000000000000001361131222100207065ustar00rootroot00000000000000snakemake-5.10.0/tests/test_group_job_fail/Snakefile000066400000000000000000000007021361131222100225310ustar00rootroot00000000000000samples = [1,2,3,4,5] rule all: input: "test.out" rule a: output: "a/{sample}.out" group: 0 shell: "touch {output}" rule b: input: "a/{sample}.out" output: "b/{sample}.out" group: 0 shell: "touch {output}; exit 1" rule c: input: expand("b/{sample}.out", sample=samples) output: "test.out" group: 1 shell: "touch {output}" snakemake-5.10.0/tests/test_group_job_fail/expected-results/000077500000000000000000000000001361131222100242065ustar00rootroot00000000000000snakemake-5.10.0/tests/test_group_job_fail/expected-results/.gitignore000066400000000000000000000000001361131222100261640ustar00rootroot00000000000000snakemake-5.10.0/tests/test_group_jobs/000077500000000000000000000000001361131222100200765ustar00rootroot00000000000000snakemake-5.10.0/tests/test_group_jobs/Snakefile000066400000000000000000000006721361131222100217270ustar00rootroot00000000000000samples = [1,2,3,4,5] rule all: input: "test.out" rule a: output: "a/{sample}.out" group: 0 shell: "touch {output}" rule b: input: "a/{sample}.out" output: "b/{sample}.out" group: 0 shell: "touch {output}" rule c: input: expand("b/{sample}.out", sample=samples) output: "test.out" group: 1 shell: "touch {output}" snakemake-5.10.0/tests/test_group_jobs/expected-results/000077500000000000000000000000001361131222100233765ustar00rootroot00000000000000snakemake-5.10.0/tests/test_group_jobs/expected-results/test.out000066400000000000000000000000001361131222100250740ustar00rootroot00000000000000snakemake-5.10.0/tests/test_group_jobs/qsub000077500000000000000000000002001361131222100207660ustar00rootroot00000000000000#!/bin/bash echo `date` >> qsub.log tail -n1 $1 >> qsub.log # simulate printing of job id by a random number echo $RANDOM sh $1 snakemake-5.10.0/tests/test_gs_requester_pays/000077500000000000000000000000001361131222100214715ustar00rootroot00000000000000snakemake-5.10.0/tests/test_gs_requester_pays/Snakefile000066400000000000000000000007151361131222100233200ustar00rootroot00000000000000from snakemake.remote import GS import google.auth try: GS = GS.RemoteProvider() rule copy: input: GS.remote(config["url"], user_project=config["project"]) output: "landsat-data.txt" shell: "cp {input} {output}" except google.auth.exceptions.DefaultCredentialsError: # ignore the test if not authenticated print("skipping test_remote_gs because we are not authenticated with gcloud") snakemake-5.10.0/tests/test_gs_requester_pays/expected-results/000077500000000000000000000000001361131222100247715ustar00rootroot00000000000000snakemake-5.10.0/tests/test_gs_requester_pays/expected-results/landsat-data.txt000066400000000000000000000203761361131222100300770ustar00rootroot00000000000000GROUP = L1_METADATA_FILE GROUP = METADATA_FILE_INFO ORIGIN = "Image courtesy of the U.S. Geological Survey" REQUEST_ID = "0501705013406_00001" LANDSAT_SCENE_ID = "LC80010032017120LGN00" LANDSAT_PRODUCT_ID = "LC08_L1GT_001003_20170430_20170501_01_RT" COLLECTION_NUMBER = 01 FILE_DATE = 2017-05-01T16:00:24Z STATION_ID = "LGN" PROCESSING_SOFTWARE_VERSION = "LPGS_2.7.0" END_GROUP = METADATA_FILE_INFO GROUP = PRODUCT_METADATA DATA_TYPE = "L1GT" COLLECTION_CATEGORY = "RT" ELEVATION_SOURCE = "GLS2000" OUTPUT_FORMAT = "GEOTIFF" SPACECRAFT_ID = "LANDSAT_8" SENSOR_ID = "OLI_TIRS" WRS_PATH = 1 WRS_ROW = 3 NADIR_OFFNADIR = "NADIR" TARGET_WRS_PATH = 1 TARGET_WRS_ROW = 3 DATE_ACQUIRED = 2017-04-30 SCENE_CENTER_TIME = "14:07:16.5180850Z" CORNER_UL_LAT_PRODUCT = 80.21528 CORNER_UL_LON_PRODUCT = -17.96312 CORNER_UR_LAT_PRODUCT = 80.28798 CORNER_UR_LON_PRODUCT = -3.45901 CORNER_LL_LAT_PRODUCT = 77.79053 CORNER_LL_LON_PRODUCT = -16.19251 CORNER_LR_LAT_PRODUCT = 77.84841 CORNER_LR_LON_PRODUCT = -4.56164 CORNER_UL_PROJECTION_X_PRODUCT = 330600.000 CORNER_UL_PROJECTION_Y_PRODUCT = 8918700.000 CORNER_UR_PROJECTION_X_PRODUCT = 604200.000 CORNER_UR_PROJECTION_Y_PRODUCT = 8918700.000 CORNER_LL_PROJECTION_X_PRODUCT = 330600.000 CORNER_LL_PROJECTION_Y_PRODUCT = 8645400.000 CORNER_LR_PROJECTION_X_PRODUCT = 604200.000 CORNER_LR_PROJECTION_Y_PRODUCT = 8645400.000 PANCHROMATIC_LINES = 18221 PANCHROMATIC_SAMPLES = 18241 REFLECTIVE_LINES = 9111 REFLECTIVE_SAMPLES = 9121 THERMAL_LINES = 9111 THERMAL_SAMPLES = 9121 FILE_NAME_BAND_1 = "LC08_L1GT_001003_20170430_20170501_01_RT_B1.TIF" FILE_NAME_BAND_2 = "LC08_L1GT_001003_20170430_20170501_01_RT_B2.TIF" FILE_NAME_BAND_3 = "LC08_L1GT_001003_20170430_20170501_01_RT_B3.TIF" FILE_NAME_BAND_4 = "LC08_L1GT_001003_20170430_20170501_01_RT_B4.TIF" FILE_NAME_BAND_5 = "LC08_L1GT_001003_20170430_20170501_01_RT_B5.TIF" FILE_NAME_BAND_6 = "LC08_L1GT_001003_20170430_20170501_01_RT_B6.TIF" FILE_NAME_BAND_7 = "LC08_L1GT_001003_20170430_20170501_01_RT_B7.TIF" FILE_NAME_BAND_8 = "LC08_L1GT_001003_20170430_20170501_01_RT_B8.TIF" FILE_NAME_BAND_9 = "LC08_L1GT_001003_20170430_20170501_01_RT_B9.TIF" FILE_NAME_BAND_10 = "LC08_L1GT_001003_20170430_20170501_01_RT_B10.TIF" FILE_NAME_BAND_11 = "LC08_L1GT_001003_20170430_20170501_01_RT_B11.TIF" FILE_NAME_BAND_QUALITY = "LC08_L1GT_001003_20170430_20170501_01_RT_BQA.TIF" ANGLE_COEFFICIENT_FILE_NAME = "LC08_L1GT_001003_20170430_20170501_01_RT_ANG.txt" METADATA_FILE_NAME = "LC08_L1GT_001003_20170430_20170501_01_RT_MTL.txt" CPF_NAME = "LC08CPF_20170401_20170630_01.02" BPF_NAME_OLI = "LO8BPF20170430140614_20170430144404.01" BPF_NAME_TIRS = "LT8BPF20170426235522_20170427000359.01" RLUT_FILE_NAME = "LC08RLUT_20150303_20431231_01_12.h5" END_GROUP = PRODUCT_METADATA GROUP = IMAGE_ATTRIBUTES CLOUD_COVER = 24.32 CLOUD_COVER_LAND = -1 IMAGE_QUALITY_OLI = 9 IMAGE_QUALITY_TIRS = 7 TIRS_SSM_MODEL = "PRELIMINARY" TIRS_SSM_POSITION_STATUS = "ESTIMATED" TIRS_STRAY_LIGHT_CORRECTION_SOURCE = "TIRS" ROLL_ANGLE = -0.001 SUN_AZIMUTH = -156.47580997 SUN_ELEVATION = 24.99099132 EARTH_SUN_DISTANCE = 1.0074392 SATURATION_BAND_1 = "N" SATURATION_BAND_2 = "N" SATURATION_BAND_3 = "N" SATURATION_BAND_4 = "N" SATURATION_BAND_5 = "N" SATURATION_BAND_6 = "N" SATURATION_BAND_7 = "N" SATURATION_BAND_8 = "N" SATURATION_BAND_9 = "N" TRUNCATION_OLI = "UPPER" END_GROUP = IMAGE_ATTRIBUTES GROUP = MIN_MAX_RADIANCE RADIANCE_MAXIMUM_BAND_1 = 748.87909 RADIANCE_MINIMUM_BAND_1 = -61.84268 RADIANCE_MAXIMUM_BAND_2 = 766.86133 RADIANCE_MINIMUM_BAND_2 = -63.32766 RADIANCE_MAXIMUM_BAND_3 = 706.65613 RADIANCE_MINIMUM_BAND_3 = -58.35589 RADIANCE_MAXIMUM_BAND_4 = 595.89227 RADIANCE_MINIMUM_BAND_4 = -49.20898 RADIANCE_MAXIMUM_BAND_5 = 364.65634 RADIANCE_MINIMUM_BAND_5 = -30.11344 RADIANCE_MAXIMUM_BAND_6 = 90.68671 RADIANCE_MINIMUM_BAND_6 = -7.48894 RADIANCE_MAXIMUM_BAND_7 = 30.56628 RADIANCE_MINIMUM_BAND_7 = -2.52417 RADIANCE_MAXIMUM_BAND_8 = 674.38605 RADIANCE_MINIMUM_BAND_8 = -55.69102 RADIANCE_MAXIMUM_BAND_9 = 142.51598 RADIANCE_MINIMUM_BAND_9 = -11.76902 RADIANCE_MAXIMUM_BAND_10 = 22.00180 RADIANCE_MINIMUM_BAND_10 = 0.10033 RADIANCE_MAXIMUM_BAND_11 = 22.00180 RADIANCE_MINIMUM_BAND_11 = 0.10033 END_GROUP = MIN_MAX_RADIANCE GROUP = MIN_MAX_REFLECTANCE REFLECTANCE_MAXIMUM_BAND_1 = 1.210700 REFLECTANCE_MINIMUM_BAND_1 = -0.099980 REFLECTANCE_MAXIMUM_BAND_2 = 1.210700 REFLECTANCE_MINIMUM_BAND_2 = -0.099980 REFLECTANCE_MAXIMUM_BAND_3 = 1.210700 REFLECTANCE_MINIMUM_BAND_3 = -0.099980 REFLECTANCE_MAXIMUM_BAND_4 = 1.210700 REFLECTANCE_MINIMUM_BAND_4 = -0.099980 REFLECTANCE_MAXIMUM_BAND_5 = 1.210700 REFLECTANCE_MINIMUM_BAND_5 = -0.099980 REFLECTANCE_MAXIMUM_BAND_6 = 1.210700 REFLECTANCE_MINIMUM_BAND_6 = -0.099980 REFLECTANCE_MAXIMUM_BAND_7 = 1.210700 REFLECTANCE_MINIMUM_BAND_7 = -0.099980 REFLECTANCE_MAXIMUM_BAND_8 = 1.210700 REFLECTANCE_MINIMUM_BAND_8 = -0.099980 REFLECTANCE_MAXIMUM_BAND_9 = 1.210700 REFLECTANCE_MINIMUM_BAND_9 = -0.099980 END_GROUP = MIN_MAX_REFLECTANCE GROUP = MIN_MAX_PIXEL_VALUE QUANTIZE_CAL_MAX_BAND_1 = 65535 QUANTIZE_CAL_MIN_BAND_1 = 1 QUANTIZE_CAL_MAX_BAND_2 = 65535 QUANTIZE_CAL_MIN_BAND_2 = 1 QUANTIZE_CAL_MAX_BAND_3 = 65535 QUANTIZE_CAL_MIN_BAND_3 = 1 QUANTIZE_CAL_MAX_BAND_4 = 65535 QUANTIZE_CAL_MIN_BAND_4 = 1 QUANTIZE_CAL_MAX_BAND_5 = 65535 QUANTIZE_CAL_MIN_BAND_5 = 1 QUANTIZE_CAL_MAX_BAND_6 = 65535 QUANTIZE_CAL_MIN_BAND_6 = 1 QUANTIZE_CAL_MAX_BAND_7 = 65535 QUANTIZE_CAL_MIN_BAND_7 = 1 QUANTIZE_CAL_MAX_BAND_8 = 65535 QUANTIZE_CAL_MIN_BAND_8 = 1 QUANTIZE_CAL_MAX_BAND_9 = 65535 QUANTIZE_CAL_MIN_BAND_9 = 1 QUANTIZE_CAL_MAX_BAND_10 = 65535 QUANTIZE_CAL_MIN_BAND_10 = 1 QUANTIZE_CAL_MAX_BAND_11 = 65535 QUANTIZE_CAL_MIN_BAND_11 = 1 END_GROUP = MIN_MAX_PIXEL_VALUE GROUP = RADIOMETRIC_RESCALING RADIANCE_MULT_BAND_1 = 1.2371E-02 RADIANCE_MULT_BAND_2 = 1.2668E-02 RADIANCE_MULT_BAND_3 = 1.1674E-02 RADIANCE_MULT_BAND_4 = 9.8438E-03 RADIANCE_MULT_BAND_5 = 6.0239E-03 RADIANCE_MULT_BAND_6 = 1.4981E-03 RADIANCE_MULT_BAND_7 = 5.0494E-04 RADIANCE_MULT_BAND_8 = 1.1140E-02 RADIANCE_MULT_BAND_9 = 2.3543E-03 RADIANCE_MULT_BAND_10 = 3.3420E-04 RADIANCE_MULT_BAND_11 = 3.3420E-04 RADIANCE_ADD_BAND_1 = -61.85505 RADIANCE_ADD_BAND_2 = -63.34032 RADIANCE_ADD_BAND_3 = -58.36757 RADIANCE_ADD_BAND_4 = -49.21882 RADIANCE_ADD_BAND_5 = -30.11946 RADIANCE_ADD_BAND_6 = -7.49044 RADIANCE_ADD_BAND_7 = -2.52468 RADIANCE_ADD_BAND_8 = -55.70216 RADIANCE_ADD_BAND_9 = -11.77137 RADIANCE_ADD_BAND_10 = 0.10000 RADIANCE_ADD_BAND_11 = 0.10000 REFLECTANCE_MULT_BAND_1 = 2.0000E-05 REFLECTANCE_MULT_BAND_2 = 2.0000E-05 REFLECTANCE_MULT_BAND_3 = 2.0000E-05 REFLECTANCE_MULT_BAND_4 = 2.0000E-05 REFLECTANCE_MULT_BAND_5 = 2.0000E-05 REFLECTANCE_MULT_BAND_6 = 2.0000E-05 REFLECTANCE_MULT_BAND_7 = 2.0000E-05 REFLECTANCE_MULT_BAND_8 = 2.0000E-05 REFLECTANCE_MULT_BAND_9 = 2.0000E-05 REFLECTANCE_ADD_BAND_1 = -0.100000 REFLECTANCE_ADD_BAND_2 = -0.100000 REFLECTANCE_ADD_BAND_3 = -0.100000 REFLECTANCE_ADD_BAND_4 = -0.100000 REFLECTANCE_ADD_BAND_5 = -0.100000 REFLECTANCE_ADD_BAND_6 = -0.100000 REFLECTANCE_ADD_BAND_7 = -0.100000 REFLECTANCE_ADD_BAND_8 = -0.100000 REFLECTANCE_ADD_BAND_9 = -0.100000 END_GROUP = RADIOMETRIC_RESCALING GROUP = TIRS_THERMAL_CONSTANTS K1_CONSTANT_BAND_10 = 774.8853 K2_CONSTANT_BAND_10 = 1321.0789 K1_CONSTANT_BAND_11 = 480.8883 K2_CONSTANT_BAND_11 = 1201.1442 END_GROUP = TIRS_THERMAL_CONSTANTS GROUP = PROJECTION_PARAMETERS MAP_PROJECTION = "UTM" DATUM = "WGS84" ELLIPSOID = "WGS84" UTM_ZONE = 29 GRID_CELL_SIZE_PANCHROMATIC = 15.00 GRID_CELL_SIZE_REFLECTIVE = 30.00 GRID_CELL_SIZE_THERMAL = 30.00 ORIENTATION = "NORTH_UP" RESAMPLING_OPTION = "CUBIC_CONVOLUTION" END_GROUP = PROJECTION_PARAMETERS END_GROUP = L1_METADATA_FILE END snakemake-5.10.0/tests/test_inoutput_is_path/000077500000000000000000000000001361131222100213235ustar00rootroot00000000000000snakemake-5.10.0/tests/test_inoutput_is_path/Snakefile000066400000000000000000000005111361131222100231440ustar00rootroot00000000000000from pathlib import Path rule: input: Path("test.in").resolve() # absolute, must exist output: Path("test.out") # relative, does not have to exist (yet) run: test = shell("echo 42;", read=True) assert int(test) == 42 with open(output[0], "w") as f: for l in shell("cat {input}", iterable=True): print(l, file=f) snakemake-5.10.0/tests/test_inoutput_is_path/expected-results/000077500000000000000000000000001361131222100246235ustar00rootroot00000000000000snakemake-5.10.0/tests/test_inoutput_is_path/expected-results/test.out000066400000000000000000000000101361131222100263220ustar00rootroot00000000000000foo bar snakemake-5.10.0/tests/test_inoutput_is_path/test.in000066400000000000000000000000101361131222100226210ustar00rootroot00000000000000foo bar snakemake-5.10.0/tests/test_inoutput_is_path/test.out000066400000000000000000000000101361131222100230220ustar00rootroot00000000000000foo bar snakemake-5.10.0/tests/test_input_generator/000077500000000000000000000000001361131222100211325ustar00rootroot00000000000000snakemake-5.10.0/tests/test_input_generator/Snakefile000066400000000000000000000014631361131222100227620ustar00rootroot00000000000000# What if an input function returns a generator rather than a list? # Pythonically, generators are preferred to lists. #This always worked fine: def input_func1(wildcards): return [ "%s.%d.in" % (wildcards.base, n) for n in range(1,4) ] #This fails: def input_func2(wildcards): return ( "%s.%d.in" % (wildcards.base, n) for n in range(1,4) ) #As does this def input_func3(wildcards): for n in range(1,4): yield "%s.%d.in" % (wildcards.base, n) rule main: input: "foo.out1", "foo.out2", "foo.out3" rule test1: output: "{base}.out1" input: input_func1 shell: "cat {input} > {output}" rule test2: output: "{base}.out2" input: input_func2 shell: "cat {input} > {output}" rule test3: output: "{base}.out3" input: input_func3 shell: "cat {input} > {output}" snakemake-5.10.0/tests/test_input_generator/expected-results/000077500000000000000000000000001361131222100244325ustar00rootroot00000000000000snakemake-5.10.0/tests/test_input_generator/expected-results/foo.out1000066400000000000000000000000061361131222100260230ustar00rootroot000000000000001 2 3 snakemake-5.10.0/tests/test_input_generator/expected-results/foo.out2000066400000000000000000000000061361131222100260240ustar00rootroot000000000000001 2 3 snakemake-5.10.0/tests/test_input_generator/expected-results/foo.out3000066400000000000000000000000061361131222100260250ustar00rootroot000000000000001 2 3 snakemake-5.10.0/tests/test_input_generator/foo.1.in000066400000000000000000000000021361131222100223740ustar00rootroot000000000000001 snakemake-5.10.0/tests/test_input_generator/foo.2.in000066400000000000000000000000021361131222100223750ustar00rootroot000000000000002 snakemake-5.10.0/tests/test_input_generator/foo.3.in000066400000000000000000000000021361131222100223760ustar00rootroot000000000000003 snakemake-5.10.0/tests/test_io.py000066400000000000000000000065251361131222100167160ustar00rootroot00000000000000from snakemake.io import _wildcard_regex, expand from snakemake.exceptions import WildcardError def test_wildcard_regex(): def matches(text): return [ (match.group("name"), match.group("constraint")) for match in _wildcard_regex.finditer(text) ] # without constraints assert matches("") == [] assert matches("{") == [] assert matches("}") == [] assert matches("{}") == [] assert matches("{0}") == [("0", None)] assert matches("{abc}") == [("abc", None)] assert matches("abc{def}{ghi}") == [("def", None), ("ghi", None)] # with constraints assert matches("{w,constraint}") == [("w", "constraint")] assert matches("{w , constraint}") == [("w", "constraint")] # fails because constraint is detected as 'constraint ' # assert matches('{w,constraint }') == [('w', 'constraint')] assert matches("abc { w , constraint} def") == [("w", "constraint")] # multiple wildcards assert matches("{a,1} {b,2} {c,3}") == [("a", "1"), ("b", "2"), ("c", "3")] # more complicated constraints assert matches(r"{w,([a-z]+|pat\|t*ern)}") == [("w", r"([a-z]+|pat\|t*ern)")] assert matches(r"{w,([a-z]+|pat\|te{1,3}rn){5,7}}") == [ ("w", r"([a-z]+|pat\|te{1,3}rn){5,7}") ] # This used to be very slow with an older version of the regex assert matches("{w, long constraint without closing brace") == [] def test_expand(): wildcards = {"a": [1, 2], "b": [3, 4], "c": [5]} # each provided wildcard is used in the filepattern assert sorted(expand("{a}{b}{c}", **wildcards)) == sorted( ["135", "145", "235", "245"] ) # redundant wildcards are provided assert sorted(expand("{a}{c}", **wildcards)) == sorted(["15", "25"]) # missing wildcards (should fail) try: expand("{a}{d}", **wildcards) assert False except WildcardError: pass # do not expand on strings and non iterables assert expand("{x}{y}", **{"x": "Hello, ", "y": "world!"}) == ["Hello, world!"] assert expand("{x}{y}", **{"x": 4, "y": 2}) == ["42"] # format-minilang: field names assert sorted( expand("first letter of sample: {samples[0]}", samples=["A123", "B456", "C789"]) ) == sorted( [ "first letter of sample: A", "first letter of sample: B", "first letter of sample: C", ] ) assert expand("{str.__class__}", str="") == [""] # format-minilang: conversions class ConvTest: def __str__(self): return "string" def __repr__(self): return "representation" assert expand("{test!r}", test=ConvTest()) == ["representation"] assert expand("{test!s}", test=ConvTest()) == ["string"] # format-minilang: format specifications assert sorted( expand( "The answer to life, the universe, and everything: {answer:f}", answer=range(41, 43), ) ) == sorted( [ "The answer to life, the universe, and everything: 41.000000", "The answer to life, the universe, and everything: 42.000000", ] ) # multiple filepatterns with different wildcards assert sorted( expand(["a: {a} + b: {b}", "c: {c}"], a="aa", b=["b", "bb"], c=["c", "cc"]) ) == sorted(["a: aa + b: b", "a: aa + b: bb", "c: c", "c: cc"]) snakemake-5.10.0/tests/test_issue1037/000077500000000000000000000000001361131222100173705ustar00rootroot00000000000000snakemake-5.10.0/tests/test_issue1037/Foo_A.start000066400000000000000000000000001361131222100214200ustar00rootroot00000000000000snakemake-5.10.0/tests/test_issue1037/Snakefile000066400000000000000000000006501361131222100212150ustar00rootroot00000000000000ruleorder: done2 > done1 rule step1: input: '{sample}.start' output: '{sample}.step1' group: 'mygroup' shell: 'touch {output}' rule done1: input: '{sample}.step1' output: '{sample}.done' group: 'mygroup' shell: 'touch {output}' rule done2: input: '{sample}.step1' output: '{sample}.done' wildcard_constraints: sample = 'Foo_.+' group: 'mygroup' shell: 'touch {output}' snakemake-5.10.0/tests/test_issue1037/expected-results/000077500000000000000000000000001361131222100226705ustar00rootroot00000000000000snakemake-5.10.0/tests/test_issue1037/expected-results/.gitignore000066400000000000000000000000001361131222100246460ustar00rootroot00000000000000snakemake-5.10.0/tests/test_issue1037/qsub000077500000000000000000000002231361131222100202650ustar00rootroot00000000000000#!/bin/bash echo `date` >> qsub.log tail -n1 $1 >> qsub.log # simulate printing of job id by a random number echo $RANDOM cat $1 >> qsub.log sh $1 snakemake-5.10.0/tests/test_issue1041/000077500000000000000000000000001361131222100173635ustar00rootroot00000000000000snakemake-5.10.0/tests/test_issue1041/Snakefile000066400000000000000000000007471361131222100212170ustar00rootroot00000000000000CHUNKS = range(3) rule all: input: expand('raw.split_{chunk}.txt', chunk=CHUNKS) rule start: group: 'group1' output: 'raw.txt' shell: 'echo "hi" > {output}' rule split: input: txt='raw.txt' output: expand('raw.split_{chunk}.txt', chunk=CHUNKS) group: 'group1' shell: ''' sleep 3 echo 0 > {output[0]} echo 1 > {output[1]} echo 2 > {output[2]} ''' snakemake-5.10.0/tests/test_issue1041/expected-results/000077500000000000000000000000001361131222100226635ustar00rootroot00000000000000snakemake-5.10.0/tests/test_issue1041/expected-results/raw.split_0.txt000066400000000000000000000000021361131222100255560ustar00rootroot000000000000000 snakemake-5.10.0/tests/test_issue1041/expected-results/raw.split_1.txt000066400000000000000000000000021361131222100255570ustar00rootroot000000000000001 snakemake-5.10.0/tests/test_issue1041/expected-results/raw.split_2.txt000066400000000000000000000000021361131222100255600ustar00rootroot000000000000002 snakemake-5.10.0/tests/test_issue1046/000077500000000000000000000000001361131222100173705ustar00rootroot00000000000000snakemake-5.10.0/tests/test_issue1046/Snakefile000066400000000000000000000004311361131222100212120ustar00rootroot00000000000000rule all: input: "test_report.html" rule test: input: "{name}.csv" output: "{name}_report.html" params: # DOES NOT WORK! title = lambda wildcards, input: input[0] # WORKS!! # title = lambda wildcards: wildcards.name wrapper: "file:my_wrapper" snakemake-5.10.0/tests/test_issue1046/expected-results/000077500000000000000000000000001361131222100226705ustar00rootroot00000000000000snakemake-5.10.0/tests/test_issue1046/expected-results/test_report.html000066400000000000000000000000111361131222100261200ustar00rootroot00000000000000test.csv snakemake-5.10.0/tests/test_issue1046/my_wrapper/000077500000000000000000000000001361131222100215555ustar00rootroot00000000000000snakemake-5.10.0/tests/test_issue1046/my_wrapper/wrapper.py000066400000000000000000000001521361131222100236050ustar00rootroot00000000000000from snakemake import shell shell("echo {} > {}".format(snakemake.params['title'], snakemake.output[0])) snakemake-5.10.0/tests/test_issue1046/test.csv000066400000000000000000000000001361131222100210520ustar00rootroot00000000000000snakemake-5.10.0/tests/test_issue1083/000077500000000000000000000000001361131222100173715ustar00rootroot00000000000000snakemake-5.10.0/tests/test_issue1083/Snakefile000066400000000000000000000003421361131222100212140ustar00rootroot00000000000000rule: output: "foo.txt" input: "bar.txt" singularity: "docker://bash" shadow: "minimal" shell: "mount; " "pwd; " "ls -l {input}; " "cat {input} > {output}" snakemake-5.10.0/tests/test_issue1083/bar.txt000066400000000000000000000000001361131222100206640ustar00rootroot00000000000000snakemake-5.10.0/tests/test_issue1083/expected-results/000077500000000000000000000000001361131222100226715ustar00rootroot00000000000000snakemake-5.10.0/tests/test_issue1083/expected-results/foo.txt000066400000000000000000000000001361131222100242030ustar00rootroot00000000000000snakemake-5.10.0/tests/test_issue1085/000077500000000000000000000000001361131222100173735ustar00rootroot00000000000000snakemake-5.10.0/tests/test_issue1085/Snakefile000066400000000000000000000002421361131222100212150ustar00rootroot00000000000000def get_params(wildcards): return {'test': 'oo', 'norm': 'oo'} rule test: output: "aa" params: unpack(get_params) shell: "echo {params}" snakemake-5.10.0/tests/test_issue1085/expected-results/000077500000000000000000000000001361131222100226735ustar00rootroot00000000000000snakemake-5.10.0/tests/test_issue1085/expected-results/.gitignore000066400000000000000000000000001361131222100246510ustar00rootroot00000000000000snakemake-5.10.0/tests/test_issue1092/000077500000000000000000000000001361131222100173715ustar00rootroot00000000000000snakemake-5.10.0/tests/test_issue1092/Snakefile000066400000000000000000000017341361131222100212220ustar00rootroot00000000000000# a target rule to define the desired final output rule all: input: "aggregated.txt", # the checkpoint that shall trigger re-evaluation of the DAG checkpoint clustering: output: clusters=directory("clustering") shell: "mkdir clustering; " "for i in 1 2 3; do echo $i > clustering/$i.txt; done" def aggregate_input(wildcards): checkpoint_output = checkpoints.clustering.get(**wildcards).output[0] print("beyond") return sorted( expand("post/{i}.txt", i=glob_wildcards(os.path.join(checkpoint_output, "{i}.txt")).i) ) # an aggregation over all produced clusters rule aggregate: input: aggregate_input output: "aggregated.txt" #shell: # "cat {input} > {output}" run: shell("cat {input} > {output}") # an intermediate rule rule intermediate: input: "clustering/{i}.txt" output: "post/{i}.txt" shell: "cp {input} {output}" snakemake-5.10.0/tests/test_issue1092/expected-results/000077500000000000000000000000001361131222100226715ustar00rootroot00000000000000snakemake-5.10.0/tests/test_issue1092/expected-results/aggregated.txt000066400000000000000000000000061361131222100255200ustar00rootroot000000000000001 2 3 snakemake-5.10.0/tests/test_issue1093/000077500000000000000000000000001361131222100173725ustar00rootroot00000000000000snakemake-5.10.0/tests/test_issue1093/Snakefile000066400000000000000000000017001361131222100212140ustar00rootroot00000000000000# a target rule to define the desired final output rule all: input: "aggregated.txt", # the checkpoint that shall trigger re-evaluation of the DAG checkpoint clustering: output: clusters=directory("clustering") shell: "mkdir clustering; " "for i in 1 2 3; do echo $i > clustering/$i.txt; done" def aggregate_input(wildcards): checkpoint_output = checkpoints.clustering.get(**wildcards).output[0] return expand("post/{i}.txt", i=sorted(glob_wildcards(os.path.join(checkpoint_output, "{i}.txt")).i)) # an aggregation over all produced clusters rule aggregate: input: aggregate_input output: "aggregated.txt" shell: "cat {input} > {output}" # an intermediate rule rule intermediate: input: "clustering/{i}.txt" output: "post/{i}.txt" conda: "condaenv.yaml" shell: "which bwa; " "cp {input} {output}" snakemake-5.10.0/tests/test_issue1093/condaenv.yaml000066400000000000000000000001031361131222100220450ustar00rootroot00000000000000channels: - conda-forge - bioconda dependencies: - bwa snakemake-5.10.0/tests/test_issue1093/expected-results/000077500000000000000000000000001361131222100226725ustar00rootroot00000000000000snakemake-5.10.0/tests/test_issue1093/expected-results/aggregated.txt000066400000000000000000000000061361131222100255210ustar00rootroot000000000000001 2 3 snakemake-5.10.0/tests/test_issue1281/000077500000000000000000000000001361131222100173715ustar00rootroot00000000000000snakemake-5.10.0/tests/test_issue1281/Snakefile000066400000000000000000000010461361131222100212160ustar00rootroot00000000000000# using dictionary expansion mydictionary={ 'apple': 'crunchy fruit', 'banana': 'mushy and yellow' } rule all: input: expand('{key}.sh', key=mydictionary.keys()) rule test: output: temp('{f}.txt') params: keyval=lambda wildcards: mydictionary[wildcards.f] shell: """ echo {params.keyval} > {output} cat {output} """ rule test2: input: rules.test.output output: '{f}.sh' shell: "touch {output}" rule checkme: input: expand(rules.test2.output, f=mydictionary.keys()) snakemake-5.10.0/tests/test_issue1281/expected-results/000077500000000000000000000000001361131222100226715ustar00rootroot00000000000000snakemake-5.10.0/tests/test_issue1281/expected-results/apple.sh000066400000000000000000000000001361131222100243140ustar00rootroot00000000000000snakemake-5.10.0/tests/test_issue1281/expected-results/banana.sh000066400000000000000000000000001361131222100244330ustar00rootroot00000000000000snakemake-5.10.0/tests/test_issue1284/000077500000000000000000000000001361131222100173745ustar00rootroot00000000000000snakemake-5.10.0/tests/test_issue1284/Snakefile000066400000000000000000000014531361131222100212230ustar00rootroot00000000000000rule all: input: 'result.r1', 'result.c1', # targeting checkpoint output overrides input 'result.c2' def rule1_input(wc): checkpoints.check1.get(**wc).output[0] return "result.r2" rule r1: input: rule1_input output: 'result.r1', shell: 'echo {input} > {output}' rule r2: output: 'result.r2' shell: 'echo r2 > {output}' def check1_input(wc): checkpoints.check2.get(**wc).output[0] return 'result.r3' checkpoint check1: input: check1_input output: 'result.c1' shell: 'echo c1 > {output}' checkpoint check2: output: 'result.c2' shell: 'echo c2 > {output}' rule r3: output: 'result.r3' shell: 'echo r3 > {output}' snakemake-5.10.0/tests/test_issue1284/expected-results/000077500000000000000000000000001361131222100226745ustar00rootroot00000000000000snakemake-5.10.0/tests/test_issue1284/expected-results/result.c1000066400000000000000000000000031361131222100244300ustar00rootroot00000000000000c1 snakemake-5.10.0/tests/test_issue1284/expected-results/result.c2000066400000000000000000000000031361131222100244310ustar00rootroot00000000000000c2 snakemake-5.10.0/tests/test_issue1284/expected-results/result.r1000066400000000000000000000000121361131222100244470ustar00rootroot00000000000000result.r2 snakemake-5.10.0/tests/test_issue1284/expected-results/result.r2000066400000000000000000000000031361131222100244500ustar00rootroot00000000000000r2 snakemake-5.10.0/tests/test_issue1284/expected-results/result.r3000066400000000000000000000000031361131222100244510ustar00rootroot00000000000000r3 snakemake-5.10.0/tests/test_issue260/000077500000000000000000000000001361131222100173055ustar00rootroot00000000000000snakemake-5.10.0/tests/test_issue260/Snakefile000066400000000000000000000010311361131222100211240ustar00rootroot00000000000000rule all: input: 'output/result.n3', output: 'output/done.txt', shell: 'echo all >> {output}' rule n3: input: dynamic("output/{id2}.n2"), output: "output/result.n3", shell: 'echo n3 > {output}' rule n2: input: dyn=dynamic("output/{id1}.n1"), output: dynamic("output/{id2}.n2"), shell: 'echo n2 > output/result.n2' rule n1: output: dyn=dynamic("output/{id1}.n1"), shell: 'echo n1 > output/result.n1' snakemake-5.10.0/tests/test_issue260/expected-results/000077500000000000000000000000001361131222100226055ustar00rootroot00000000000000snakemake-5.10.0/tests/test_issue260/expected-results/output/000077500000000000000000000000001361131222100241455ustar00rootroot00000000000000snakemake-5.10.0/tests/test_issue260/expected-results/output/done.txt000066400000000000000000000000041361131222100256250ustar00rootroot00000000000000all snakemake-5.10.0/tests/test_issue260/expected-results/output/result.n1000066400000000000000000000000031361131222100257140ustar00rootroot00000000000000n1 snakemake-5.10.0/tests/test_issue260/expected-results/output/result.n2000066400000000000000000000000031361131222100257150ustar00rootroot00000000000000n2 snakemake-5.10.0/tests/test_issue260/expected-results/output/result.n3000066400000000000000000000000031361131222100257160ustar00rootroot00000000000000n3 snakemake-5.10.0/tests/test_issue328/000077500000000000000000000000001361131222100173125ustar00rootroot00000000000000snakemake-5.10.0/tests/test_issue328/Snakefile000066400000000000000000000007711361131222100211430ustar00rootroot00000000000000from pytools.persistent_dict import PersistentDict storage = PersistentDict("storage") rule merge: input: dynamic("in_{sample}.txt") output: "out.txt" shell: "touch {output}" storage["split_counter"] = 0 rule split: input: "in.txt" output: dynamic("in_{sample}.txt") run: if storage["split_counter"] > 0: raise Exception("Rule split was executed multiple times.") storage["split_counter"] += 1 shell("touch in_1.txt in_2.txt") snakemake-5.10.0/tests/test_issue328/expected-results/000077500000000000000000000000001361131222100226125ustar00rootroot00000000000000snakemake-5.10.0/tests/test_issue328/expected-results/out.txt000066400000000000000000000000001361131222100241500ustar00rootroot00000000000000snakemake-5.10.0/tests/test_issue328/in.txt000066400000000000000000000000001361131222100204470ustar00rootroot00000000000000snakemake-5.10.0/tests/test_issue381/000077500000000000000000000000001361131222100173115ustar00rootroot00000000000000snakemake-5.10.0/tests/test_issue381/Snakefile000066400000000000000000000003641361131222100211400ustar00rootroot00000000000000 rule all: input: "b.out" rule a: input: "a.in" output: "a.out" shell: "touch {output}" rule b: input: rules.a.input output: "b.out" shell: "touch {output}" snakemake-5.10.0/tests/test_issue381/a.in000066400000000000000000000000001361131222100200470ustar00rootroot00000000000000snakemake-5.10.0/tests/test_issue381/expected-results/000077500000000000000000000000001361131222100226115ustar00rootroot00000000000000snakemake-5.10.0/tests/test_issue381/expected-results/b.out000066400000000000000000000000001361131222100235510ustar00rootroot00000000000000snakemake-5.10.0/tests/test_issue471/000077500000000000000000000000001361131222100173115ustar00rootroot00000000000000snakemake-5.10.0/tests/test_issue471/Snakefile000066400000000000000000000004611361131222100211360ustar00rootroot00000000000000rule all: input: "test1.2.out" def process_params(wildcards) : e,a = wildcards.ea.split(".") return { 'epsilon' : '0' + e, 'alpha' : '0.' + a } rule a: output: "test{ea}.out" params: p=process_params shell: "echo {params.p[epsilon]} > {output}" snakemake-5.10.0/tests/test_issue471/expected-results/000077500000000000000000000000001361131222100226115ustar00rootroot00000000000000snakemake-5.10.0/tests/test_issue471/expected-results/test1.2.out000066400000000000000000000000031361131222100245330ustar00rootroot0000000000000001 snakemake-5.10.0/tests/test_issue584/000077500000000000000000000000001361131222100173165ustar00rootroot00000000000000snakemake-5.10.0/tests/test_issue584/Snakefile000066400000000000000000000002421361131222100211400ustar00rootroot00000000000000rule all: input: "out1" rule generate: output: "out1" params: test=lambda wildcards: "{test}" shell: "echo "" > out1" snakemake-5.10.0/tests/test_issue584/expected-results/000077500000000000000000000000001361131222100226165ustar00rootroot00000000000000snakemake-5.10.0/tests/test_issue584/expected-results/out1000066400000000000000000000000011361131222100234200ustar00rootroot00000000000000 snakemake-5.10.0/tests/test_issue612/000077500000000000000000000000001361131222100173065ustar00rootroot00000000000000snakemake-5.10.0/tests/test_issue612/Snakefile000066400000000000000000000001351361131222100211310ustar00rootroot00000000000000rule A: run: print("A") rule B: run: print("B") rule C: run: print("C") snakemake-5.10.0/tests/test_issue612/expected-results/000077500000000000000000000000001361131222100226065ustar00rootroot00000000000000snakemake-5.10.0/tests/test_issue612/expected-results/.gitignore000066400000000000000000000000001361131222100245640ustar00rootroot00000000000000snakemake-5.10.0/tests/test_issue635/000077500000000000000000000000001361131222100173135ustar00rootroot00000000000000snakemake-5.10.0/tests/test_issue635/Snakefile000066400000000000000000000003021361131222100211320ustar00rootroot00000000000000 rule all: input: "report.html" rule rmd: input: "input.txt" output: "report.html" conda: "envs/rmarkdown.yaml" script: "scripts/report.Rmd" snakemake-5.10.0/tests/test_issue635/envs/000077500000000000000000000000001361131222100202665ustar00rootroot00000000000000snakemake-5.10.0/tests/test_issue635/envs/rmarkdown.yaml000066400000000000000000000001201361131222100231470ustar00rootroot00000000000000channels: - conda-forge dependencies: - r-base =3.6.1 - r-rmarkdown =1.17 snakemake-5.10.0/tests/test_issue635/expected-results/000077500000000000000000000000001361131222100226135ustar00rootroot00000000000000snakemake-5.10.0/tests/test_issue635/expected-results/report.html000066400000000000000000025615521361131222100250340ustar00rootroot00000000000000 Test Report

R Markdown

This is an R Markdown document.

Test include from snakemake input.txt.

# This works, but indicates that the working directory is NOT the workdir
data <- read.table("datadir/input.txt")
data
##   V1 V2 V3
## 1  1  2  3
getwd()
## [1] "/home/johannes/scms/snakemake/tests/test_issue365"
# This fails
#data <- read.table("snakemake@input[[1]]")
#data
snakemake-5.10.0/tests/test_issue635/input.txt000066400000000000000000000000061361131222100212070ustar00rootroot000000000000001 2 3 snakemake-5.10.0/tests/test_issue635/scripts/000077500000000000000000000000001361131222100210025ustar00rootroot00000000000000snakemake-5.10.0/tests/test_issue635/scripts/report.Rmd000066400000000000000000000012351361131222100227620ustar00rootroot00000000000000--- title: "Test Report" author: - "Your Name" date: "`r format(Sys.time(), '%d %B, %Y')`" params: rmd: "report.Rmd" output: html_document: highlight: tango number_sections: no theme: default toc: yes toc_depth: 3 toc_float: collapsed: no smooth_scroll: yes --- ## R Markdown This is an R Markdown document. Test include from snakemake ``r snakemake@input``. ```{r} print(getwd()) ``` ```{r} # This fails data <- read.table(snakemake@input[[1]]) data ``` ## Source R Markdown source file (to produce this document) snakemake-5.10.0/tests/test_issue805/000077500000000000000000000000001361131222100173125ustar00rootroot00000000000000snakemake-5.10.0/tests/test_issue805/Snakefile000066400000000000000000000003331361131222100211350ustar00rootroot00000000000000rule a: output: "test.out" shell: "echo {params.b} > {output}" params: b=1 rule b: input: "test.out" output: "test2.out" shell: "touch {output}" snakemake-5.10.0/tests/test_issue805/expected-results/000077500000000000000000000000001361131222100226125ustar00rootroot00000000000000snakemake-5.10.0/tests/test_issue805/expected-results/test.out000066400000000000000000000000021361131222100243120ustar00rootroot000000000000001 snakemake-5.10.0/tests/test_issue850/000077500000000000000000000000001361131222100173125ustar00rootroot00000000000000snakemake-5.10.0/tests/test_issue850/Snakefile000066400000000000000000000007261361131222100211430ustar00rootroot00000000000000 lists = [["1.bam", "2.bam"], ["3.bam", "4.bam"]] rule done: input: ["-".join(l) for l in lists], "2.qc2" rule a: output: touch("{sample}.bam") group: "cell" rule b: input: "{sample}.bam" output: touch("{sample}.qc") group: "cell" rule c: input: "{sample}.qc" output: touch("{sample}.qc2") group: "cell" for l in lists: rule: input: l output: temp(touch(str("-".join(l)))) group: "cell" snakemake-5.10.0/tests/test_issue850/expected-results/000077500000000000000000000000001361131222100226125ustar00rootroot00000000000000snakemake-5.10.0/tests/test_issue850/expected-results/2.qc2000066400000000000000000000000001361131222100233500ustar00rootroot00000000000000snakemake-5.10.0/tests/test_issue850/qsub000077500000000000000000000002231361131222100202070ustar00rootroot00000000000000#!/bin/bash echo `date` >> qsub.log tail -n1 $1 >> qsub.log # simulate printing of job id by a random number echo $RANDOM cat $1 >> qsub.log sh $1 snakemake-5.10.0/tests/test_issue854/000077500000000000000000000000001361131222100173165ustar00rootroot00000000000000snakemake-5.10.0/tests/test_issue854/Snakefile000066400000000000000000000002001361131222100211320ustar00rootroot00000000000000 rule a: output: "test.{x}.txt" benchmark: "benchmarks/test.txt" shell: "touch {output}" snakemake-5.10.0/tests/test_issue854/expected-results/000077500000000000000000000000001361131222100226165ustar00rootroot00000000000000snakemake-5.10.0/tests/test_issue854/expected-results/.gitignore000066400000000000000000000000001361131222100245740ustar00rootroot00000000000000snakemake-5.10.0/tests/test_issue860/000077500000000000000000000000001361131222100173135ustar00rootroot00000000000000snakemake-5.10.0/tests/test_issue860/Snakefile000066400000000000000000000010541361131222100211370ustar00rootroot00000000000000rule a: output: "{sample}.bam" group: "cell" shell: "touch {output}" rule b: input: "{sample}.bam" output: "{sample}.qc" group: "cell" shadow: "minimal" shell: "touch {output}" rule c: input: "{sample}.qc" output: "{sample}.qc2" group: "cell" shell: "touch {output}" lists = [["1.bam", "2.bam"], ["3.bam", "4.bam"]] for l in lists: rule: input: l output: temp(touch(str("-".join(l)))) group: "cell" rule done: input: [str("-".join(l)) for l in lists], "2.qc2" snakemake-5.10.0/tests/test_issue860/expected-results/000077500000000000000000000000001361131222100226135ustar00rootroot00000000000000snakemake-5.10.0/tests/test_issue860/expected-results/1.bam000066400000000000000000000000001361131222100234220ustar00rootroot00000000000000snakemake-5.10.0/tests/test_issue860/expected-results/2.bam000066400000000000000000000000001361131222100234230ustar00rootroot00000000000000snakemake-5.10.0/tests/test_issue860/expected-results/2.qc000066400000000000000000000000001361131222100232670ustar00rootroot00000000000000snakemake-5.10.0/tests/test_issue860/expected-results/2.qc2000066400000000000000000000000001361131222100233510ustar00rootroot00000000000000snakemake-5.10.0/tests/test_issue860/expected-results/3.bam000066400000000000000000000000001361131222100234240ustar00rootroot00000000000000snakemake-5.10.0/tests/test_issue860/expected-results/4.bam000066400000000000000000000000001361131222100234250ustar00rootroot00000000000000snakemake-5.10.0/tests/test_issue860/qsub000077500000000000000000000002231361131222100202100ustar00rootroot00000000000000#!/bin/bash echo `date` >> qsub.log tail -n1 $1 >> qsub.log # simulate printing of job id by a random number echo $RANDOM cat $1 >> qsub.log sh $1 snakemake-5.10.0/tests/test_issue894/000077500000000000000000000000001361131222100173225ustar00rootroot00000000000000snakemake-5.10.0/tests/test_issue894/Snakefile000066400000000000000000000001511361131222100211430ustar00rootroot00000000000000onsuccess: assert not os.path.exists("b") rule a: output: "a", temp("b") shell: "touch a b" snakemake-5.10.0/tests/test_issue894/expected-results/000077500000000000000000000000001361131222100226225ustar00rootroot00000000000000snakemake-5.10.0/tests/test_issue894/expected-results/a000066400000000000000000000000001361131222100227530ustar00rootroot00000000000000snakemake-5.10.0/tests/test_issue912/000077500000000000000000000000001361131222100173115ustar00rootroot00000000000000snakemake-5.10.0/tests/test_issue912/Snakefile000066400000000000000000000014351361131222100211400ustar00rootroot00000000000000# Create the directory fake/test and the file fake/test/sample.Mutect2.snpSift.vcf.gz # Run on cluster, example: # snakemake --cluster 'bash ' -j1 -p rule all: input: expand( "fake/test/{t}.Mutect2.snpSift.hardfilter.vcf.gz", t=['sample']), rule rule1: input: vcf = ancient('fake/{y}/{x}.vcf.gz'), output: indel = temp('fake/{y}/{x}.indels.raw.vcf.gz'), log: 'fake/logs/rule1.{y}.{x}.log' params: jobname = 'rule1.{x}' shell: 'touch {output.indel}' rule rule2: input: indel = 'fake/{y}/{x}.indels.raw.vcf.gz', output: 'fake/{y}/{x}.hardfilter.vcf.gz' log: 'fake/logs/rule2.{y}.{x}.log' params: jobname = 'rule2', shell: 'touch {output}' snakemake-5.10.0/tests/test_issue912/expected-results/000077500000000000000000000000001361131222100226115ustar00rootroot00000000000000snakemake-5.10.0/tests/test_issue912/expected-results/fake/000077500000000000000000000000001361131222100235175ustar00rootroot00000000000000snakemake-5.10.0/tests/test_issue912/expected-results/fake/logs/000077500000000000000000000000001361131222100244635ustar00rootroot00000000000000rule1.test.sample.Mutect2.snpSift.log000066400000000000000000000000001361131222100333320ustar00rootroot00000000000000snakemake-5.10.0/tests/test_issue912/expected-results/fake/logsrule2.test.sample.Mutect2.snpSift.log000066400000000000000000000000001361131222100333330ustar00rootroot00000000000000snakemake-5.10.0/tests/test_issue912/expected-results/fake/logssnakemake-5.10.0/tests/test_issue912/expected-results/fake/test/000077500000000000000000000000001361131222100244765ustar00rootroot00000000000000sample.Mutect2.snpSift.hardfilter.vcf.gz000066400000000000000000000000001361131222100340770ustar00rootroot00000000000000snakemake-5.10.0/tests/test_issue912/expected-results/fake/testsnakemake-5.10.0/tests/test_issue912/fake/000077500000000000000000000000001361131222100202175ustar00rootroot00000000000000snakemake-5.10.0/tests/test_issue912/fake/test/000077500000000000000000000000001361131222100211765ustar00rootroot00000000000000snakemake-5.10.0/tests/test_issue912/fake/test/sample.Mutect2.snpSift.vcf.gz000066400000000000000000000000001361131222100265330ustar00rootroot00000000000000snakemake-5.10.0/tests/test_issue912/qsub000077500000000000000000000002231361131222100202060ustar00rootroot00000000000000#!/bin/bash echo `date` >> qsub.log tail -n1 $1 >> qsub.log # simulate printing of job id by a random number echo $RANDOM cat $1 >> qsub.log sh $1 snakemake-5.10.0/tests/test_issue916/000077500000000000000000000000001361131222100173155ustar00rootroot00000000000000snakemake-5.10.0/tests/test_issue916/Snakefile000066400000000000000000000001531361131222100211400ustar00rootroot00000000000000rule all: input: "pythonTest" rule testIssue916: output: "pythonTest" script: "pythonTest.py" snakemake-5.10.0/tests/test_issue916/expected-results/000077500000000000000000000000001361131222100226155ustar00rootroot00000000000000snakemake-5.10.0/tests/test_issue916/expected-results/pythonTest000066400000000000000000000000451361131222100247200ustar00rootroot00000000000000local_script.contents blah blah blah snakemake-5.10.0/tests/test_issue916/local_script.py000066400000000000000000000000341361131222100223420ustar00rootroot00000000000000contents = "blah blah blah" snakemake-5.10.0/tests/test_issue916/pythonTest.py000066400000000000000000000012151361131222100220470ustar00rootroot00000000000000#!/usr/bin/env python import sys import os import local_script # Ensure that the __real_file__ path ends in .snakemake dname = os.path.dirname(__real_file__) print(dname) if not dname.endswith(os.path.join(".snakemake", "scripts")): sys.exit("We're not being written in the output directory!\n") # Ensure that the __file__ path ends in test_issue916 dname = os.path.dirname(__file__) print(dname) if not dname.endswith("test_issue916"): sys.exit("We're not faking __file__ properly!\n") # Write out script to indicte success. of = open(snakemake.output[0], "w") of.write("local_script.contents {}\n".format(local_script.contents)) of.close() snakemake-5.10.0/tests/test_issue930/000077500000000000000000000000001361131222100173115ustar00rootroot00000000000000snakemake-5.10.0/tests/test_issue930/Snakefile000066400000000000000000000012061361131222100211340ustar00rootroot00000000000000samples = ["0","1"] rule all: input: "test.out" rule build_index: output: "large_reference_index" shell: "touch {output}" rule a: output: "a/{sample}.out" group: "sample_group" shell: "touch {output}" rule b: input: rules.a.output, rules.build_index.output output: "b/{sample}.out" group: "sample_group" shell: "touch {output}" rule c: input: expand("a/{sample}.out", sample=samples), expand("b/{sample}.out", sample=samples) output: "test.out" shell: "touch {output}" snakemake-5.10.0/tests/test_issue930/expected-results/000077500000000000000000000000001361131222100226115ustar00rootroot00000000000000snakemake-5.10.0/tests/test_issue930/expected-results/test.out000066400000000000000000000000001361131222100243070ustar00rootroot00000000000000snakemake-5.10.0/tests/test_issue930/qsub000077500000000000000000000002231361131222100202060ustar00rootroot00000000000000#!/bin/bash echo `date` >> qsub.log tail -n1 $1 >> qsub.log # simulate printing of job id by a random number echo $RANDOM cat $1 >> qsub.log sh $1 snakemake-5.10.0/tests/test_issue956/000077500000000000000000000000001361131222100173215ustar00rootroot00000000000000snakemake-5.10.0/tests/test_issue956/Snakefile000066400000000000000000000016011361131222100211430ustar00rootroot00000000000000rule all: input: expand( "f_{result_type}.txt", result_type=["A", "B"]), rule make_A: output: result_A = "A_{result_type}.txt", shell: """ echo "A" > {output.result_A} """ rule make_B: output: result_B = "B_{result_type}.txt", shell: """ echo "B" > {output.result_B} """ def source_result_type(wildcards): if wildcards.result_type == "A": return rules.make_A.output.result_A elif wildcards.result_type == "B": return rules.make_B.output.result_B else: raise NotImplementedError(f"{wildcards.result_type} not possible.\n") rule generate_final_results: input: file_in = source_result_type, output: file_out = "f_{result_type}.txt", shell: """ cat {input.file_in} > {output.file_out} """ snakemake-5.10.0/tests/test_issue956/expected-results/000077500000000000000000000000001361131222100226215ustar00rootroot00000000000000snakemake-5.10.0/tests/test_issue956/expected-results/f_A.txt000066400000000000000000000000021361131222100240370ustar00rootroot00000000000000A snakemake-5.10.0/tests/test_issue956/expected-results/f_B.txt000066400000000000000000000000021361131222100240400ustar00rootroot00000000000000B snakemake-5.10.0/tests/test_issue958/000077500000000000000000000000001361131222100173235ustar00rootroot00000000000000snakemake-5.10.0/tests/test_issue958/Snakefile000066400000000000000000000002541361131222100211500ustar00rootroot00000000000000rule all: input: 'b.txt' rule g_touch_a: output: touch('a.txt') group: 'g' rule g_make_b_from_a: input: 'a.txt' output: touch('b.txt') group: 'g' snakemake-5.10.0/tests/test_issue958/a.txt000066400000000000000000000000001361131222100202720ustar00rootroot00000000000000snakemake-5.10.0/tests/test_issue958/expected-results/000077500000000000000000000000001361131222100226235ustar00rootroot00000000000000snakemake-5.10.0/tests/test_issue958/expected-results/.gitignore000066400000000000000000000000001361131222100246010ustar00rootroot00000000000000snakemake-5.10.0/tests/test_job_properties/000077500000000000000000000000001361131222100207535ustar00rootroot00000000000000snakemake-5.10.0/tests/test_job_properties/Snakefile000066400000000000000000000005571361131222100226060ustar00rootroot00000000000000 rule all: input: "test2.out" rule a: output: "test1.in" shell: "touch {output}" rule b: input: "test1.in" output: "test1.out" group: "x" shell: "touch {output}" rule c: input: "test1.out" output: "test2.out" group: "x" shell: "touch {output}" snakemake-5.10.0/tests/test_job_properties/expected-results/000077500000000000000000000000001361131222100242535ustar00rootroot00000000000000snakemake-5.10.0/tests/test_job_properties/expected-results/test2.out000066400000000000000000000000001361131222100260330ustar00rootroot00000000000000snakemake-5.10.0/tests/test_job_properties/qsub.py000077500000000000000000000004771361131222100223120ustar00rootroot00000000000000#!/usr/bin/env python3 import sys import os import random from snakemake.utils import read_job_properties jobscript = sys.argv[1] job_properties = read_job_properties(jobscript) with open("qsub.log", "a") as log: print(job_properties, file=log) print(random.randint(1, 100)) os.system("sh {}".format(jobscript)) snakemake-5.10.0/tests/test_jupyter_notebook/000077500000000000000000000000001361131222100213275ustar00rootroot00000000000000snakemake-5.10.0/tests/test_jupyter_notebook/Notebook.ipynb000066400000000000000000000017421361131222100241560ustar00rootroot00000000000000{ "cells": [ { "cell_type": "code", "execution_count": null, "metadata": {}, "outputs": [], "source": [ "with open(snakemake.input.infile) as fd:\n", " data = fd.read()" ] }, { "cell_type": "code", "execution_count": null, "metadata": {}, "outputs": [], "source": [ "new_results = data + '!!!'" ] }, { "cell_type": "code", "execution_count": null, "metadata": {}, "outputs": [], "source": [ "with open(snakemake.output.outfile, 'w') as fd:\n", " fd.write(new_results)" ] } ], "metadata": { "kernelspec": { "display_name": "Python 3", "language": "python", "name": "python3" }, "language_info": { "codemirror_mode": { "name": "ipython", "version": 3 }, "file_extension": ".py", "mimetype": "text/x-python", "name": "python", "nbconvert_exporter": "python", "pygments_lexer": "ipython3", "version": "3.7.4" } }, "nbformat": 4, "nbformat_minor": 2 } snakemake-5.10.0/tests/test_jupyter_notebook/Snakefile000066400000000000000000000011521361131222100231520ustar00rootroot00000000000000rule all: input: 'result_final.txt' rule foo: output: fname = 'data.txt' run: with open(output.fname, 'w') as fd: fd.write('result of serious computation') rule bar: input: infile = 'data.txt' output: outfile = 'result_intermediate.txt' conda: 'env.yaml' notebook: 'Notebook.ipynb' rule baz: input: infile = 'result_intermediate.txt' output: outfile = 'result_final.txt' log: notebook = 'Notebook_Processed.ipynb' conda: 'env.yaml' notebook: 'Notebook.ipynb' snakemake-5.10.0/tests/test_jupyter_notebook/env.yaml000066400000000000000000000001221361131222100227760ustar00rootroot00000000000000channels: - conda-forge - bioconda dependencies: - python >=3.5 - jupyter snakemake-5.10.0/tests/test_keyword_list/000077500000000000000000000000001361131222100204445ustar00rootroot00000000000000snakemake-5.10.0/tests/test_keyword_list/Snakefile000066400000000000000000000002221361131222100222640ustar00rootroot00000000000000rule: input: bla="test.in1 test.in2".split() output: "test.out" run: print(input.bla) assert len(input.bla) == 2 shell("touch {output}") snakemake-5.10.0/tests/test_keyword_list/expected-results/000077500000000000000000000000001361131222100237445ustar00rootroot00000000000000snakemake-5.10.0/tests/test_keyword_list/expected-results/test.out000066400000000000000000000000001361131222100254420ustar00rootroot00000000000000snakemake-5.10.0/tests/test_keyword_list/test.in1000066400000000000000000000000001361131222100220220ustar00rootroot00000000000000snakemake-5.10.0/tests/test_keyword_list/test.in2000066400000000000000000000000001361131222100220230ustar00rootroot00000000000000snakemake-5.10.0/tests/test_kubernetes/000077500000000000000000000000001361131222100200745ustar00rootroot00000000000000snakemake-5.10.0/tests/test_kubernetes/README.md000066400000000000000000000011071361131222100213520ustar00rootroot00000000000000# Executing this test case To run this test, you need a running kubernetes setup. For google cloud, see [here](https://snakemake.readthedocs.io/en/stable/executable.html#google-cloud-engine). With this, you can execute in case of google cloud: snakemake --kubernetes --use-conda --default-remote-provider GS --default-remote-prefix my-bucket while replacing ``my-bucket`` with your storage bucket. The same test should also work on amazon (given that kubernetes is setup): snakemake --kubernetes --use-conda --default-remote-provider S3 --default-remote-prefix my-bucket snakemake-5.10.0/tests/test_kubernetes/Snakefile000066400000000000000000000017551361131222100217300ustar00rootroot00000000000000import os from snakemake.remote.GS import RemoteProvider as GSRemoteProvider GS = GSRemoteProvider() rule all: input: "landsat-data.txt.bz2" rule copy: input: GS.remote("gcp-public-data-landsat/LC08/01/001/003/LC08_L1GT_001003_20170430_20170501_01_RT/LC08_L1GT_001003_20170430_20170501_01_RT_MTL.txt") output: "landsat-data.txt" resources: mem_mb=100 run: # we could test volume size like this but it is currently unclear what f1-micro instances provide as boot disk size #stats = os.statvfs('.') #volume_gib = stats.f_bsize * stats.f_blocks / 1.074e9 #assert volume_gib > 90 shell("cp {input} {output}") rule pack: input: "landsat-data.txt" output: "landsat-data.txt.bz2" conda: "envs/gzip.yaml" singularity: "docker://continuumio/miniconda3:4.4.10" log: "logs/pack.log" shell: "bzip2 -c {input} > {output}; echo successful > {log}" snakemake-5.10.0/tests/test_kubernetes/envs/000077500000000000000000000000001361131222100210475ustar00rootroot00000000000000snakemake-5.10.0/tests/test_kubernetes/envs/gzip.yaml000066400000000000000000000000621361131222100227020ustar00rootroot00000000000000channels: - conda-forge dependencies: - bzip2 snakemake-5.10.0/tests/test_kubernetes/expected-results/000077500000000000000000000000001361131222100233745ustar00rootroot00000000000000snakemake-5.10.0/tests/test_kubernetes/expected-results/.gitignore000066400000000000000000000000001361131222100253520ustar00rootroot00000000000000snakemake-5.10.0/tests/test_list_untracked/000077500000000000000000000000001361131222100207405ustar00rootroot00000000000000snakemake-5.10.0/tests/test_list_untracked/Snakefile000066400000000000000000000001761361131222100225700ustar00rootroot00000000000000rule run_test: output: "leftover_files" shell: "python -m snakemake -s Snakefile_inner --list-untracked 2> {output}" snakemake-5.10.0/tests/test_list_untracked/Snakefile_inner000066400000000000000000000007111361131222100237560ustar00rootroot00000000000000shell("mkdir -p some_workdir/some_subdir && \ touch some_workdir/used_input && \ touch some_workdir/some_subdir/used_output && \ touch some_workdir/some_subdir/not_used && \ touch some_workdir/log && \ touch some_workdir/.hiddenfile && \ mkdir -p some_workdir/.hiddendir && \ touch some_workdir/.hiddendir/not_used2") workdir: "some_workdir" rule a: input: "used_input" output: "some_subdir/used_output" log: "log" snakemake-5.10.0/tests/test_list_untracked/expected-results/000077500000000000000000000000001361131222100242405ustar00rootroot00000000000000snakemake-5.10.0/tests/test_list_untracked/expected-results/leftover_files000066400000000000000000000000551361131222100271730ustar00rootroot00000000000000Building DAG of jobs... some_subdir/not_used snakemake-5.10.0/tests/test_local_import/000077500000000000000000000000001361131222100204115ustar00rootroot00000000000000snakemake-5.10.0/tests/test_local_import/Snakefile000066400000000000000000000001121361131222100222270ustar00rootroot00000000000000import bar import foo rule: output: "test.out" shell: "touch {output}" snakemake-5.10.0/tests/test_local_import/bar.py000066400000000000000000000000001361131222100215150ustar00rootroot00000000000000snakemake-5.10.0/tests/test_local_import/expected-results/000077500000000000000000000000001361131222100237115ustar00rootroot00000000000000snakemake-5.10.0/tests/test_local_import/expected-results/test.out000066400000000000000000000000001361131222100254070ustar00rootroot00000000000000snakemake-5.10.0/tests/test_local_import/foo/000077500000000000000000000000001361131222100211745ustar00rootroot00000000000000snakemake-5.10.0/tests/test_local_import/foo/__init__.py000066400000000000000000000000001361131222100232730ustar00rootroot00000000000000snakemake-5.10.0/tests/test_log_input/000077500000000000000000000000001361131222100177255ustar00rootroot00000000000000snakemake-5.10.0/tests/test_log_input/Snakefile000066400000000000000000000005131361131222100215500ustar00rootroot00000000000000 rule all: input: "test.a.txt" rule a: output: "unused.{sample}.txt" log: "logs/{sample}.txt" shell: "echo {wildcards.sample} > {log}; touch {output}" rule b: input: "logs/{sample}.txt" output: "test.{sample}.txt" shell: "cp {input} {output}" snakemake-5.10.0/tests/test_log_input/expected-results/000077500000000000000000000000001361131222100232255ustar00rootroot00000000000000snakemake-5.10.0/tests/test_log_input/expected-results/test.a.txt000066400000000000000000000000021361131222100251540ustar00rootroot00000000000000a snakemake-5.10.0/tests/test_many_jobs/000077500000000000000000000000001361131222100177065ustar00rootroot00000000000000snakemake-5.10.0/tests/test_many_jobs/Snakefile000066400000000000000000000005541361131222100215360ustar00rootroot00000000000000 rule: input: expand("{sample}.out", sample=range(50000)) rule: input: "{sample}.inter2" output: "{sample}.out" shell: "touch {output}" rule: input: "{sample}.inter1" output: "{sample}.inter2" shell: "touch {output}" rule: input: "{sample}.in" output: "{sample}.inter1" shell: "touch {output}" rule: output: "{sample}.in" shell: "touch {output}" snakemake-5.10.0/tests/test_multiext/000077500000000000000000000000001361131222100176005ustar00rootroot00000000000000snakemake-5.10.0/tests/test_multiext/Snakefile000066400000000000000000000001561361131222100214260ustar00rootroot00000000000000rule a: output: multiext("ref/genome", ".ann", ".bwt", ".sa") shell: "touch {output}" snakemake-5.10.0/tests/test_multiext/expected-results/000077500000000000000000000000001361131222100231005ustar00rootroot00000000000000snakemake-5.10.0/tests/test_multiext/expected-results/ref/000077500000000000000000000000001361131222100236545ustar00rootroot00000000000000snakemake-5.10.0/tests/test_multiext/expected-results/ref/genome.ann000066400000000000000000000000001361131222100256120ustar00rootroot00000000000000snakemake-5.10.0/tests/test_multiext/expected-results/ref/genome.bwt000066400000000000000000000000001361131222100256320ustar00rootroot00000000000000snakemake-5.10.0/tests/test_multiext/expected-results/ref/genome.sa000066400000000000000000000000001361131222100254410ustar00rootroot00000000000000snakemake-5.10.0/tests/test_multiple_includes/000077500000000000000000000000001361131222100214465ustar00rootroot00000000000000snakemake-5.10.0/tests/test_multiple_includes/Snakefile000066400000000000000000000001541361131222100232720ustar00rootroot00000000000000include: 'test_rule.smk' include: 'test_second_rule.smk' rule all: input: rules.test_second_rule.outputsnakemake-5.10.0/tests/test_multiple_includes/expected-results/000077500000000000000000000000001361131222100247465ustar00rootroot00000000000000snakemake-5.10.0/tests/test_multiple_includes/expected-results/test1.txt000066400000000000000000000000001361131222100265350ustar00rootroot00000000000000snakemake-5.10.0/tests/test_multiple_includes/expected-results/test2.txt000066400000000000000000000000001361131222100265360ustar00rootroot00000000000000snakemake-5.10.0/tests/test_multiple_includes/test_rule.smk000066400000000000000000000001041361131222100241630ustar00rootroot00000000000000rule test_rule: output: 'test1.txt' shell: 'touch {output}'snakemake-5.10.0/tests/test_multiple_includes/test_second_rule.smk000066400000000000000000000001551361131222100255240ustar00rootroot00000000000000rule test_second_rule: input: rules.test_rule.output output: 'test2.txt' shell: 'touch {output}'snakemake-5.10.0/tests/test_nonstr_params/000077500000000000000000000000001361131222100206135ustar00rootroot00000000000000snakemake-5.10.0/tests/test_nonstr_params/Snakefile000066400000000000000000000002171361131222100224370ustar00rootroot00000000000000rule: output: "test.out" params: test=True run: assert params.test is True shell("touch {output}") snakemake-5.10.0/tests/test_nonstr_params/expected-results/000077500000000000000000000000001361131222100241135ustar00rootroot00000000000000snakemake-5.10.0/tests/test_nonstr_params/expected-results/test.out000066400000000000000000000000001361131222100256110ustar00rootroot00000000000000snakemake-5.10.0/tests/test_omitfrom/000077500000000000000000000000001361131222100175615ustar00rootroot00000000000000snakemake-5.10.0/tests/test_omitfrom/Snakefile000066400000000000000000000023201361131222100214020ustar00rootroot00000000000000 rule all: input: "levelthree.txt", "independent.txt", expand("test{num}.final", num=[1, 2]) rule levelone: output: "levelone.txt" shell: "touch {output}" rule leveltwo_first: input: rules.levelone.output output: "leveltwo_first.txt" shell: "cp -f {input} {output}" rule leveltwo_second: input: rules.levelone.output output: "leveltwo_second.txt" shell: "cp -f {input} {output}" rule levelthree: # should not be created input: rules.leveltwo_first.output, rules.leveltwo_second.output output: "levelthree.txt" shell: "cat {input} > {output}" rule independent: # should be created in --omit-from but not --until output: "independent.txt" shell: "touch {output}" ###### Wildcard Rules ####### rule zeroth_wildcard: output: "test{num}.txt" shell: "touch {output}" rule first_wildcard: input: 'test{num}.txt' output: 'test{num}.first' shell: 'cp -f {input} {output}' rule second_wildcard: input: 'test{num}.first' output: 'test{num}.second' shell: 'cp -f {input} {output}' rule final_wildcard: input: 'test{num}.second' output: 'test{num}.final' shell: 'cp -f {input} {output}' snakemake-5.10.0/tests/test_omitfrom/expected-results/000077500000000000000000000000001361131222100230615ustar00rootroot00000000000000snakemake-5.10.0/tests/test_omitfrom/expected-results/independent.txt000066400000000000000000000000001361131222100261050ustar00rootroot00000000000000snakemake-5.10.0/tests/test_omitfrom/expected-results/levelone.txt000066400000000000000000000000001361131222100254210ustar00rootroot00000000000000snakemake-5.10.0/tests/test_output_file_cache/000077500000000000000000000000001361131222100214075ustar00rootroot00000000000000snakemake-5.10.0/tests/test_output_file_cache/Snakefile000066400000000000000000000011431361131222100232320ustar00rootroot00000000000000rule all: input: "test3.x.out", "test3.y.out" rule a: output: "test.out" shell: "echo test > {output}" rule b: input: "test.out" output: multiext("test2", ".out", ".out2") shell: "echo test2 > {output[0]}; echo test22 > {output[1]}" rule c: input: "test2.out", "test.out" output: "test3.{w}.out" params: a=1.5 shell: "echo test3 {params.a} > {output}" rule invalid_multi: output: "invalid1.txt", "invalid2.txt" shell: "touch {output}" snakemake-5.10.0/tests/test_output_file_cache/cache/000077500000000000000000000000001361131222100224525ustar00rootroot00000000000000snakemake-5.10.0/tests/test_output_file_cache/cache/.gitkeep000066400000000000000000000000001361131222100240710ustar00rootroot00000000000000snakemake-5.10.0/tests/test_output_file_cache/expected-results/000077500000000000000000000000001361131222100247075ustar00rootroot00000000000000snakemake-5.10.0/tests/test_output_file_cache/expected-results/cache/000077500000000000000000000000001361131222100257525ustar00rootroot0000000000000013b6128773a87e3d14cac7fab4949705be33620855bc102f07cffdae63664ea1000066400000000000000000000000121361131222100364010ustar00rootroot00000000000000snakemake-5.10.0/tests/test_output_file_cache/expected-results/cachetest3 1.5 c547ff53a86ac70fecf68cf675b774bd158027def062bb65892b2f4f1662bc0e.out000066400000000000000000000000061361131222100374640ustar00rootroot00000000000000snakemake-5.10.0/tests/test_output_file_cache/expected-results/cachetest2 fa466047205bfd2dc7fe1fcbd5ec3591e3c1c5f73e8c7112493092191af2bee8000066400000000000000000000000051361131222100366310ustar00rootroot00000000000000snakemake-5.10.0/tests/test_output_file_cache/expected-results/cachetest snakemake-5.10.0/tests/test_output_file_cache/expected-results/test.out000066400000000000000000000000051361131222100264120ustar00rootroot00000000000000test snakemake-5.10.0/tests/test_output_file_cache/expected-results/test2.out000066400000000000000000000000061361131222100264750ustar00rootroot00000000000000test2 snakemake-5.10.0/tests/test_output_file_cache/expected-results/test3.x.out000066400000000000000000000000121361131222100267410ustar00rootroot00000000000000test3 1.5 snakemake-5.10.0/tests/test_output_file_cache/expected-results/test3.y.out000066400000000000000000000000121361131222100267420ustar00rootroot00000000000000test3 1.5 snakemake-5.10.0/tests/test_output_file_cache_remote/000077500000000000000000000000001361131222100227625ustar00rootroot00000000000000snakemake-5.10.0/tests/test_output_file_cache_remote/Snakefile000066400000000000000000000006701361131222100246110ustar00rootroot00000000000000rule all: input: "test3.x.out", "test3.y.out" rule a: output: "test.out" shell: "echo test > {output}" rule b: input: "test.out" output: "test2.out" shell: "echo test2 > {output}" rule c: input: "test2.out", "test.out" output: "test3.{w}.out" params: a=1.5 shell: "echo test3 {params.a} > {output}" snakemake-5.10.0/tests/test_output_file_cache_remote/expected-results/000077500000000000000000000000001361131222100262625ustar00rootroot00000000000000snakemake-5.10.0/tests/test_output_file_cache_remote/expected-results/cache/000077500000000000000000000000001361131222100273255ustar00rootroot0000000000000013b6128773a87e3d14cac7fab4949705be33620855bc102f07cffdae63664ea1000066400000000000000000000000121361131222100377540ustar00rootroot00000000000000snakemake-5.10.0/tests/test_output_file_cache_remote/expected-results/cachetest3 1.5 c547ff53a86ac70fecf68cf675b774bd158027def062bb65892b2f4f1662bc0e000066400000000000000000000000061361131222100402310ustar00rootroot00000000000000snakemake-5.10.0/tests/test_output_file_cache_remote/expected-results/cachetest2 fa466047205bfd2dc7fe1fcbd5ec3591e3c1c5f73e8c7112493092191af2bee8000066400000000000000000000000051361131222100402040ustar00rootroot00000000000000snakemake-5.10.0/tests/test_output_file_cache_remote/expected-results/cachetest snakemake-5.10.0/tests/test_output_file_cache_remote/test.txt000066400000000000000000000000001361131222100244700ustar00rootroot00000000000000snakemake-5.10.0/tests/test_params/000077500000000000000000000000001361131222100172105ustar00rootroot00000000000000snakemake-5.10.0/tests/test_params/Snakefile000066400000000000000000000003571361131222100210410ustar00rootroot00000000000000 """ This is a test for the params syntax. """ rule: input: "somedir/test.out" rule: params: lambda wildcards: "-f", dir="{dir}" output: "{dir}/test.out" shell: "rm -r {params.dir}; mkdir -p {params.dir}; touch {params[0]} {output}" snakemake-5.10.0/tests/test_params/expected-results/000077500000000000000000000000001361131222100225105ustar00rootroot00000000000000snakemake-5.10.0/tests/test_params/expected-results/somedir/000077500000000000000000000000001361131222100241525ustar00rootroot00000000000000snakemake-5.10.0/tests/test_params/expected-results/somedir/test.out000066400000000000000000000000001361131222100256500ustar00rootroot00000000000000snakemake-5.10.0/tests/test_parser/000077500000000000000000000000001361131222100172215ustar00rootroot00000000000000snakemake-5.10.0/tests/test_parser/Snakefile000066400000000000000000000001721361131222100210450ustar00rootroot00000000000000 class Test: def __init__(self): self.include = "test.out" rule: output: Test().include shell: "touch {output}" snakemake-5.10.0/tests/test_parser/expected-results/000077500000000000000000000000001361131222100225215ustar00rootroot00000000000000snakemake-5.10.0/tests/test_parser/expected-results/test.out000066400000000000000000000000001361131222100242170ustar00rootroot00000000000000snakemake-5.10.0/tests/test_parser/test.out000066400000000000000000000000001361131222100207170ustar00rootroot00000000000000snakemake-5.10.0/tests/test_pathlib/000077500000000000000000000000001361131222100173505ustar00rootroot00000000000000snakemake-5.10.0/tests/test_pathlib/Snakefile000066400000000000000000000031041361131222100211720ustar00rootroot00000000000000from pathlib import Path # Untested: # ancient # subworkflows # directory OUTDIR = Path("outdir") existing_file = Path("existing_file.txt") rule all: input: OUTDIR / "output_existing", #OUTDIR / "output_temp", OUTDIR / "output_protected", OUTDIR / "output_other_rule_output_existing", OUTDIR / "function_unpacking/output_function_unpacking", rule input_Path: input: Path("{sample}_file.txt") output: OUTDIR / "output_{sample}" log: OUTDIR / "log_{sample}" shell: """ cat {input} > {output} echo log {wildcards.sample} > {log} """ rule input_Path_output_temp: input: existing_file output: temp(OUTDIR / "output_temp") log: OUTDIR / "log_temp" shell: """ cat {input} > {output} echo log temp > {log} """ rule input_Path_output_protected: input: existing_file output: protected(OUTDIR / "output_protected") log: OUTDIR / "log_protected" shell: """ cat {input} > {output} echo log protected > {log} """ rule input_other_rule_output: input: rules.input_Path.output output: OUTDIR / "output_other_rule_output_{sample}" log: OUTDIR / "log_other_rule_output_{sample}" shell: """ cat {input} > {output} echo log protected > {log} """ def myfunc1(): return [existing_file] def myfunc2(): return {'existing_file2': existing_file} rule input_function_unpacking: input: *myfunc1(), **myfunc2(), output: OUTDIR / "function_unpacking/output_function_unpacking" log: OUTDIR / "log_function_unpacking" shell: """ echo {input[0]} > {output} echo {input.existing_file2} >> {output} echo log function unpacking > {log} """ snakemake-5.10.0/tests/test_pathlib/existing_file.txt000066400000000000000000000000111361131222100227320ustar00rootroot00000000000000I exist! snakemake-5.10.0/tests/test_pathlib/expected-results/000077500000000000000000000000001361131222100226505ustar00rootroot00000000000000snakemake-5.10.0/tests/test_pathlib/expected-results/outdir/000077500000000000000000000000001361131222100241565ustar00rootroot00000000000000snakemake-5.10.0/tests/test_pathlib/expected-results/outdir/function_unpacking/000077500000000000000000000000001361131222100300425ustar00rootroot00000000000000output_function_unpacking000066400000000000000000000000441361131222100352100ustar00rootroot00000000000000snakemake-5.10.0/tests/test_pathlib/expected-results/outdir/function_unpackingexisting_file.txt existing_file.txt snakemake-5.10.0/tests/test_pathlib/expected-results/outdir/log_dynamic000066400000000000000000000000141361131222100263610ustar00rootroot00000000000000log dynamic snakemake-5.10.0/tests/test_pathlib/expected-results/outdir/log_existing000066400000000000000000000000151361131222100265700ustar00rootroot00000000000000log existing snakemake-5.10.0/tests/test_pathlib/expected-results/outdir/log_function_unpacking000066400000000000000000000000271361131222100306250ustar00rootroot00000000000000log function unpacking snakemake-5.10.0/tests/test_pathlib/expected-results/outdir/log_other_rule_output000066400000000000000000000000161361131222100305270ustar00rootroot00000000000000log protected snakemake-5.10.0/tests/test_pathlib/expected-results/outdir/log_protected000066400000000000000000000000161361131222100267300ustar00rootroot00000000000000log protected snakemake-5.10.0/tests/test_pathlib/expected-results/outdir/output_existing000066400000000000000000000000111361131222100273430ustar00rootroot00000000000000I exist! snakemake-5.10.0/tests/test_pathlib/expected-results/outdir/output_other_rule_output_existing000066400000000000000000000000111361131222100332130ustar00rootroot00000000000000I exist! snakemake-5.10.0/tests/test_pathlib/expected-results/outdir/output_protected000066400000000000000000000000111361131222100275020ustar00rootroot00000000000000I exist! snakemake-5.10.0/tests/test_pathlib_missing_file/000077500000000000000000000000001361131222100221005ustar00rootroot00000000000000snakemake-5.10.0/tests/test_pathlib_missing_file/Snakefile000066400000000000000000000004541361131222100237270ustar00rootroot00000000000000from pathlib import Path # Things to test: # ancient # subworkflows output = Path("output") nonexistent_file = Path("nonexistent_file.txt") rule all: input: output rule input_nonexistent_Path: input: nonexistent_file output: output shell: """ echo "This should fail" > {output} """ snakemake-5.10.0/tests/test_pathlib_missing_file/expected-results/000077500000000000000000000000001361131222100254005ustar00rootroot00000000000000snakemake-5.10.0/tests/test_pathlib_missing_file/expected-results/.gitkeep000066400000000000000000000000001361131222100270170ustar00rootroot00000000000000snakemake-5.10.0/tests/test_persistent_dict/000077500000000000000000000000001361131222100211305ustar00rootroot00000000000000snakemake-5.10.0/tests/test_persistent_dict/Snakefile000066400000000000000000000010171361131222100227530ustar00rootroot00000000000000from pytools.persistent_dict import PersistentDict storage = PersistentDict("mystorage") storage.store("var1", 100) rule all: input: expand("test.{i}.out", i=range(3)) rule: input: "test.in" output: "test.{i}.out" run: assert storage.fetch("var1") == 100 with open(output[0], "w") as out: v = storage.fetch("var2") assert v == 1 print(v, file=out) rule: output: temp("test.in") # mark output as temp, since var1 has to be stored in each run run: storage.store("var2", 1) shell("touch {output}") snakemake-5.10.0/tests/test_persistent_dict/expected-results/000077500000000000000000000000001361131222100244305ustar00rootroot00000000000000snakemake-5.10.0/tests/test_persistent_dict/expected-results/.gitignore000066400000000000000000000000001361131222100264060ustar00rootroot00000000000000snakemake-5.10.0/tests/test_pipes/000077500000000000000000000000001361131222100170455ustar00rootroot00000000000000snakemake-5.10.0/tests/test_pipes/Snakefile000066400000000000000000000005201361131222100206660ustar00rootroot00000000000000rule all: input: expand("test.{i}.out", i=range(2)) rule a: output: pipe("test.{i}.txt") shell: "for i in {{0..2}}; do echo {wildcards.i} >> {output}; done" rule b: input: "test.{i}.txt" output: "test.{i}.out" shell: "grep {wildcards.i} < {input} > {output}" snakemake-5.10.0/tests/test_pipes/expected-results/000077500000000000000000000000001361131222100223455ustar00rootroot00000000000000snakemake-5.10.0/tests/test_pipes/expected-results/test.0.out000066400000000000000000000000061361131222100242070ustar00rootroot000000000000000 0 0 snakemake-5.10.0/tests/test_pipes/expected-results/test.1.out000066400000000000000000000000061361131222100242100ustar00rootroot000000000000001 1 1 snakemake-5.10.0/tests/test_pipes2/000077500000000000000000000000001361131222100171275ustar00rootroot00000000000000snakemake-5.10.0/tests/test_pipes2/Snakefile000066400000000000000000000004511361131222100207530ustar00rootroot00000000000000rule all: input: "foo.txt" rule one: output: pipe("pipe.txt") shell: "echo test > {output}" rule two: input: pipe("pipe.txt") output: "foo.txt" shell: """ cat {input} > /dev/null sleep 10 touch {output} """ snakemake-5.10.0/tests/test_pipes2/expected-results/000077500000000000000000000000001361131222100224275ustar00rootroot00000000000000snakemake-5.10.0/tests/test_pipes2/expected-results/foo.txt000066400000000000000000000000001361131222100237410ustar00rootroot00000000000000snakemake-5.10.0/tests/test_pipes_fail/000077500000000000000000000000001361131222100200405ustar00rootroot00000000000000snakemake-5.10.0/tests/test_pipes_fail/Snakefile000066400000000000000000000006041361131222100216640ustar00rootroot00000000000000rule all: input: expand("test.{i}.out", i=range(2)) rule a: output: pipe("test.{i}.txt") shell: # this job fails because of a syntax error "for i in {{0..2}}; ddo echo {wildcards.i} >> {output}; done" rule b: input: "test.{i}.txt" output: "test.{i}.out" shell: "grep {wildcards.i} < {input} > {output}" snakemake-5.10.0/tests/test_pipes_fail/expected-results/000077500000000000000000000000001361131222100233405ustar00rootroot00000000000000snakemake-5.10.0/tests/test_pipes_fail/expected-results/.gitignore000066400000000000000000000000001361131222100253160ustar00rootroot00000000000000snakemake-5.10.0/tests/test_profile/000077500000000000000000000000001361131222100173655ustar00rootroot00000000000000snakemake-5.10.0/tests/test_profile/Snakefile000066400000000000000000000001211361131222100212030ustar00rootroot00000000000000rule: shell: "python -m snakemake --profile . -s Snakefile.internal" snakemake-5.10.0/tests/test_profile/Snakefile.internal000066400000000000000000000001161361131222100230220ustar00rootroot00000000000000rule a: output: config["out"] shell: "touch {output}" snakemake-5.10.0/tests/test_profile/config.yaml000066400000000000000000000000561361131222100215170ustar00rootroot00000000000000configfile: "workflow-config.yaml" cores: all snakemake-5.10.0/tests/test_profile/expected-results/000077500000000000000000000000001361131222100226655ustar00rootroot00000000000000snakemake-5.10.0/tests/test_profile/expected-results/test.out000066400000000000000000000000001361131222100243630ustar00rootroot00000000000000snakemake-5.10.0/tests/test_profile/workflow-config.yaml000066400000000000000000000000201361131222100233560ustar00rootroot00000000000000out: "test.out" snakemake-5.10.0/tests/test_protected_symlink_output/000077500000000000000000000000001361131222100231045ustar00rootroot00000000000000snakemake-5.10.0/tests/test_protected_symlink_output/Snakefile000066400000000000000000000020501361131222100247250ustar00rootroot00000000000000# vim: ft=python """Snakemake will not delete write-protected files. But a symlink to a write-protected file is another matter. We should be able to overwrite those. """ """Description of the test: protected1 and protected2 are non-writeable files outlink is a symlink to protected1 after the main rule runs, outlink should point to protected2, and outfile should contain "contents2". """ import os import time # Set up the files just once if not os.path.exists("outlink"): shell("echo contents1 > protected1") shell("echo contents2 > protected2") shell("ln -s protected1 outlink") shell("chmod a-w protected1 protected2") # Print the result for debugging shell("ls -lR > /dev/stderr") rule main: output: "outfile", "outlink" run: # outlink should be gone but not protected1 or protected2 shell("test ! -e outlink") shell("test -e protected1 && test -e protected2") # Re-point the symlink shell("ln -s protected2 outlink") shell("cat outlink > outfile") snakemake-5.10.0/tests/test_protected_symlink_output/expected-results/000077500000000000000000000000001361131222100264045ustar00rootroot00000000000000snakemake-5.10.0/tests/test_protected_symlink_output/expected-results/outfile000066400000000000000000000000121361131222100277670ustar00rootroot00000000000000contents2 snakemake-5.10.0/tests/test_protected_symlink_output/expected-results/outlink000066400000000000000000000000121361131222100300050ustar00rootroot00000000000000contents2 snakemake-5.10.0/tests/test_r_wrapper/000077500000000000000000000000001361131222100177265ustar00rootroot00000000000000snakemake-5.10.0/tests/test_r_wrapper/Snakefile000066400000000000000000000001421361131222100215470ustar00rootroot00000000000000rule r_wrapper: output: "deleteme" wrapper: "file://tests/test_r_wrapper" snakemake-5.10.0/tests/test_r_wrapper/wrapper.R000066400000000000000000000001401361131222100215240ustar00rootroot00000000000000outfile = snakemake@output[[1]] x <- data.frame() write.table(x, file=outfile, col.names=FALSE) snakemake-5.10.0/tests/test_remote/000077500000000000000000000000001361131222100172205ustar00rootroot00000000000000snakemake-5.10.0/tests/test_remote/Snakefile000066400000000000000000000062331361131222100210500ustar00rootroot00000000000000#import re, os, sys from snakemake.remote.S3Mocked import RemoteProvider as S3RemoteProvider S3 = S3RemoteProvider() # remote dynamic file test # This makes use of a special provider that mocks up S3 using the moto # library so that boto calls hit local "buckets" rule all: input: # only keeping the file so we can copy it out to the cwd S3.remote("test-remote-bucket/out.txt", keep_local=True) run: shell("mv test-remote-bucket/out.txt ./") rule split: input: S3.remote('test-remote-bucket/test.txt') output: S3.remote(dynamic('test-remote-bucket/prefix{split_id}.txt')) run: shell('split -l 2 {input} test-remote-bucket/prefix') for f in os.listdir(os.getcwd()+"/test-remote-bucket"): if re.search('prefix[a-z][a-z]', f): os.rename("test-remote-bucket/"+f, "test-remote-bucket/"+f + '.txt') rule cut: input: S3.remote('test-remote-bucket/prefix{split_id,[a-z][a-z]}.txt') output: S3.remote('test-remote-bucket/{split_id}_cut.txt') shell: 'cut -f 1,2 {input} > {output}' rule merge: input: S3.remote(dynamic('test-remote-bucket/{split_id}_cut.txt')) output: S3.remote('test-remote-bucket/out.txt'), run: shell('echo {input}; cat {input} > {output}') # after we finish, we need to remove the pickle storing # the local moto "buckets" so we are starting fresh # next time this test is run. This file is created by # the moto wrapper defined in S3Mocked.py onsuccess: shell("rm ./motoState.p") onerror: shell("rm ./motoState.p") # or if you prefer to not instantiate a RemoteProvider object, and rely on the module # import S3Mocked as S3Mocked # # remote dynamic file test # # This makes use of a special provider that mocks up S3 using the moto # # library so that boto calls hit local "buckets" # rule all: # input: # # only keeping the file so we can copy it out to the cwd # remote("test-remote-bucket/out.txt", keep_local=True, provider=S3Mocked, additional_kwargs={}) # run: # shell("mv test-remote-bucket/out.txt ./") # rule split: # input: remote('test-remote-bucket/test.txt', keep_local=False, provider=S3Mocked, additional_kwargs={}) # output: remote(dynamic('test-remote-bucket/prefix{split_id}.txt'), provider=S3Mocked, additional_kwargs={}) # run: # shell('split -l 2 {input} test-remote-bucket/prefix') # for f in os.listdir(os.getcwd()+"/test-remote-bucket"): # if re.search('prefix[a-z][a-z]', f): # os.rename("test-remote-bucket/"+f, "test-remote-bucket/"+f + '.txt') # rule cut: # input: remote('test-remote-bucket/prefix{split_id,[a-z][a-z]}.txt', provider=S3Mocked, additional_kwargs={}) # output: # remote('test-remote-bucket/{split_id}_cut.txt', provider=S3Mocked, additional_kwargs={}) # shell: 'cut -f 1,2 {input} > {output}' # rule merge: # input: # remote(dynamic('test-remote-bucket/{split_id}_cut.txt'), provider=S3Mocked, additional_kwargs={}) # output: # remote('test-remote-bucket/out.txt', provider=S3Mocked, additional_kwargs={}), # run: # shell('echo {input}; cat {input} > {output}') snakemake-5.10.0/tests/test_remote/expected-results/000077500000000000000000000000001361131222100225205ustar00rootroot00000000000000snakemake-5.10.0/tests/test_remote/expected-results/out.txt000066400000000000000000000001101361131222100240600ustar00rootroot000000000000000 1 2 0 1 2 0 1 2 0 1 2 snakemake-5.10.0/tests/test_remote/test.txt000066400000000000000000000001101361131222100207300ustar00rootroot000000000000000 1 2 0 1 2 0 1 2 0 1 2 snakemake-5.10.0/tests/test_remote_azure/000077500000000000000000000000001361131222100204265ustar00rootroot00000000000000snakemake-5.10.0/tests/test_remote_azure/.gitignore000066400000000000000000000000321361131222100224110ustar00rootroot00000000000000test.txt.gz globbing.done snakemake-5.10.0/tests/test_remote_azure/README.md000066400000000000000000000006701361131222100217100ustar00rootroot00000000000000# Instruction for testing of Azure Storage integration * in order to perform this test, an Azure Storage Account is required * Both the storage account and associated key need to be passed to snakemake at runtime * currently this is solved by setting and exporting environment variables called ** $AZURE_ACCOUNT ** $AZURE_KEY * furthermore, in the storage account, a container "snakemake-test" needs to be created prio to running the test snakemake-5.10.0/tests/test_remote_azure/Snakefile000066400000000000000000000023171361131222100222550ustar00rootroot00000000000000import os import fnmatch import snakemake from snakemake.exceptions import MissingInputException from snakemake.remote.AzureStorage import RemoteProvider as AzureRemoteProvider # setup Azure Storage for remote access # for testing these variable can be added to CircleCI account_key=os.environ['AZURE_KEY'] account_name=os.environ['AZURE_ACCOUNT'] AS = AzureRemoteProvider(account_name=account_name, account_key=account_key) rule upload_to_azure_storage: input: "data/test.txt.gz" output: AS.remote("snakemake-test/data_upload/test.txt.gz") run: shell("cp {input} {output}") rule download_from_azure_storage: input: AS.remote("snakemake-test/data_upload/test.txt.gz") output: "test.txt.gz" run: shell("cp {input} {output}") rule test_globbing: input: AS.remote("snakemake-test/data_upload/test.txt.gz") output: touch("globbing.done") run: basenames, = AS.glob_wildcards("snakemake-test/data_upload/{base}.txt.gz") assert "test" in basenames rule test_download: input: "globbing.done", "test.txt.gz" rule test_upload: input: AS.remote("snakemake-test/data_upload/test.txt.gz") snakemake-5.10.0/tests/test_remote_gs/000077500000000000000000000000001361131222100177115ustar00rootroot00000000000000snakemake-5.10.0/tests/test_remote_gs/Snakefile000066400000000000000000000010431361131222100215330ustar00rootroot00000000000000from snakemake.remote import GS import google.auth try: GS = GS.RemoteProvider() rule copy: input: GS.remote("gcp-public-data-landsat/LC08/01/001/003/LC08_L1GT_001003_20170430_20170501_01_RT/LC08_L1GT_001003_20170430_20170501_01_RT_MTL.txt") output: "landsat-data.txt" shell: "cp {input} {output}" except google.auth.exceptions.DefaultCredentialsError: # ignore the test if not authenticated print("skipping test_remote_gs because we are not authenticated with gcloud") snakemake-5.10.0/tests/test_remote_gs/expected-results/000077500000000000000000000000001361131222100232115ustar00rootroot00000000000000snakemake-5.10.0/tests/test_remote_gs/expected-results/landsat-data.txt000066400000000000000000000203761361131222100263170ustar00rootroot00000000000000GROUP = L1_METADATA_FILE GROUP = METADATA_FILE_INFO ORIGIN = "Image courtesy of the U.S. Geological Survey" REQUEST_ID = "0501705013406_00001" LANDSAT_SCENE_ID = "LC80010032017120LGN00" LANDSAT_PRODUCT_ID = "LC08_L1GT_001003_20170430_20170501_01_RT" COLLECTION_NUMBER = 01 FILE_DATE = 2017-05-01T16:00:24Z STATION_ID = "LGN" PROCESSING_SOFTWARE_VERSION = "LPGS_2.7.0" END_GROUP = METADATA_FILE_INFO GROUP = PRODUCT_METADATA DATA_TYPE = "L1GT" COLLECTION_CATEGORY = "RT" ELEVATION_SOURCE = "GLS2000" OUTPUT_FORMAT = "GEOTIFF" SPACECRAFT_ID = "LANDSAT_8" SENSOR_ID = "OLI_TIRS" WRS_PATH = 1 WRS_ROW = 3 NADIR_OFFNADIR = "NADIR" TARGET_WRS_PATH = 1 TARGET_WRS_ROW = 3 DATE_ACQUIRED = 2017-04-30 SCENE_CENTER_TIME = "14:07:16.5180850Z" CORNER_UL_LAT_PRODUCT = 80.21528 CORNER_UL_LON_PRODUCT = -17.96312 CORNER_UR_LAT_PRODUCT = 80.28798 CORNER_UR_LON_PRODUCT = -3.45901 CORNER_LL_LAT_PRODUCT = 77.79053 CORNER_LL_LON_PRODUCT = -16.19251 CORNER_LR_LAT_PRODUCT = 77.84841 CORNER_LR_LON_PRODUCT = -4.56164 CORNER_UL_PROJECTION_X_PRODUCT = 330600.000 CORNER_UL_PROJECTION_Y_PRODUCT = 8918700.000 CORNER_UR_PROJECTION_X_PRODUCT = 604200.000 CORNER_UR_PROJECTION_Y_PRODUCT = 8918700.000 CORNER_LL_PROJECTION_X_PRODUCT = 330600.000 CORNER_LL_PROJECTION_Y_PRODUCT = 8645400.000 CORNER_LR_PROJECTION_X_PRODUCT = 604200.000 CORNER_LR_PROJECTION_Y_PRODUCT = 8645400.000 PANCHROMATIC_LINES = 18221 PANCHROMATIC_SAMPLES = 18241 REFLECTIVE_LINES = 9111 REFLECTIVE_SAMPLES = 9121 THERMAL_LINES = 9111 THERMAL_SAMPLES = 9121 FILE_NAME_BAND_1 = "LC08_L1GT_001003_20170430_20170501_01_RT_B1.TIF" FILE_NAME_BAND_2 = "LC08_L1GT_001003_20170430_20170501_01_RT_B2.TIF" FILE_NAME_BAND_3 = "LC08_L1GT_001003_20170430_20170501_01_RT_B3.TIF" FILE_NAME_BAND_4 = "LC08_L1GT_001003_20170430_20170501_01_RT_B4.TIF" FILE_NAME_BAND_5 = "LC08_L1GT_001003_20170430_20170501_01_RT_B5.TIF" FILE_NAME_BAND_6 = "LC08_L1GT_001003_20170430_20170501_01_RT_B6.TIF" FILE_NAME_BAND_7 = "LC08_L1GT_001003_20170430_20170501_01_RT_B7.TIF" FILE_NAME_BAND_8 = "LC08_L1GT_001003_20170430_20170501_01_RT_B8.TIF" FILE_NAME_BAND_9 = "LC08_L1GT_001003_20170430_20170501_01_RT_B9.TIF" FILE_NAME_BAND_10 = "LC08_L1GT_001003_20170430_20170501_01_RT_B10.TIF" FILE_NAME_BAND_11 = "LC08_L1GT_001003_20170430_20170501_01_RT_B11.TIF" FILE_NAME_BAND_QUALITY = "LC08_L1GT_001003_20170430_20170501_01_RT_BQA.TIF" ANGLE_COEFFICIENT_FILE_NAME = "LC08_L1GT_001003_20170430_20170501_01_RT_ANG.txt" METADATA_FILE_NAME = "LC08_L1GT_001003_20170430_20170501_01_RT_MTL.txt" CPF_NAME = "LC08CPF_20170401_20170630_01.02" BPF_NAME_OLI = "LO8BPF20170430140614_20170430144404.01" BPF_NAME_TIRS = "LT8BPF20170426235522_20170427000359.01" RLUT_FILE_NAME = "LC08RLUT_20150303_20431231_01_12.h5" END_GROUP = PRODUCT_METADATA GROUP = IMAGE_ATTRIBUTES CLOUD_COVER = 24.32 CLOUD_COVER_LAND = -1 IMAGE_QUALITY_OLI = 9 IMAGE_QUALITY_TIRS = 7 TIRS_SSM_MODEL = "PRELIMINARY" TIRS_SSM_POSITION_STATUS = "ESTIMATED" TIRS_STRAY_LIGHT_CORRECTION_SOURCE = "TIRS" ROLL_ANGLE = -0.001 SUN_AZIMUTH = -156.47580997 SUN_ELEVATION = 24.99099132 EARTH_SUN_DISTANCE = 1.0074392 SATURATION_BAND_1 = "N" SATURATION_BAND_2 = "N" SATURATION_BAND_3 = "N" SATURATION_BAND_4 = "N" SATURATION_BAND_5 = "N" SATURATION_BAND_6 = "N" SATURATION_BAND_7 = "N" SATURATION_BAND_8 = "N" SATURATION_BAND_9 = "N" TRUNCATION_OLI = "UPPER" END_GROUP = IMAGE_ATTRIBUTES GROUP = MIN_MAX_RADIANCE RADIANCE_MAXIMUM_BAND_1 = 748.87909 RADIANCE_MINIMUM_BAND_1 = -61.84268 RADIANCE_MAXIMUM_BAND_2 = 766.86133 RADIANCE_MINIMUM_BAND_2 = -63.32766 RADIANCE_MAXIMUM_BAND_3 = 706.65613 RADIANCE_MINIMUM_BAND_3 = -58.35589 RADIANCE_MAXIMUM_BAND_4 = 595.89227 RADIANCE_MINIMUM_BAND_4 = -49.20898 RADIANCE_MAXIMUM_BAND_5 = 364.65634 RADIANCE_MINIMUM_BAND_5 = -30.11344 RADIANCE_MAXIMUM_BAND_6 = 90.68671 RADIANCE_MINIMUM_BAND_6 = -7.48894 RADIANCE_MAXIMUM_BAND_7 = 30.56628 RADIANCE_MINIMUM_BAND_7 = -2.52417 RADIANCE_MAXIMUM_BAND_8 = 674.38605 RADIANCE_MINIMUM_BAND_8 = -55.69102 RADIANCE_MAXIMUM_BAND_9 = 142.51598 RADIANCE_MINIMUM_BAND_9 = -11.76902 RADIANCE_MAXIMUM_BAND_10 = 22.00180 RADIANCE_MINIMUM_BAND_10 = 0.10033 RADIANCE_MAXIMUM_BAND_11 = 22.00180 RADIANCE_MINIMUM_BAND_11 = 0.10033 END_GROUP = MIN_MAX_RADIANCE GROUP = MIN_MAX_REFLECTANCE REFLECTANCE_MAXIMUM_BAND_1 = 1.210700 REFLECTANCE_MINIMUM_BAND_1 = -0.099980 REFLECTANCE_MAXIMUM_BAND_2 = 1.210700 REFLECTANCE_MINIMUM_BAND_2 = -0.099980 REFLECTANCE_MAXIMUM_BAND_3 = 1.210700 REFLECTANCE_MINIMUM_BAND_3 = -0.099980 REFLECTANCE_MAXIMUM_BAND_4 = 1.210700 REFLECTANCE_MINIMUM_BAND_4 = -0.099980 REFLECTANCE_MAXIMUM_BAND_5 = 1.210700 REFLECTANCE_MINIMUM_BAND_5 = -0.099980 REFLECTANCE_MAXIMUM_BAND_6 = 1.210700 REFLECTANCE_MINIMUM_BAND_6 = -0.099980 REFLECTANCE_MAXIMUM_BAND_7 = 1.210700 REFLECTANCE_MINIMUM_BAND_7 = -0.099980 REFLECTANCE_MAXIMUM_BAND_8 = 1.210700 REFLECTANCE_MINIMUM_BAND_8 = -0.099980 REFLECTANCE_MAXIMUM_BAND_9 = 1.210700 REFLECTANCE_MINIMUM_BAND_9 = -0.099980 END_GROUP = MIN_MAX_REFLECTANCE GROUP = MIN_MAX_PIXEL_VALUE QUANTIZE_CAL_MAX_BAND_1 = 65535 QUANTIZE_CAL_MIN_BAND_1 = 1 QUANTIZE_CAL_MAX_BAND_2 = 65535 QUANTIZE_CAL_MIN_BAND_2 = 1 QUANTIZE_CAL_MAX_BAND_3 = 65535 QUANTIZE_CAL_MIN_BAND_3 = 1 QUANTIZE_CAL_MAX_BAND_4 = 65535 QUANTIZE_CAL_MIN_BAND_4 = 1 QUANTIZE_CAL_MAX_BAND_5 = 65535 QUANTIZE_CAL_MIN_BAND_5 = 1 QUANTIZE_CAL_MAX_BAND_6 = 65535 QUANTIZE_CAL_MIN_BAND_6 = 1 QUANTIZE_CAL_MAX_BAND_7 = 65535 QUANTIZE_CAL_MIN_BAND_7 = 1 QUANTIZE_CAL_MAX_BAND_8 = 65535 QUANTIZE_CAL_MIN_BAND_8 = 1 QUANTIZE_CAL_MAX_BAND_9 = 65535 QUANTIZE_CAL_MIN_BAND_9 = 1 QUANTIZE_CAL_MAX_BAND_10 = 65535 QUANTIZE_CAL_MIN_BAND_10 = 1 QUANTIZE_CAL_MAX_BAND_11 = 65535 QUANTIZE_CAL_MIN_BAND_11 = 1 END_GROUP = MIN_MAX_PIXEL_VALUE GROUP = RADIOMETRIC_RESCALING RADIANCE_MULT_BAND_1 = 1.2371E-02 RADIANCE_MULT_BAND_2 = 1.2668E-02 RADIANCE_MULT_BAND_3 = 1.1674E-02 RADIANCE_MULT_BAND_4 = 9.8438E-03 RADIANCE_MULT_BAND_5 = 6.0239E-03 RADIANCE_MULT_BAND_6 = 1.4981E-03 RADIANCE_MULT_BAND_7 = 5.0494E-04 RADIANCE_MULT_BAND_8 = 1.1140E-02 RADIANCE_MULT_BAND_9 = 2.3543E-03 RADIANCE_MULT_BAND_10 = 3.3420E-04 RADIANCE_MULT_BAND_11 = 3.3420E-04 RADIANCE_ADD_BAND_1 = -61.85505 RADIANCE_ADD_BAND_2 = -63.34032 RADIANCE_ADD_BAND_3 = -58.36757 RADIANCE_ADD_BAND_4 = -49.21882 RADIANCE_ADD_BAND_5 = -30.11946 RADIANCE_ADD_BAND_6 = -7.49044 RADIANCE_ADD_BAND_7 = -2.52468 RADIANCE_ADD_BAND_8 = -55.70216 RADIANCE_ADD_BAND_9 = -11.77137 RADIANCE_ADD_BAND_10 = 0.10000 RADIANCE_ADD_BAND_11 = 0.10000 REFLECTANCE_MULT_BAND_1 = 2.0000E-05 REFLECTANCE_MULT_BAND_2 = 2.0000E-05 REFLECTANCE_MULT_BAND_3 = 2.0000E-05 REFLECTANCE_MULT_BAND_4 = 2.0000E-05 REFLECTANCE_MULT_BAND_5 = 2.0000E-05 REFLECTANCE_MULT_BAND_6 = 2.0000E-05 REFLECTANCE_MULT_BAND_7 = 2.0000E-05 REFLECTANCE_MULT_BAND_8 = 2.0000E-05 REFLECTANCE_MULT_BAND_9 = 2.0000E-05 REFLECTANCE_ADD_BAND_1 = -0.100000 REFLECTANCE_ADD_BAND_2 = -0.100000 REFLECTANCE_ADD_BAND_3 = -0.100000 REFLECTANCE_ADD_BAND_4 = -0.100000 REFLECTANCE_ADD_BAND_5 = -0.100000 REFLECTANCE_ADD_BAND_6 = -0.100000 REFLECTANCE_ADD_BAND_7 = -0.100000 REFLECTANCE_ADD_BAND_8 = -0.100000 REFLECTANCE_ADD_BAND_9 = -0.100000 END_GROUP = RADIOMETRIC_RESCALING GROUP = TIRS_THERMAL_CONSTANTS K1_CONSTANT_BAND_10 = 774.8853 K2_CONSTANT_BAND_10 = 1321.0789 K1_CONSTANT_BAND_11 = 480.8883 K2_CONSTANT_BAND_11 = 1201.1442 END_GROUP = TIRS_THERMAL_CONSTANTS GROUP = PROJECTION_PARAMETERS MAP_PROJECTION = "UTM" DATUM = "WGS84" ELLIPSOID = "WGS84" UTM_ZONE = 29 GRID_CELL_SIZE_PANCHROMATIC = 15.00 GRID_CELL_SIZE_REFLECTIVE = 30.00 GRID_CELL_SIZE_THERMAL = 30.00 ORIENTATION = "NORTH_UP" RESAMPLING_OPTION = "CUBIC_CONVOLUTION" END_GROUP = PROJECTION_PARAMETERS END_GROUP = L1_METADATA_FILE END snakemake-5.10.0/tests/test_remote_gs/landsat-data.txt000066400000000000000000000203761361131222100230170ustar00rootroot00000000000000GROUP = L1_METADATA_FILE GROUP = METADATA_FILE_INFO ORIGIN = "Image courtesy of the U.S. Geological Survey" REQUEST_ID = "0501705013406_00001" LANDSAT_SCENE_ID = "LC80010032017120LGN00" LANDSAT_PRODUCT_ID = "LC08_L1GT_001003_20170430_20170501_01_RT" COLLECTION_NUMBER = 01 FILE_DATE = 2017-05-01T16:00:24Z STATION_ID = "LGN" PROCESSING_SOFTWARE_VERSION = "LPGS_2.7.0" END_GROUP = METADATA_FILE_INFO GROUP = PRODUCT_METADATA DATA_TYPE = "L1GT" COLLECTION_CATEGORY = "RT" ELEVATION_SOURCE = "GLS2000" OUTPUT_FORMAT = "GEOTIFF" SPACECRAFT_ID = "LANDSAT_8" SENSOR_ID = "OLI_TIRS" WRS_PATH = 1 WRS_ROW = 3 NADIR_OFFNADIR = "NADIR" TARGET_WRS_PATH = 1 TARGET_WRS_ROW = 3 DATE_ACQUIRED = 2017-04-30 SCENE_CENTER_TIME = "14:07:16.5180850Z" CORNER_UL_LAT_PRODUCT = 80.21528 CORNER_UL_LON_PRODUCT = -17.96312 CORNER_UR_LAT_PRODUCT = 80.28798 CORNER_UR_LON_PRODUCT = -3.45901 CORNER_LL_LAT_PRODUCT = 77.79053 CORNER_LL_LON_PRODUCT = -16.19251 CORNER_LR_LAT_PRODUCT = 77.84841 CORNER_LR_LON_PRODUCT = -4.56164 CORNER_UL_PROJECTION_X_PRODUCT = 330600.000 CORNER_UL_PROJECTION_Y_PRODUCT = 8918700.000 CORNER_UR_PROJECTION_X_PRODUCT = 604200.000 CORNER_UR_PROJECTION_Y_PRODUCT = 8918700.000 CORNER_LL_PROJECTION_X_PRODUCT = 330600.000 CORNER_LL_PROJECTION_Y_PRODUCT = 8645400.000 CORNER_LR_PROJECTION_X_PRODUCT = 604200.000 CORNER_LR_PROJECTION_Y_PRODUCT = 8645400.000 PANCHROMATIC_LINES = 18221 PANCHROMATIC_SAMPLES = 18241 REFLECTIVE_LINES = 9111 REFLECTIVE_SAMPLES = 9121 THERMAL_LINES = 9111 THERMAL_SAMPLES = 9121 FILE_NAME_BAND_1 = "LC08_L1GT_001003_20170430_20170501_01_RT_B1.TIF" FILE_NAME_BAND_2 = "LC08_L1GT_001003_20170430_20170501_01_RT_B2.TIF" FILE_NAME_BAND_3 = "LC08_L1GT_001003_20170430_20170501_01_RT_B3.TIF" FILE_NAME_BAND_4 = "LC08_L1GT_001003_20170430_20170501_01_RT_B4.TIF" FILE_NAME_BAND_5 = "LC08_L1GT_001003_20170430_20170501_01_RT_B5.TIF" FILE_NAME_BAND_6 = "LC08_L1GT_001003_20170430_20170501_01_RT_B6.TIF" FILE_NAME_BAND_7 = "LC08_L1GT_001003_20170430_20170501_01_RT_B7.TIF" FILE_NAME_BAND_8 = "LC08_L1GT_001003_20170430_20170501_01_RT_B8.TIF" FILE_NAME_BAND_9 = "LC08_L1GT_001003_20170430_20170501_01_RT_B9.TIF" FILE_NAME_BAND_10 = "LC08_L1GT_001003_20170430_20170501_01_RT_B10.TIF" FILE_NAME_BAND_11 = "LC08_L1GT_001003_20170430_20170501_01_RT_B11.TIF" FILE_NAME_BAND_QUALITY = "LC08_L1GT_001003_20170430_20170501_01_RT_BQA.TIF" ANGLE_COEFFICIENT_FILE_NAME = "LC08_L1GT_001003_20170430_20170501_01_RT_ANG.txt" METADATA_FILE_NAME = "LC08_L1GT_001003_20170430_20170501_01_RT_MTL.txt" CPF_NAME = "LC08CPF_20170401_20170630_01.02" BPF_NAME_OLI = "LO8BPF20170430140614_20170430144404.01" BPF_NAME_TIRS = "LT8BPF20170426235522_20170427000359.01" RLUT_FILE_NAME = "LC08RLUT_20150303_20431231_01_12.h5" END_GROUP = PRODUCT_METADATA GROUP = IMAGE_ATTRIBUTES CLOUD_COVER = 24.32 CLOUD_COVER_LAND = -1 IMAGE_QUALITY_OLI = 9 IMAGE_QUALITY_TIRS = 7 TIRS_SSM_MODEL = "PRELIMINARY" TIRS_SSM_POSITION_STATUS = "ESTIMATED" TIRS_STRAY_LIGHT_CORRECTION_SOURCE = "TIRS" ROLL_ANGLE = -0.001 SUN_AZIMUTH = -156.47580997 SUN_ELEVATION = 24.99099132 EARTH_SUN_DISTANCE = 1.0074392 SATURATION_BAND_1 = "N" SATURATION_BAND_2 = "N" SATURATION_BAND_3 = "N" SATURATION_BAND_4 = "N" SATURATION_BAND_5 = "N" SATURATION_BAND_6 = "N" SATURATION_BAND_7 = "N" SATURATION_BAND_8 = "N" SATURATION_BAND_9 = "N" TRUNCATION_OLI = "UPPER" END_GROUP = IMAGE_ATTRIBUTES GROUP = MIN_MAX_RADIANCE RADIANCE_MAXIMUM_BAND_1 = 748.87909 RADIANCE_MINIMUM_BAND_1 = -61.84268 RADIANCE_MAXIMUM_BAND_2 = 766.86133 RADIANCE_MINIMUM_BAND_2 = -63.32766 RADIANCE_MAXIMUM_BAND_3 = 706.65613 RADIANCE_MINIMUM_BAND_3 = -58.35589 RADIANCE_MAXIMUM_BAND_4 = 595.89227 RADIANCE_MINIMUM_BAND_4 = -49.20898 RADIANCE_MAXIMUM_BAND_5 = 364.65634 RADIANCE_MINIMUM_BAND_5 = -30.11344 RADIANCE_MAXIMUM_BAND_6 = 90.68671 RADIANCE_MINIMUM_BAND_6 = -7.48894 RADIANCE_MAXIMUM_BAND_7 = 30.56628 RADIANCE_MINIMUM_BAND_7 = -2.52417 RADIANCE_MAXIMUM_BAND_8 = 674.38605 RADIANCE_MINIMUM_BAND_8 = -55.69102 RADIANCE_MAXIMUM_BAND_9 = 142.51598 RADIANCE_MINIMUM_BAND_9 = -11.76902 RADIANCE_MAXIMUM_BAND_10 = 22.00180 RADIANCE_MINIMUM_BAND_10 = 0.10033 RADIANCE_MAXIMUM_BAND_11 = 22.00180 RADIANCE_MINIMUM_BAND_11 = 0.10033 END_GROUP = MIN_MAX_RADIANCE GROUP = MIN_MAX_REFLECTANCE REFLECTANCE_MAXIMUM_BAND_1 = 1.210700 REFLECTANCE_MINIMUM_BAND_1 = -0.099980 REFLECTANCE_MAXIMUM_BAND_2 = 1.210700 REFLECTANCE_MINIMUM_BAND_2 = -0.099980 REFLECTANCE_MAXIMUM_BAND_3 = 1.210700 REFLECTANCE_MINIMUM_BAND_3 = -0.099980 REFLECTANCE_MAXIMUM_BAND_4 = 1.210700 REFLECTANCE_MINIMUM_BAND_4 = -0.099980 REFLECTANCE_MAXIMUM_BAND_5 = 1.210700 REFLECTANCE_MINIMUM_BAND_5 = -0.099980 REFLECTANCE_MAXIMUM_BAND_6 = 1.210700 REFLECTANCE_MINIMUM_BAND_6 = -0.099980 REFLECTANCE_MAXIMUM_BAND_7 = 1.210700 REFLECTANCE_MINIMUM_BAND_7 = -0.099980 REFLECTANCE_MAXIMUM_BAND_8 = 1.210700 REFLECTANCE_MINIMUM_BAND_8 = -0.099980 REFLECTANCE_MAXIMUM_BAND_9 = 1.210700 REFLECTANCE_MINIMUM_BAND_9 = -0.099980 END_GROUP = MIN_MAX_REFLECTANCE GROUP = MIN_MAX_PIXEL_VALUE QUANTIZE_CAL_MAX_BAND_1 = 65535 QUANTIZE_CAL_MIN_BAND_1 = 1 QUANTIZE_CAL_MAX_BAND_2 = 65535 QUANTIZE_CAL_MIN_BAND_2 = 1 QUANTIZE_CAL_MAX_BAND_3 = 65535 QUANTIZE_CAL_MIN_BAND_3 = 1 QUANTIZE_CAL_MAX_BAND_4 = 65535 QUANTIZE_CAL_MIN_BAND_4 = 1 QUANTIZE_CAL_MAX_BAND_5 = 65535 QUANTIZE_CAL_MIN_BAND_5 = 1 QUANTIZE_CAL_MAX_BAND_6 = 65535 QUANTIZE_CAL_MIN_BAND_6 = 1 QUANTIZE_CAL_MAX_BAND_7 = 65535 QUANTIZE_CAL_MIN_BAND_7 = 1 QUANTIZE_CAL_MAX_BAND_8 = 65535 QUANTIZE_CAL_MIN_BAND_8 = 1 QUANTIZE_CAL_MAX_BAND_9 = 65535 QUANTIZE_CAL_MIN_BAND_9 = 1 QUANTIZE_CAL_MAX_BAND_10 = 65535 QUANTIZE_CAL_MIN_BAND_10 = 1 QUANTIZE_CAL_MAX_BAND_11 = 65535 QUANTIZE_CAL_MIN_BAND_11 = 1 END_GROUP = MIN_MAX_PIXEL_VALUE GROUP = RADIOMETRIC_RESCALING RADIANCE_MULT_BAND_1 = 1.2371E-02 RADIANCE_MULT_BAND_2 = 1.2668E-02 RADIANCE_MULT_BAND_3 = 1.1674E-02 RADIANCE_MULT_BAND_4 = 9.8438E-03 RADIANCE_MULT_BAND_5 = 6.0239E-03 RADIANCE_MULT_BAND_6 = 1.4981E-03 RADIANCE_MULT_BAND_7 = 5.0494E-04 RADIANCE_MULT_BAND_8 = 1.1140E-02 RADIANCE_MULT_BAND_9 = 2.3543E-03 RADIANCE_MULT_BAND_10 = 3.3420E-04 RADIANCE_MULT_BAND_11 = 3.3420E-04 RADIANCE_ADD_BAND_1 = -61.85505 RADIANCE_ADD_BAND_2 = -63.34032 RADIANCE_ADD_BAND_3 = -58.36757 RADIANCE_ADD_BAND_4 = -49.21882 RADIANCE_ADD_BAND_5 = -30.11946 RADIANCE_ADD_BAND_6 = -7.49044 RADIANCE_ADD_BAND_7 = -2.52468 RADIANCE_ADD_BAND_8 = -55.70216 RADIANCE_ADD_BAND_9 = -11.77137 RADIANCE_ADD_BAND_10 = 0.10000 RADIANCE_ADD_BAND_11 = 0.10000 REFLECTANCE_MULT_BAND_1 = 2.0000E-05 REFLECTANCE_MULT_BAND_2 = 2.0000E-05 REFLECTANCE_MULT_BAND_3 = 2.0000E-05 REFLECTANCE_MULT_BAND_4 = 2.0000E-05 REFLECTANCE_MULT_BAND_5 = 2.0000E-05 REFLECTANCE_MULT_BAND_6 = 2.0000E-05 REFLECTANCE_MULT_BAND_7 = 2.0000E-05 REFLECTANCE_MULT_BAND_8 = 2.0000E-05 REFLECTANCE_MULT_BAND_9 = 2.0000E-05 REFLECTANCE_ADD_BAND_1 = -0.100000 REFLECTANCE_ADD_BAND_2 = -0.100000 REFLECTANCE_ADD_BAND_3 = -0.100000 REFLECTANCE_ADD_BAND_4 = -0.100000 REFLECTANCE_ADD_BAND_5 = -0.100000 REFLECTANCE_ADD_BAND_6 = -0.100000 REFLECTANCE_ADD_BAND_7 = -0.100000 REFLECTANCE_ADD_BAND_8 = -0.100000 REFLECTANCE_ADD_BAND_9 = -0.100000 END_GROUP = RADIOMETRIC_RESCALING GROUP = TIRS_THERMAL_CONSTANTS K1_CONSTANT_BAND_10 = 774.8853 K2_CONSTANT_BAND_10 = 1321.0789 K1_CONSTANT_BAND_11 = 480.8883 K2_CONSTANT_BAND_11 = 1201.1442 END_GROUP = TIRS_THERMAL_CONSTANTS GROUP = PROJECTION_PARAMETERS MAP_PROJECTION = "UTM" DATUM = "WGS84" ELLIPSOID = "WGS84" UTM_ZONE = 29 GRID_CELL_SIZE_PANCHROMATIC = 15.00 GRID_CELL_SIZE_REFLECTIVE = 30.00 GRID_CELL_SIZE_THERMAL = 30.00 ORIENTATION = "NORTH_UP" RESAMPLING_OPTION = "CUBIC_CONVOLUTION" END_GROUP = PROJECTION_PARAMETERS END_GROUP = L1_METADATA_FILE END snakemake-5.10.0/tests/test_remote_http/000077500000000000000000000000001361131222100202575ustar00rootroot00000000000000snakemake-5.10.0/tests/test_remote_http/Snakefile000066400000000000000000000023071361131222100221050ustar00rootroot00000000000000from snakemake.remote.HTTP import RemoteProvider as HTTPRemoteProvider HTTP = HTTPRemoteProvider() # The plain text version and the unzipped .gz version should have the same content. # The diff command returns exit code 0 for identical files, 1 for differing files and 2 for errors. rule compare: input: "landsat-data.txt", "landsat-data-unzipped.txt" shell: "diff {input[0]} {input[1]}" rule copy: input: HTTP.remote("bitbucket.org/snakemake/snakemake/raw/http-gzip-autodecode/tests/test_remote_http/expected-results/landsat-data.txt") output: "landsat-data.txt" shell: "cp {input} {output}" rule copy_gz: input: HTTP.remote("bitbucket.org/snakemake/snakemake/raw/http-gzip-autodecode/tests/test_remote_http/expected-results/landsat-data.txt.gz") output: "landsat-data.txt.gz" shell: "cp {input} {output}" # This only works if the input file is a gzipped file. # Hence, it will fail, if the .txt.gz file is automagically decompressed by the requests module. rule unizp: input: "landsat-data.txt.gz" output: "landsat-data-unzipped.txt" shell: "gunzip -c {input} > {output}" snakemake-5.10.0/tests/test_remote_http/expected-results/000077500000000000000000000000001361131222100235575ustar00rootroot00000000000000snakemake-5.10.0/tests/test_remote_http/expected-results/landsat-data.txt000066400000000000000000000203761361131222100266650ustar00rootroot00000000000000GROUP = L1_METADATA_FILE GROUP = METADATA_FILE_INFO ORIGIN = "Image courtesy of the U.S. Geological Survey" REQUEST_ID = "0501705013406_00001" LANDSAT_SCENE_ID = "LC80010032017120LGN00" LANDSAT_PRODUCT_ID = "LC08_L1GT_001003_20170430_20170501_01_RT" COLLECTION_NUMBER = 01 FILE_DATE = 2017-05-01T16:00:24Z STATION_ID = "LGN" PROCESSING_SOFTWARE_VERSION = "LPGS_2.7.0" END_GROUP = METADATA_FILE_INFO GROUP = PRODUCT_METADATA DATA_TYPE = "L1GT" COLLECTION_CATEGORY = "RT" ELEVATION_SOURCE = "GLS2000" OUTPUT_FORMAT = "GEOTIFF" SPACECRAFT_ID = "LANDSAT_8" SENSOR_ID = "OLI_TIRS" WRS_PATH = 1 WRS_ROW = 3 NADIR_OFFNADIR = "NADIR" TARGET_WRS_PATH = 1 TARGET_WRS_ROW = 3 DATE_ACQUIRED = 2017-04-30 SCENE_CENTER_TIME = "14:07:16.5180850Z" CORNER_UL_LAT_PRODUCT = 80.21528 CORNER_UL_LON_PRODUCT = -17.96312 CORNER_UR_LAT_PRODUCT = 80.28798 CORNER_UR_LON_PRODUCT = -3.45901 CORNER_LL_LAT_PRODUCT = 77.79053 CORNER_LL_LON_PRODUCT = -16.19251 CORNER_LR_LAT_PRODUCT = 77.84841 CORNER_LR_LON_PRODUCT = -4.56164 CORNER_UL_PROJECTION_X_PRODUCT = 330600.000 CORNER_UL_PROJECTION_Y_PRODUCT = 8918700.000 CORNER_UR_PROJECTION_X_PRODUCT = 604200.000 CORNER_UR_PROJECTION_Y_PRODUCT = 8918700.000 CORNER_LL_PROJECTION_X_PRODUCT = 330600.000 CORNER_LL_PROJECTION_Y_PRODUCT = 8645400.000 CORNER_LR_PROJECTION_X_PRODUCT = 604200.000 CORNER_LR_PROJECTION_Y_PRODUCT = 8645400.000 PANCHROMATIC_LINES = 18221 PANCHROMATIC_SAMPLES = 18241 REFLECTIVE_LINES = 9111 REFLECTIVE_SAMPLES = 9121 THERMAL_LINES = 9111 THERMAL_SAMPLES = 9121 FILE_NAME_BAND_1 = "LC08_L1GT_001003_20170430_20170501_01_RT_B1.TIF" FILE_NAME_BAND_2 = "LC08_L1GT_001003_20170430_20170501_01_RT_B2.TIF" FILE_NAME_BAND_3 = "LC08_L1GT_001003_20170430_20170501_01_RT_B3.TIF" FILE_NAME_BAND_4 = "LC08_L1GT_001003_20170430_20170501_01_RT_B4.TIF" FILE_NAME_BAND_5 = "LC08_L1GT_001003_20170430_20170501_01_RT_B5.TIF" FILE_NAME_BAND_6 = "LC08_L1GT_001003_20170430_20170501_01_RT_B6.TIF" FILE_NAME_BAND_7 = "LC08_L1GT_001003_20170430_20170501_01_RT_B7.TIF" FILE_NAME_BAND_8 = "LC08_L1GT_001003_20170430_20170501_01_RT_B8.TIF" FILE_NAME_BAND_9 = "LC08_L1GT_001003_20170430_20170501_01_RT_B9.TIF" FILE_NAME_BAND_10 = "LC08_L1GT_001003_20170430_20170501_01_RT_B10.TIF" FILE_NAME_BAND_11 = "LC08_L1GT_001003_20170430_20170501_01_RT_B11.TIF" FILE_NAME_BAND_QUALITY = "LC08_L1GT_001003_20170430_20170501_01_RT_BQA.TIF" ANGLE_COEFFICIENT_FILE_NAME = "LC08_L1GT_001003_20170430_20170501_01_RT_ANG.txt" METADATA_FILE_NAME = "LC08_L1GT_001003_20170430_20170501_01_RT_MTL.txt" CPF_NAME = "LC08CPF_20170401_20170630_01.02" BPF_NAME_OLI = "LO8BPF20170430140614_20170430144404.01" BPF_NAME_TIRS = "LT8BPF20170426235522_20170427000359.01" RLUT_FILE_NAME = "LC08RLUT_20150303_20431231_01_12.h5" END_GROUP = PRODUCT_METADATA GROUP = IMAGE_ATTRIBUTES CLOUD_COVER = 24.32 CLOUD_COVER_LAND = -1 IMAGE_QUALITY_OLI = 9 IMAGE_QUALITY_TIRS = 7 TIRS_SSM_MODEL = "PRELIMINARY" TIRS_SSM_POSITION_STATUS = "ESTIMATED" TIRS_STRAY_LIGHT_CORRECTION_SOURCE = "TIRS" ROLL_ANGLE = -0.001 SUN_AZIMUTH = -156.47580997 SUN_ELEVATION = 24.99099132 EARTH_SUN_DISTANCE = 1.0074392 SATURATION_BAND_1 = "N" SATURATION_BAND_2 = "N" SATURATION_BAND_3 = "N" SATURATION_BAND_4 = "N" SATURATION_BAND_5 = "N" SATURATION_BAND_6 = "N" SATURATION_BAND_7 = "N" SATURATION_BAND_8 = "N" SATURATION_BAND_9 = "N" TRUNCATION_OLI = "UPPER" END_GROUP = IMAGE_ATTRIBUTES GROUP = MIN_MAX_RADIANCE RADIANCE_MAXIMUM_BAND_1 = 748.87909 RADIANCE_MINIMUM_BAND_1 = -61.84268 RADIANCE_MAXIMUM_BAND_2 = 766.86133 RADIANCE_MINIMUM_BAND_2 = -63.32766 RADIANCE_MAXIMUM_BAND_3 = 706.65613 RADIANCE_MINIMUM_BAND_3 = -58.35589 RADIANCE_MAXIMUM_BAND_4 = 595.89227 RADIANCE_MINIMUM_BAND_4 = -49.20898 RADIANCE_MAXIMUM_BAND_5 = 364.65634 RADIANCE_MINIMUM_BAND_5 = -30.11344 RADIANCE_MAXIMUM_BAND_6 = 90.68671 RADIANCE_MINIMUM_BAND_6 = -7.48894 RADIANCE_MAXIMUM_BAND_7 = 30.56628 RADIANCE_MINIMUM_BAND_7 = -2.52417 RADIANCE_MAXIMUM_BAND_8 = 674.38605 RADIANCE_MINIMUM_BAND_8 = -55.69102 RADIANCE_MAXIMUM_BAND_9 = 142.51598 RADIANCE_MINIMUM_BAND_9 = -11.76902 RADIANCE_MAXIMUM_BAND_10 = 22.00180 RADIANCE_MINIMUM_BAND_10 = 0.10033 RADIANCE_MAXIMUM_BAND_11 = 22.00180 RADIANCE_MINIMUM_BAND_11 = 0.10033 END_GROUP = MIN_MAX_RADIANCE GROUP = MIN_MAX_REFLECTANCE REFLECTANCE_MAXIMUM_BAND_1 = 1.210700 REFLECTANCE_MINIMUM_BAND_1 = -0.099980 REFLECTANCE_MAXIMUM_BAND_2 = 1.210700 REFLECTANCE_MINIMUM_BAND_2 = -0.099980 REFLECTANCE_MAXIMUM_BAND_3 = 1.210700 REFLECTANCE_MINIMUM_BAND_3 = -0.099980 REFLECTANCE_MAXIMUM_BAND_4 = 1.210700 REFLECTANCE_MINIMUM_BAND_4 = -0.099980 REFLECTANCE_MAXIMUM_BAND_5 = 1.210700 REFLECTANCE_MINIMUM_BAND_5 = -0.099980 REFLECTANCE_MAXIMUM_BAND_6 = 1.210700 REFLECTANCE_MINIMUM_BAND_6 = -0.099980 REFLECTANCE_MAXIMUM_BAND_7 = 1.210700 REFLECTANCE_MINIMUM_BAND_7 = -0.099980 REFLECTANCE_MAXIMUM_BAND_8 = 1.210700 REFLECTANCE_MINIMUM_BAND_8 = -0.099980 REFLECTANCE_MAXIMUM_BAND_9 = 1.210700 REFLECTANCE_MINIMUM_BAND_9 = -0.099980 END_GROUP = MIN_MAX_REFLECTANCE GROUP = MIN_MAX_PIXEL_VALUE QUANTIZE_CAL_MAX_BAND_1 = 65535 QUANTIZE_CAL_MIN_BAND_1 = 1 QUANTIZE_CAL_MAX_BAND_2 = 65535 QUANTIZE_CAL_MIN_BAND_2 = 1 QUANTIZE_CAL_MAX_BAND_3 = 65535 QUANTIZE_CAL_MIN_BAND_3 = 1 QUANTIZE_CAL_MAX_BAND_4 = 65535 QUANTIZE_CAL_MIN_BAND_4 = 1 QUANTIZE_CAL_MAX_BAND_5 = 65535 QUANTIZE_CAL_MIN_BAND_5 = 1 QUANTIZE_CAL_MAX_BAND_6 = 65535 QUANTIZE_CAL_MIN_BAND_6 = 1 QUANTIZE_CAL_MAX_BAND_7 = 65535 QUANTIZE_CAL_MIN_BAND_7 = 1 QUANTIZE_CAL_MAX_BAND_8 = 65535 QUANTIZE_CAL_MIN_BAND_8 = 1 QUANTIZE_CAL_MAX_BAND_9 = 65535 QUANTIZE_CAL_MIN_BAND_9 = 1 QUANTIZE_CAL_MAX_BAND_10 = 65535 QUANTIZE_CAL_MIN_BAND_10 = 1 QUANTIZE_CAL_MAX_BAND_11 = 65535 QUANTIZE_CAL_MIN_BAND_11 = 1 END_GROUP = MIN_MAX_PIXEL_VALUE GROUP = RADIOMETRIC_RESCALING RADIANCE_MULT_BAND_1 = 1.2371E-02 RADIANCE_MULT_BAND_2 = 1.2668E-02 RADIANCE_MULT_BAND_3 = 1.1674E-02 RADIANCE_MULT_BAND_4 = 9.8438E-03 RADIANCE_MULT_BAND_5 = 6.0239E-03 RADIANCE_MULT_BAND_6 = 1.4981E-03 RADIANCE_MULT_BAND_7 = 5.0494E-04 RADIANCE_MULT_BAND_8 = 1.1140E-02 RADIANCE_MULT_BAND_9 = 2.3543E-03 RADIANCE_MULT_BAND_10 = 3.3420E-04 RADIANCE_MULT_BAND_11 = 3.3420E-04 RADIANCE_ADD_BAND_1 = -61.85505 RADIANCE_ADD_BAND_2 = -63.34032 RADIANCE_ADD_BAND_3 = -58.36757 RADIANCE_ADD_BAND_4 = -49.21882 RADIANCE_ADD_BAND_5 = -30.11946 RADIANCE_ADD_BAND_6 = -7.49044 RADIANCE_ADD_BAND_7 = -2.52468 RADIANCE_ADD_BAND_8 = -55.70216 RADIANCE_ADD_BAND_9 = -11.77137 RADIANCE_ADD_BAND_10 = 0.10000 RADIANCE_ADD_BAND_11 = 0.10000 REFLECTANCE_MULT_BAND_1 = 2.0000E-05 REFLECTANCE_MULT_BAND_2 = 2.0000E-05 REFLECTANCE_MULT_BAND_3 = 2.0000E-05 REFLECTANCE_MULT_BAND_4 = 2.0000E-05 REFLECTANCE_MULT_BAND_5 = 2.0000E-05 REFLECTANCE_MULT_BAND_6 = 2.0000E-05 REFLECTANCE_MULT_BAND_7 = 2.0000E-05 REFLECTANCE_MULT_BAND_8 = 2.0000E-05 REFLECTANCE_MULT_BAND_9 = 2.0000E-05 REFLECTANCE_ADD_BAND_1 = -0.100000 REFLECTANCE_ADD_BAND_2 = -0.100000 REFLECTANCE_ADD_BAND_3 = -0.100000 REFLECTANCE_ADD_BAND_4 = -0.100000 REFLECTANCE_ADD_BAND_5 = -0.100000 REFLECTANCE_ADD_BAND_6 = -0.100000 REFLECTANCE_ADD_BAND_7 = -0.100000 REFLECTANCE_ADD_BAND_8 = -0.100000 REFLECTANCE_ADD_BAND_9 = -0.100000 END_GROUP = RADIOMETRIC_RESCALING GROUP = TIRS_THERMAL_CONSTANTS K1_CONSTANT_BAND_10 = 774.8853 K2_CONSTANT_BAND_10 = 1321.0789 K1_CONSTANT_BAND_11 = 480.8883 K2_CONSTANT_BAND_11 = 1201.1442 END_GROUP = TIRS_THERMAL_CONSTANTS GROUP = PROJECTION_PARAMETERS MAP_PROJECTION = "UTM" DATUM = "WGS84" ELLIPSOID = "WGS84" UTM_ZONE = 29 GRID_CELL_SIZE_PANCHROMATIC = 15.00 GRID_CELL_SIZE_REFLECTIVE = 30.00 GRID_CELL_SIZE_THERMAL = 30.00 ORIENTATION = "NORTH_UP" RESAMPLING_OPTION = "CUBIC_CONVOLUTION" END_GROUP = PROJECTION_PARAMETERS END_GROUP = L1_METADATA_FILE END snakemake-5.10.0/tests/test_remote_http/expected-results/landsat-data.txt.gz000066400000000000000000000037041361131222100273000ustar00rootroot00000000000000DZlandsat-data.txt[SD;H@,Ƙ~VދG#=:O\$g4j5Կ~ve>骭w? lϙII1/vSoݷyyU:?%؟o?Ǯhw?w'﫳m?eHXp'+$6iVfH%0AũDh.uuhS3: i |21_Y iUYje{~4 &> D=O}"݋xSaKi4yyMu4_L7 Xő$+vs Myy3K!Sߜ`;+׮M;apԭJYe㱳6ufNs!{{V6mU[3}э<LqKm}ʌLOYnl~nsyd{nD&ų>Iއ%Dȥ"8Rb2S(+Q4b\9ڋe8t)ZtJDX>G-;($Q, O¯5H Aߦ㢰o8b>Ã,2}nq-y DVA1]@lUx $VAcx$Uz VA=hhrg6)rsr% iy)h't^<:J;G_{ 5w$Pobf/! jl.D9!3QFg]7FA@}DewL99A%cΟ[5U{{e+a%f'N?Hꆥ۸6ٞCVj9/4Uwe%ƭF(nTjtG@?OK-z5g Ýp](M[=? c."sGXvãXq?HY͋uC-}I(fTu(h[Uɗs6a6a6a7lræ&62lZj:˔L^sjv_8 21H-ty9s I)ϣn@s{M$9ݞ cs"$1_Z uBsl0)00 `; `w<0DCaC0 `; M2tCZ/1XSSXQ 8luގBnCհr sizes.txt" snakemake-5.10.0/tests/test_remote_ncbi/expected-results/000077500000000000000000000000001361131222100235135ustar00rootroot00000000000000snakemake-5.10.0/tests/test_remote_ncbi/expected-results/sizes.txt000066400000000000000000000001161361131222100254070ustar00rootroot000000000000005801 KY785484.1.fasta 5255 KY785481.1.fasta 5318 KY785480.1.fasta 16374 total snakemake-5.10.0/tests/test_remote_ncbi_simple/000077500000000000000000000000001361131222100215645ustar00rootroot00000000000000snakemake-5.10.0/tests/test_remote_ncbi_simple/Snakefile000066400000000000000000000006211361131222100234070ustar00rootroot00000000000000from snakemake.remote.NCBI import RemoteProvider as NCBIRemoteProvider NCBI = NCBIRemoteProvider(email="someone@example.com") # email required by NCBI to prevent abuse rule all: input: "sizes.txt" rule download_and_count: input: NCBI.remote("KY785484.1.fasta", db="nuccore") output: "sizes.txt" shell: r"wc -c {input} | sed 's/^[ \t]*//' > sizes.txt" snakemake-5.10.0/tests/test_remote_ncbi_simple/expected-results/000077500000000000000000000000001361131222100250645ustar00rootroot00000000000000snakemake-5.10.0/tests/test_remote_ncbi_simple/expected-results/sizes.txt000066400000000000000000000000271361131222100267610ustar00rootroot0000000000000010861 KY785484.1.fasta snakemake-5.10.0/tests/test_remote_sftp/000077500000000000000000000000001361131222100202545ustar00rootroot00000000000000snakemake-5.10.0/tests/test_remote_sftp/Snakefile000066400000000000000000000003741361131222100221040ustar00rootroot00000000000000from snakemake.remote.SFTP import RemoteProvider SFTP = RemoteProvider(username="demo", password="password") rule a: input: SFTP.remote("test.rebex.net/readme.txt") output: "readme.txt" shell: "cp {input} {output}" snakemake-5.10.0/tests/test_remote_sftp/expected-results/000077500000000000000000000000001361131222100235545ustar00rootroot00000000000000snakemake-5.10.0/tests/test_remote_sftp/expected-results/readme.txt000066400000000000000000000006231361131222100255530ustar00rootroot00000000000000Welcome, you are connected to an FTP or SFTP server used for testing purposes by Rebex FTP/SSL or Rebex SFTP sample code. Only read access is allowed and the FTP download speed is limited to 16KBps. For infomation about Rebex FTP/SSL, Rebex SFTP and other Rebex .NET components, please visit our website at http://www.rebex.net/ For feedback and support, contact support@rebex.net Thanks! snakemake-5.10.0/tests/test_report/000077500000000000000000000000001361131222100172405ustar00rootroot00000000000000snakemake-5.10.0/tests/test_report/.snakemake/000077500000000000000000000000001361131222100212555ustar00rootroot00000000000000snakemake-5.10.0/tests/test_report/.snakemake/metadata/000077500000000000000000000000001361131222100230355ustar00rootroot00000000000000snakemake-5.10.0/tests/test_report/.snakemake/metadata/dGVzdC40Lm91dA==000066400000000000000000000015301361131222100253460ustar00rootroot00000000000000{"version": null, "code": "gAMoQxB0AGQBfA1kAo0CAQBkAFMAcQAoWAUAAABpbnB1dHEBWAYAAABvdXRwdXRxAlgGAAAAcGFyYW1zcQNYCQAAAHdpbGRjYXJkc3EEWAcAAAB0aHJlYWRzcQVYCQAAAHJlc291cmNlc3EGWAMAAABsb2dxB1gHAAAAdmVyc2lvbnEIWAQAAABydWxlcQlYCQAAAGNvbmRhX2VudnEKWA8AAABzaW5ndWxhcml0eV9pbWdxC1gQAAAAc2luZ3VsYXJpdHlfYXJnc3EMWA8AAAB1c2Vfc2luZ3VsYXJpdHlxDVgMAAAAYmVuY2hfcmVjb3JkcQ5YBQAAAGpvYmlkcQ90cRBdcREoTlgoAAAAc2xlZXAgYHNodWYgLWkgMS0zIC1uIDFgOyB0b3VjaCB7b3V0cHV0fXESaA6FcRNlWAUAAABzaGVsbHEUhXEVdHEWLg==", "rule": "c", "input": [], "log": [], "params": [], "shellcmd": "sleep `shuf -i 1-3 -n 1`; touch test.4.out", "incomplete": false, "starttime": 1526474374.13434, "endtime": 1526474376.911341, "job_hash": -4193666763668718067, "conda_env": "Y2hhbm5lbHM6CiAgLSBjb25kYS1mb3JnZQpkZXBlbmRlbmNpZXM6CiAgLSBtYWtlCg==", "singularity_img_url": "docker://continuumio/miniconda3:4.4.10"}snakemake-5.10.0/tests/test_report/.snakemake/metadata/dGVzdC41Lm91dA==000066400000000000000000000015321361131222100253510ustar00rootroot00000000000000{"version": null, "code": "gAMoQxB0AGQBfA1kAo0CAQBkAFMAcQAoWAUAAABpbnB1dHEBWAYAAABvdXRwdXRxAlgGAAAAcGFyYW1zcQNYCQAAAHdpbGRjYXJkc3EEWAcAAAB0aHJlYWRzcQVYCQAAAHJlc291cmNlc3EGWAMAAABsb2dxB1gHAAAAdmVyc2lvbnEIWAQAAABydWxlcQlYCQAAAGNvbmRhX2VudnEKWA8AAABzaW5ndWxhcml0eV9pbWdxC1gQAAAAc2luZ3VsYXJpdHlfYXJnc3EMWA8AAAB1c2Vfc2luZ3VsYXJpdHlxDVgMAAAAYmVuY2hfcmVjb3JkcQ5YBQAAAGpvYmlkcQ90cRBdcREoTlgoAAAAc2xlZXAgYHNodWYgLWkgMS0zIC1uIDFgOyB0b3VjaCB7b3V0cHV0fXESaA6FcRNlWAUAAABzaGVsbHEUhXEVdHEWLg==", "rule": "c", "input": [], "log": [], "params": [], "shellcmd": "sleep `shuf -i 1-3 -n 1`; touch test.5.out", "incomplete": false, "starttime": 1526474375.8873405, "endtime": 1526474377.318341, "job_hash": -2933524654530661864, "conda_env": "Y2hhbm5lbHM6CiAgLSBjb25kYS1mb3JnZQpkZXBlbmRlbmNpZXM6CiAgLSBtYWtlCg==", "singularity_img_url": "docker://continuumio/miniconda3:4.4.10"}snakemake-5.10.0/tests/test_report/.snakemake/metadata/dGVzdC42Lm91dA==000066400000000000000000000015321361131222100253520ustar00rootroot00000000000000{"version": null, "code": "gAMoQxB0AGQBfA1kAo0CAQBkAFMAcQAoWAUAAABpbnB1dHEBWAYAAABvdXRwdXRxAlgGAAAAcGFyYW1zcQNYCQAAAHdpbGRjYXJkc3EEWAcAAAB0aHJlYWRzcQVYCQAAAHJlc291cmNlc3EGWAMAAABsb2dxB1gHAAAAdmVyc2lvbnEIWAQAAABydWxlcQlYCQAAAGNvbmRhX2VudnEKWA8AAABzaW5ndWxhcml0eV9pbWdxC1gQAAAAc2luZ3VsYXJpdHlfYXJnc3EMWA8AAAB1c2Vfc2luZ3VsYXJpdHlxDVgMAAAAYmVuY2hfcmVjb3JkcQ5YBQAAAGpvYmlkcQ90cRBdcREoTlgoAAAAc2xlZXAgYHNodWYgLWkgMS0zIC1uIDFgOyB0b3VjaCB7b3V0cHV0fXESaA6FcRNlWAUAAABzaGVsbHEUhXEVdHEWLg==", "rule": "c", "input": [], "log": [], "params": [], "shellcmd": "sleep `shuf -i 1-3 -n 1`; touch test.6.out", "incomplete": false, "starttime": 1526474374.1203399, "endtime": 1526474375.9023407, "job_hash": 8643010067298761385, "conda_env": "Y2hhbm5lbHM6CiAgLSBjb25kYS1mb3JnZQpkZXBlbmRlbmNpZXM6CiAgLSBtYWtlCg==", "singularity_img_url": "docker://continuumio/miniconda3:4.4.10"}snakemake-5.10.0/tests/test_report/.snakemake/metadata/dGVzdC43Lm91dA==000066400000000000000000000015311361131222100253520ustar00rootroot00000000000000{"version": null, "code": "gAMoQxB0AGQBfA1kAo0CAQBkAFMAcQAoWAUAAABpbnB1dHEBWAYAAABvdXRwdXRxAlgGAAAAcGFyYW1zcQNYCQAAAHdpbGRjYXJkc3EEWAcAAAB0aHJlYWRzcQVYCQAAAHJlc291cmNlc3EGWAMAAABsb2dxB1gHAAAAdmVyc2lvbnEIWAQAAABydWxlcQlYCQAAAGNvbmRhX2VudnEKWA8AAABzaW5ndWxhcml0eV9pbWdxC1gQAAAAc2luZ3VsYXJpdHlfYXJnc3EMWA8AAAB1c2Vfc2luZ3VsYXJpdHlxDVgMAAAAYmVuY2hfcmVjb3JkcQ5YBQAAAGpvYmlkcQ90cRBdcREoTlgoAAAAc2xlZXAgYHNodWYgLWkgMS0zIC1uIDFgOyB0b3VjaCB7b3V0cHV0fXESaA6FcRNlWAUAAABzaGVsbHEUhXEVdHEWLg==", "rule": "c", "input": [], "log": [], "params": [], "shellcmd": "sleep `shuf -i 1-3 -n 1`; touch test.7.out", "incomplete": false, "starttime": 1526474374.12534, "endtime": 1526474377.9363413, "job_hash": -2922925998717494899, "conda_env": "Y2hhbm5lbHM6CiAgLSBjb25kYS1mb3JnZQpkZXBlbmRlbmNpZXM6CiAgLSBtYWtlCg==", "singularity_img_url": "docker://continuumio/miniconda3:4.4.10"}snakemake-5.10.0/tests/test_report/.snakemake/metadata/dGVzdC44Lm91dA==000066400000000000000000000015301361131222100253520ustar00rootroot00000000000000{"version": null, "code": "gAMoQxB0AGQBfA1kAo0CAQBkAFMAcQAoWAUAAABpbnB1dHEBWAYAAABvdXRwdXRxAlgGAAAAcGFyYW1zcQNYCQAAAHdpbGRjYXJkc3EEWAcAAAB0aHJlYWRzcQVYCQAAAHJlc291cmNlc3EGWAMAAABsb2dxB1gHAAAAdmVyc2lvbnEIWAQAAABydWxlcQlYCQAAAGNvbmRhX2VudnEKWA8AAABzaW5ndWxhcml0eV9pbWdxC1gQAAAAc2luZ3VsYXJpdHlfYXJnc3EMWA8AAAB1c2Vfc2luZ3VsYXJpdHlxDVgMAAAAYmVuY2hfcmVjb3JkcQ5YBQAAAGpvYmlkcQ90cRBdcREoTlgoAAAAc2xlZXAgYHNodWYgLWkgMS0zIC1uIDFgOyB0b3VjaCB7b3V0cHV0fXESaA6FcRNlWAUAAABzaGVsbHEUhXEVdHEWLg==", "rule": "c", "input": [], "log": [], "params": [], "shellcmd": "sleep `shuf -i 1-3 -n 1`; touch test.8.out", "incomplete": false, "starttime": 1526474374.11534, "endtime": 1526474377.9283412, "job_hash": 2309792234881268873, "conda_env": "Y2hhbm5lbHM6CiAgLSBjb25kYS1mb3JnZQpkZXBlbmRlbmNpZXM6CiAgLSBtYWtlCg==", "singularity_img_url": "docker://continuumio/miniconda3:4.4.10"}snakemake-5.10.0/tests/test_report/.snakemake/metadata/dGVzdC45Lm91dA==000066400000000000000000000015301361131222100253530ustar00rootroot00000000000000{"version": null, "code": "gAMoQxB0AGQBfA1kAo0CAQBkAFMAcQAoWAUAAABpbnB1dHEBWAYAAABvdXRwdXRxAlgGAAAAcGFyYW1zcQNYCQAAAHdpbGRjYXJkc3EEWAcAAAB0aHJlYWRzcQVYCQAAAHJlc291cmNlc3EGWAMAAABsb2dxB1gHAAAAdmVyc2lvbnEIWAQAAABydWxlcQlYCQAAAGNvbmRhX2VudnEKWA8AAABzaW5ndWxhcml0eV9pbWdxC1gQAAAAc2luZ3VsYXJpdHlfYXJnc3EMWA8AAAB1c2Vfc2luZ3VsYXJpdHlxDVgMAAAAYmVuY2hfcmVjb3JkcQ5YBQAAAGpvYmlkcQ90cRBdcREoTlgoAAAAc2xlZXAgYHNodWYgLWkgMS0zIC1uIDFgOyB0b3VjaCB7b3V0cHV0fXESaA6FcRNlWAUAAABzaGVsbHEUhXEVdHEWLg==", "rule": "c", "input": [], "log": [], "params": [], "shellcmd": "sleep `shuf -i 1-3 -n 1`; touch test.9.out", "incomplete": false, "starttime": 1526474374.10834, "endtime": 1526474375.8943405, "job_hash": 3703979124286100515, "conda_env": "Y2hhbm5lbHM6CiAgLSBjb25kYS1mb3JnZQpkZXBlbmRlbmNpZXM6CiAgLSBtYWtlCg==", "singularity_img_url": "docker://continuumio/miniconda3:4.4.10"}snakemake-5.10.0/tests/test_report/.snakemake/metadata/dGVzdC4wLm91dA==000066400000000000000000000015311361131222100254560ustar00rootroot00000000000000{"version": null, "code": "gAMoQxB0AGQBfA1kAo0CAQBkAFMAcQAoWAUAAABpbnB1dHEBWAYAAABvdXRwdXRxAlgGAAAAcGFyYW1zcQNYCQAAAHdpbGRjYXJkc3EEWAcAAAB0aHJlYWRzcQVYCQAAAHJlc291cmNlc3EGWAMAAABsb2dxB1gHAAAAdmVyc2lvbnEIWAQAAABydWxlcQlYCQAAAGNvbmRhX2VudnEKWA8AAABzaW5ndWxhcml0eV9pbWdxC1gQAAAAc2luZ3VsYXJpdHlfYXJnc3EMWA8AAAB1c2Vfc2luZ3VsYXJpdHlxDVgMAAAAYmVuY2hfcmVjb3JkcQ5YBQAAAGpvYmlkcQ90cRBdcREoTlgoAAAAc2xlZXAgYHNodWYgLWkgMS0zIC1uIDFgOyB0b3VjaCB7b3V0cHV0fXESaA6FcRNlWAUAAABzaGVsbHEUhXEVdHEWLg==", "rule": "c", "input": [], "log": [], "params": [], "shellcmd": "sleep `shuf -i 1-3 -n 1`; touch test.0.out", "incomplete": false, "starttime": 1526474375.8993406, "endtime": 1526474379.3473418, "job_hash": 835220792718358845, "conda_env": "Y2hhbm5lbHM6CiAgLSBjb25kYS1mb3JnZQpkZXBlbmRlbmNpZXM6CiAgLSBtYWtlCg==", "singularity_img_url": "docker://continuumio/miniconda3:4.4.10"}snakemake-5.10.0/tests/test_report/.snakemake/metadata/dGVzdC4xLm91dA==000066400000000000000000000015331361131222100254610ustar00rootroot00000000000000{"version": null, "code": "gAMoQxB0AGQBfA1kAo0CAQBkAFMAcQAoWAUAAABpbnB1dHEBWAYAAABvdXRwdXRxAlgGAAAAcGFyYW1zcQNYCQAAAHdpbGRjYXJkc3EEWAcAAAB0aHJlYWRzcQVYCQAAAHJlc291cmNlc3EGWAMAAABsb2dxB1gHAAAAdmVyc2lvbnEIWAQAAABydWxlcQlYCQAAAGNvbmRhX2VudnEKWA8AAABzaW5ndWxhcml0eV9pbWdxC1gQAAAAc2luZ3VsYXJpdHlfYXJnc3EMWA8AAAB1c2Vfc2luZ3VsYXJpdHlxDVgMAAAAYmVuY2hfcmVjb3JkcQ5YBQAAAGpvYmlkcQ90cRBdcREoTlgoAAAAc2xlZXAgYHNodWYgLWkgMS0zIC1uIDFgOyB0b3VjaCB7b3V0cHV0fXESaA6FcRNlWAUAAABzaGVsbHEUhXEVdHEWLg==", "rule": "c", "input": [], "log": [], "params": [], "shellcmd": "sleep `shuf -i 1-3 -n 1`; touch test.1.out", "incomplete": false, "starttime": 1526474374.1403399, "endtime": 1526474376.8773408, "job_hash": -6430540820858145098, "conda_env": "Y2hhbm5lbHM6CiAgLSBjb25kYS1mb3JnZQpkZXBlbmRlbmNpZXM6CiAgLSBtYWtlCg==", "singularity_img_url": "docker://continuumio/miniconda3:4.4.10"}snakemake-5.10.0/tests/test_report/.snakemake/metadata/dGVzdC4yLm91dA==000066400000000000000000000015301361131222100254570ustar00rootroot00000000000000{"version": null, "code": "gAMoQxB0AGQBfA1kAo0CAQBkAFMAcQAoWAUAAABpbnB1dHEBWAYAAABvdXRwdXRxAlgGAAAAcGFyYW1zcQNYCQAAAHdpbGRjYXJkc3EEWAcAAAB0aHJlYWRzcQVYCQAAAHJlc291cmNlc3EGWAMAAABsb2dxB1gHAAAAdmVyc2lvbnEIWAQAAABydWxlcQlYCQAAAGNvbmRhX2VudnEKWA8AAABzaW5ndWxhcml0eV9pbWdxC1gQAAAAc2luZ3VsYXJpdHlfYXJnc3EMWA8AAAB1c2Vfc2luZ3VsYXJpdHlxDVgMAAAAYmVuY2hfcmVjb3JkcQ5YBQAAAGpvYmlkcQ90cRBdcREoTlgoAAAAc2xlZXAgYHNodWYgLWkgMS0zIC1uIDFgOyB0b3VjaCB7b3V0cHV0fXESaA6FcRNlWAUAAABzaGVsbHEUhXEVdHEWLg==", "rule": "c", "input": [], "log": [], "params": [], "shellcmd": "sleep `shuf -i 1-3 -n 1`; touch test.2.out", "incomplete": false, "starttime": 1526474374.11134, "endtime": 1526474375.8843405, "job_hash": 7606400900657219655, "conda_env": "Y2hhbm5lbHM6CiAgLSBjb25kYS1mb3JnZQpkZXBlbmRlbmNpZXM6CiAgLSBtYWtlCg==", "singularity_img_url": "docker://continuumio/miniconda3:4.4.10"}snakemake-5.10.0/tests/test_report/.snakemake/metadata/dGVzdC4zLm91dA==000066400000000000000000000015321361131222100254620ustar00rootroot00000000000000{"version": null, "code": "gAMoQxB0AGQBfA1kAo0CAQBkAFMAcQAoWAUAAABpbnB1dHEBWAYAAABvdXRwdXRxAlgGAAAAcGFyYW1zcQNYCQAAAHdpbGRjYXJkc3EEWAcAAAB0aHJlYWRzcQVYCQAAAHJlc291cmNlc3EGWAMAAABsb2dxB1gHAAAAdmVyc2lvbnEIWAQAAABydWxlcQlYCQAAAGNvbmRhX2VudnEKWA8AAABzaW5ndWxhcml0eV9pbWdxC1gQAAAAc2luZ3VsYXJpdHlfYXJnc3EMWA8AAAB1c2Vfc2luZ3VsYXJpdHlxDVgMAAAAYmVuY2hfcmVjb3JkcQ5YBQAAAGpvYmlkcQ90cRBdcREoTlgoAAAAc2xlZXAgYHNodWYgLWkgMS0zIC1uIDFgOyB0b3VjaCB7b3V0cHV0fXESaA6FcRNlWAUAAABzaGVsbHEUhXEVdHEWLg==", "rule": "c", "input": [], "log": [], "params": [], "shellcmd": "sleep `shuf -i 1-3 -n 1`; touch test.3.out", "incomplete": false, "starttime": 1526474374.1303399, "endtime": 1526474377.8753412, "job_hash": 7995860855952686702, "conda_env": "Y2hhbm5lbHM6CiAgLSBjb25kYS1mb3JnZQpkZXBlbmRlbmNpZXM6CiAgLSBtYWtlCg==", "singularity_img_url": "docker://continuumio/miniconda3:4.4.10"}snakemake-5.10.0/tests/test_report/Snakefile000066400000000000000000000016541361131222100210720ustar00rootroot00000000000000 report: "report/workflow.rst" rule all: input: ["fig1.svg", "fig2.png", "test.csv"] rule c: output: "test.{i}.out" singularity: "docker://continuumio/miniconda3:4.4.10" conda: "envs/test.yaml" shell: "sleep `shuf -i 1-3 -n 1`; touch {output}" rule a: input: expand("test.{i}.out", i=range(10)) output: report("fig1.svg", caption="report/fig1.rst", category="Step 1") shell: "sleep `shuf -i 1-3 -n 1`; cp data/fig1.svg {output}" rule b: input: expand("test.{i}.out", i=range(10)) output: report("fig2.png", caption="report/fig2.rst", category="Step 2") shell: "sleep `shuf -i 1-3 -n 1`; cp data/fig2.png {output}" rule d: output: report("test.csv", caption="report/table.rst") shell: "curl http://samplecsvs.s3.amazonaws.com/Sacramentorealestatetransactions.csv > {output}" snakemake-5.10.0/tests/test_report/data/000077500000000000000000000000001361131222100201515ustar00rootroot00000000000000snakemake-5.10.0/tests/test_report/data/fig1.svg000066400000000000000000000672611361131222100215340ustar00rootroot00000000000000 snakemake-5.10.0/tests/test_report/data/fig2.png000066400000000000000000000216011361131222100215060ustar00rootroot00000000000000PNG  IHDR XvpsBIT|d pHYsaa?i IDATxmy{ fY F$dC BoElCHgRbq1c6m44`CiG v&ц l /EY(JP^dw9{k8㜳[U*J!@4H#@4H#@4H#@4H#@4H#@4H#@4H#@4H#@4H#@4H#@4H#@4H#@4H#@4H#@4H#@4H#@4H#@4H#@4H#@4H#@4H#@4H#@4H#@4H#@4H#@ʬ#// QS~>}zL4).\ z*~GBTJRCG/b\tEq饗Ɗ+N ނU&{쉻+""^~x %@dժU1x7n\z 2$0^y啢B2ټys6l#"?x{vJu։^ e'VZ;w /qQWWw=k׮w|;fϟ-*z33sάwۛ1cFlݺ3Ʒ? vg~ٳS)Yfw7/?r㬳ΊiӦw1qĄ)C:rfzΙs{sN Ikd e2a„'>ַqeţ>+V??#F="Z[[cձe˖khhތ)%Kmmmrʸ bѢEq-=ꢽ=,Xk׮۷ѣcz̷; eTSS . = Kuuu]w]y(JERQFū/r 4ϟCv%ZZZFx˗/˗wwނ?H~ǀ-'&OwI&4Q-XeuԵCŇ>&by-oyKL:56l/ w}w@:RFcٲeq=ċ/Ç3fwoۋ 27o^̛713 @ @ @ @ @ @ @ @ @ @ @ @ @ @ @ @ @ @ @ @ @ @ @ @ @ @ @ @ @ @ @ @ @ @ @ @ @ @ @ @ @ 뮨= B$ٹsg|_FUUU@!jRq455g-z(W@G?|0-ZR+ T,Rfyŧ>hll,zz+Ν3f(z3`ْ%KbǎQ={DSSSlٲQs= . Fmmm v8H~1lذ7o^ѣKk׮-z~[do|#-Z;w~z*? RWW1gΜ3fLG)zz.ڎ|f FiFiFiFiFiFiFiFiFiFiFiFiFiFiFiFiFiFiFiFiFiFiFiFiFiFiFiFiFiFiFiFiFiFiFiFiFiFiFiFiFiH=1shhhFmmm455Ųeˊ QSَ;⥗^9sD}}}߿?VXGc۶m UUT*=D%ycҤI}nuttĤIb1qĂ&xy+Yuuu5*:묢Gtނ`x⡇x(X`A]6<5551yhmm@$g>""&޸ <MMMe˖n7lWvP+V?>7K.-z,ێöl ,HӉW@7.ƍgώ+2ϟf͊<v>=@&@ |$_5|ɘ0aQϟ??ZKKKdk˗˻]ۻwoA/"u,-m݀3VM͉f. /3 euԵ^{-(ɓ'q7 UF7xc۷/.첨ݻwDzebӦMkV\kkk^Dohht!@~f|k_{.SLŋ?(hoos@8&RF\ꢭ18 FiFiFiFiFiFiFiFiFiFiFiFiFiFiFiFiFiFiFiFiFiFiFiFiFiFiFiFiFiFiFiFiFiFiFiFiFiFiFiFiFiH=q7Gccc 4(FͱyGB=@/})c̙qGggg,^8&N=X466=" e~6.䒨1777)p:'@hԩG];vl]70g@JxgbذaEBꊹsFccc7.cܹUh@ He˖Ů] _BѣPaMMMe˖n7lW+h:Rx$ƍ㦛n?^8Tn8l˖-`J$@޽;8bŊQUUUHTkqS[ qWNj/W#FϏCv---~}z*cݮݻiRfӧSO=VwozϢEbĉ QIPi1iҤ&:ͱf͚xbʔ)EDl|;ٳ JW>J#@?iTUU??pǪꢽ=,Xk׮FMMML<9Z[[} ^ )Gyhkk+z FiFiFiFiFiFiFiFiFiFiFiFiFiFiFiFiFiFiFiFiFiFiFiFiFiFiFiFiFiFiFiFiFiFiFiFiFiFiFiFiFiHqwUW]o}[:.]ZXPRF]]]qwƓO>&L2ݻw֭[_rk˗//z33sάw[9qnd etg#"T*zk\x\sM<#qƂ 6*Mׯc&~z{ny1f̘n׆ Rq wyg=:&L>J޵ak_җ=fΜ_|qtvvŋcĉcEccq]˹Vicǎx饗bΜ9Q__+VG?ضm[|?k}9*m~Ν;_b 8P+%j͚5ҟvرcKMMM'KUUU|ȵyW|:˹Jׯ/W^y3ϔJRiݺuҥKOJ޵[ڏk͛K{ni'w/Vv,*M0tykrf\ҴiJϷo=-XebŊoȵs9'>OF{{{<'wĈq 76lذ5kV?CkeH}9JR۷/:TQOg}v ><"{w/vXԩS cǎw]q[ɻ֗s;vXcԨQqYgykrvX%ڏ~xcѢEGs雱o=#@'?I\tE1hРn/䒈;qģ_r%شiө4җs;/!C믏z,k]{+""&n]ݹU-Y$v?{t}Rf/s9{9p@=fΜ3g<뮻.ʸ⮻}k~3\%Z_ص7lܸ1nhjj'|][ڭf͊]vŲeoZέw瞋 … Gڷ e6`xW~#3ݩŔ)SNWJ޵Svmqy+VxJ۵7܎vmܸq1nܸ={v\y15kqwƮ܎RvoaÆżyz|})#GBQ___{tG?|g*yʡRv^:^|1běczwnS)> /O>qc׎v2v<}6o7b޼ysضm[l۶-8jl߾_}Rf~cӦMo߾n׬Y&L8&L3Ϛ5kbqEO}9uuudw*a8ӧOz*1w}k=㩄];og>c*}׎dx=-oۏZvmlڴ)ƌwyqo=#@lƌqС#x'|{xoq8x`{yw{ڳ><@L>ޙ/u?韢#kc~СCk֬x Lrٵrnk˂ 7IDAT_{ȇz;;;ӗs]?~|\2rhllѣG'?T*sҚcʕq뭷FCCC,]4֭[o^ziDSضm[OռKsܑsx /,*ޞۅ^'NI&Ő!C#ox,^8v%K 7pբ[n%l׎V6{c>zٳ#¿~U_έRwp۷/.첨ݻwDzebӦM"®[L6-{#)+ρJJ#G,{)S~t{Μ9sJե۷wϗ4lذK_~ytޞ^z]:th.]pngϞ/!\P*UUUKG3kGUM6#ϳk*uۿۥ#F:Rmmmk)ZZw}9Jݵ6mZiݮٷ g@4H#@4H#@4H#@4H#@4H#@4H#@4H#@4H#@4H#@4H#@4H#@4H#@4H#@4H#@4H#@4H#@4H#@4H#@4H#@4ܬSSIENDB`snakemake-5.10.0/tests/test_report/envs/000077500000000000000000000000001361131222100202135ustar00rootroot00000000000000snakemake-5.10.0/tests/test_report/envs/test.yaml000066400000000000000000000000611361131222100220530ustar00rootroot00000000000000channels: - conda-forge dependencies: - make snakemake-5.10.0/tests/test_report/expected-results/000077500000000000000000000000001361131222100225405ustar00rootroot00000000000000snakemake-5.10.0/tests/test_report/expected-results/report.html000066400000000000000000116166561361131222100247670ustar00rootroot00000000000000 Snakemake Report

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Workflow

This is the workflow description. Test reference fig1.svg.

Detailed software versions can be found under Rules.

Results

Workflow resultes
File Size Description Job properties
test.csv.html 113.2 kB

An example table.
Job properties
Ruled
Workflow resultes
File Size Description Job properties
fig1.svg 28.3 kB

This is a caption with a link.
Job properties
Rulea
Workflow resultes
File Size Description Job properties
fig2.png 9.1 kB

Some math ∑ii2.
Job properties
Ruleb

Statistics

If the workflow has been executed in cluster/cloud, runtimes include the waiting time in the queue.

Rules

Workflow rules
Rule Jobs Output Singularity Conda environment Code
a 1
  • fig1.svg
 
1
sleep `shuf -i 1-3 -n 1`; cp data/fig1.svg {output}
b 1
  • fig2.png
 
1
sleep `shuf -i 1-3 -n 1`; cp data/fig2.png {output}
d 1
  • test.csv
 
1
curl http://samplecsvs.s3.amazonaws.com/Sacramentorealestatetransactions.csv > {output}
c 10
  • test.0.out
  • test.1.out
  • test.2.out
  • test.3.out
  • test.4.out
  • test.5.out
  • test.6.out
  • test.7.out
  • test.8.out
  • test.9.out
 docker://continuumio/miniconda3:4.4.10
  • make
 
1
sleep `shuf -i 1-3 -n 1`; touch {output}
snakemake-5.10.0/tests/test_report/fig1.svg000066400000000000000000000672611361131222100206230ustar00rootroot00000000000000 snakemake-5.10.0/tests/test_report/fig2.png000066400000000000000000000216011361131222100205750ustar00rootroot00000000000000PNG  IHDR XvpsBIT|d pHYsaa?i IDATxmy{ fY F$dC BoElCHgRbq1c6m44`CiG v&ц l /EY(JP^dw9{k8㜳[U*J!@4H#@4H#@4H#@4H#@4H#@4H#@4H#@4H#@4H#@4H#@4H#@4H#@4H#@4H#@4H#@4H#@4H#@4H#@4H#@4H#@4H#@4H#@4H#@4H#@4H#@ʬ#// QS~>}zL4).\ z*~GBTJRCG/b\tEq饗Ɗ+N ނU&{쉻+""^~x %@dժU1x7n\z 2$0^y啢B2ټys6l#"?x{vJu։^ e'VZ;w /qQWWw=k׮w|;fϟ-*z33sάwۛ1cFlݺ3Ʒ? vg~ٳS)Yfw7/?r㬳ΊiӦw1qĄ)C:rfzΙs{sN Ikd e2a„'>ַqeţ>+V??#F="Z[[cձe˖khhތ)%Kmmmrʸ bѢEq-=ꢽ=,Xk׮۷ѣcz̷; eTSS . = Kuuu]w]y(JERQFū/r 4ϟCv%ZZZFx˗/˗wwނ?H~ǀ-'&OwI&4Q-XeuԵCŇ>&by-oyKL:56l/ w}w@:RFcٲeq=ċ/Ç3fwoۋ 27o^̛713 @ @ @ @ @ @ @ @ @ @ @ @ @ @ @ @ @ @ @ @ @ @ @ @ @ @ @ @ @ @ @ @ @ @ @ @ @ @ @ @ @ 뮨= B$ٹsg|_FUUU@!jRq455g-z(W@G?|0-ZR+ T,Rfyŧ>hll,zz+Ν3f(z3`ْ%KbǎQ={DSSSlٲQs= . Fmmm v8H~1lذ7o^ѣKk׮-z~[do|#-Z;w~z*? RWW1gΜ3fLG)zz.ڎ|f FiFiFiFiFiFiFiFiFiFiFiFiFiFiFiFiFiFiFiFiFiFiFiFiFiFiFiFiFiFiFiFiFiFiFiFiFiFiFiFiFiH=1shhhFmmm455Ųeˊ QSَ;⥗^9sD}}}߿?VXGc۶m UUT*=D%ycҤI}nuttĤIb1qĂ&xy+Yuuu5*:묢Gtނ`x⡇x(X`A]6<5551yhmm@$g>""&޸ <MMMe˖n7lWvP+V?>7K.-z,ێöl ,HӉW@7.ƍgώ+2ϟf͊<v>=@&@ |$_5|ɘ0aQϟ??ZKKKdk˗˻]ۻwoA/"u,-m݀3VM͉f. /3 euԵ^{-(ɓ'q7 UF7xc۷/.첨ݻwDzebӦMkV\kkk^Dohht!@~f|k_{.SLŋ?(hoos@8&RF\ꢭ18 FiFiFiFiFiFiFiFiFiFiFiFiFiFiFiFiFiFiFiFiFiFiFiFiFiFiFiFiFiFiFiFiFiFiFiFiFiFiFiFiFiH=q7Gccc 4(FͱyGB=@/})c̙qGggg,^8&N=X466=" e~6.䒨1777)p:'@hԩG];vl]70g@JxgbذaEBꊹsFccc7.cܹUh@ He˖Ů] _BѣPaMMMe˖n7lW+h:Rx$ƍ㦛n?^8Tn8l˖-`J$@޽;8bŊQUUUHTkqS[ qWNj/W#FϏCv---~}z*cݮݻiRfӧSO=VwozϢEbĉ QIPi1iҤ&:ͱf͚xbʔ)EDl|;ٳ JW>J#@?iTUU??pǪꢽ=,Xk׮FMMML<9Z[[} ^ )Gyhkk+z FiFiFiFiFiFiFiFiFiFiFiFiFiFiFiFiFiFiFiFiFiFiFiFiFiFiFiFiFiFiFiFiFiFiFiFiFiFiFiFiFiHqwUW]o}[:.]ZXPRF]]]qwƓO>&L2ݻw֭[_rk˗//z33sάw[9qnd etg#"T*zk\x\sM<#qƂ 6*Mׯc&~z{ny1f̘n׆ Rq wyg=:&L>J޵ak_җ=fΜ_|qtvvŋcĉcEccq]˹Vicǎx饗bΜ9Q__+VG?ضm[|?k}9*m~Ν;_b 8P+%j͚5ҟvرcKMMM'KUUU|ȵyW|:˹Jׯ/W^y3ϔJRiݺuҥKOJ޵[ڏk͛K{ni'w/Vv,*M0tykrf\ҴiJϷo=-XebŊoȵs9'>OF{{{<'wĈq 76lذ5kV?CkeH}9JR۷/:TQOg}v ><"{w/vXԩS cǎw]q[ɻ֗s;vXcԨQqYgykrvX%ڏ~xcѢEGs雱o=#@'?I\tE1hРn/䒈;qģ_r%شiө4җs;/!C믏z,k]{+""&n]ݹU-Y$v?{t}Rf/s9{9p@=fΜ3g<뮻.ʸ⮻}k~3\%Z_ص7lܸ1nhjj'|][ڭf͊]vŲeoZέw瞋 … Gڷ e6`xW~#3ݩŔ)SNWJ޵Svmqy+VxJ۵7܎vmܸq1nܸ={v\y15kqwƮ܎RvoaÆżyz|})#GBQ___{tG?|g*yʡRv^:^|1běczwnS)> /O>qc׎v2v<}6o7b޼ysضm[l۶-8jl߾_}Rf~cӦMo߾n׬Y&L8&L3Ϛ5kbqEO}9uuudw*a8ӧOz*1w}k=㩄];og>c*}׎dx=-oۏZvmlڴ)ƌwyqo=#@lƌqС#x'|{xoq8x`{yw{ڳ><@L>ޙ/u?韢#kc~СCk֬x Lrٵrnk˂ 7IDAT_{ȇz;;;ӗs]?~|\2rhllѣG'?T*sҚcʕq뭷FCCC,]4֭[o^ziDSضm[OռKsܑsx /,*ޞۅ^'NI&Ő!C#ox,^8v%K 7pբ[n%l׎V6{c>zٳ#¿~U_έRwp۷/.첨ݻwDzebӦM"®[L6-{#)+ρJJ#G,{)S~t{Μ9sJե۷wϗ4lذK_~ytޞ^z]:th.]pngϞ/!\P*UUUKG3kGUM6#ϳk*uۿۥ#F:Rmmmk)ZZw}9Jݵ6mZiݮٷ g@4H#@4H#@4H#@4H#@4H#@4H#@4H#@4H#@4H#@4H#@4H#@4H#@4H#@4H#@4H#@4H#@4H#@4H#@4H#@4ܬSSIENDB`snakemake-5.10.0/tests/test_report/report/000077500000000000000000000000001361131222100205535ustar00rootroot00000000000000snakemake-5.10.0/tests/test_report/report/fig1.rst000066400000000000000000000000731361131222100221330ustar00rootroot00000000000000This is a caption with a `link `_. snakemake-5.10.0/tests/test_report/report/fig2.rst000066400000000000000000000000361361131222100221330ustar00rootroot00000000000000Some math :math:`\sum_i i^2`. snakemake-5.10.0/tests/test_report/report/table.rst000066400000000000000000000000221361131222100223660ustar00rootroot00000000000000An example table. snakemake-5.10.0/tests/test_report/report/workflow.rst000066400000000000000000000000741361131222100231600ustar00rootroot00000000000000This is the workflow description. Test reference fig1.svg_. snakemake-5.10.0/tests/test_report/test.0.out000066400000000000000000000000001361131222100210740ustar00rootroot00000000000000snakemake-5.10.0/tests/test_report/test.1.out000066400000000000000000000000001361131222100210750ustar00rootroot00000000000000snakemake-5.10.0/tests/test_report/test.2.out000066400000000000000000000000001361131222100210760ustar00rootroot00000000000000snakemake-5.10.0/tests/test_report/test.3.out000066400000000000000000000000001361131222100210770ustar00rootroot00000000000000snakemake-5.10.0/tests/test_report/test.4.out000066400000000000000000000000001361131222100211000ustar00rootroot00000000000000snakemake-5.10.0/tests/test_report/test.5.out000066400000000000000000000000001361131222100211010ustar00rootroot00000000000000snakemake-5.10.0/tests/test_report/test.6.out000066400000000000000000000000001361131222100211020ustar00rootroot00000000000000snakemake-5.10.0/tests/test_report/test.7.out000066400000000000000000000000001361131222100211030ustar00rootroot00000000000000snakemake-5.10.0/tests/test_report/test.8.out000066400000000000000000000000001361131222100211040ustar00rootroot00000000000000snakemake-5.10.0/tests/test_report/test.9.out000066400000000000000000000000001361131222100211050ustar00rootroot00000000000000snakemake-5.10.0/tests/test_report/test.csv000066400000000000000000003350371361131222100207470ustar00rootroot00000000000000street,city,zip,state,beds,baths,sq__ft,type,sale_date,price,latitude,longitude 3526 HIGH ST,SACRAMENTO,95838,CA,2,1,836,Residential,Wed May 21 00:00:00 EDT 2008,59222,38.631913,-121.434879 51 OMAHA CT,SACRAMENTO,95823,CA,3,1,1167,Residential,Wed May 21 00:00:00 EDT 2008,68212,38.478902,-121.431028 2796 BRANCH ST,SACRAMENTO,95815,CA,2,1,796,Residential,Wed May 21 00:00:00 EDT 2008,68880,38.618305,-121.443839 2805 JANETTE WAY,SACRAMENTO,95815,CA,2,1,852,Residential,Wed May 21 00:00:00 EDT 2008,69307,38.616835,-121.439146 6001 MCMAHON DR,SACRAMENTO,95824,CA,2,1,797,Residential,Wed May 21 00:00:00 EDT 2008,81900,38.51947,-121.435768 5828 PEPPERMILL CT,SACRAMENTO,95841,CA,3,1,1122,Condo,Wed May 21 00:00:00 EDT 2008,89921,38.662595,-121.327813 6048 OGDEN NASH WAY,SACRAMENTO,95842,CA,3,2,1104,Residential,Wed May 21 00:00:00 EDT 2008,90895,38.681659,-121.351705 2561 19TH AVE,SACRAMENTO,95820,CA,3,1,1177,Residential,Wed May 21 00:00:00 EDT 2008,91002,38.535092,-121.481367 11150 TRINITY RIVER DR Unit 114,RANCHO CORDOVA,95670,CA,2,2,941,Condo,Wed May 21 00:00:00 EDT 2008,94905,38.621188,-121.270555 7325 10TH ST,RIO LINDA,95673,CA,3,2,1146,Residential,Wed May 21 00:00:00 EDT 2008,98937,38.700909,-121.442979 645 MORRISON AVE,SACRAMENTO,95838,CA,3,2,909,Residential,Wed May 21 00:00:00 EDT 2008,100309,38.637663,-121.45152 4085 FAWN CIR,SACRAMENTO,95823,CA,3,2,1289,Residential,Wed May 21 00:00:00 EDT 2008,106250,38.470746,-121.458918 2930 LA ROSA RD,SACRAMENTO,95815,CA,1,1,871,Residential,Wed May 21 00:00:00 EDT 2008,106852,38.618698,-121.435833 2113 KIRK WAY,SACRAMENTO,95822,CA,3,1,1020,Residential,Wed May 21 00:00:00 EDT 2008,107502,38.482215,-121.492603 4533 LOCH HAVEN WAY,SACRAMENTO,95842,CA,2,2,1022,Residential,Wed May 21 00:00:00 EDT 2008,108750,38.672914,-121.35934 7340 HAMDEN PL,SACRAMENTO,95842,CA,2,2,1134,Condo,Wed May 21 00:00:00 EDT 2008,110700,38.700051,-121.351278 6715 6TH ST,RIO LINDA,95673,CA,2,1,844,Residential,Wed May 21 00:00:00 EDT 2008,113263,38.689591,-121.452239 6236 LONGFORD DR Unit 1,CITRUS HEIGHTS,95621,CA,2,1,795,Condo,Wed May 21 00:00:00 EDT 2008,116250,38.679776,-121.314089 250 PERALTA AVE,SACRAMENTO,95833,CA,2,1,588,Residential,Wed May 21 00:00:00 EDT 2008,120000,38.612099,-121.469095 113 LEEWILL AVE,RIO LINDA,95673,CA,3,2,1356,Residential,Wed May 21 00:00:00 EDT 2008,121630,38.689999,-121.46322 6118 STONEHAND AVE,CITRUS HEIGHTS,95621,CA,3,2,1118,Residential,Wed May 21 00:00:00 EDT 2008,122000,38.707851,-121.320707 4882 BANDALIN WAY,SACRAMENTO,95823,CA,4,2,1329,Residential,Wed May 21 00:00:00 EDT 2008,122682,38.468173,-121.444071 7511 OAKVALE CT,NORTH HIGHLANDS,95660,CA,4,2,1240,Residential,Wed May 21 00:00:00 EDT 2008,123000,38.702792,-121.38221 9 PASTURE CT,SACRAMENTO,95834,CA,3,2,1601,Residential,Wed May 21 00:00:00 EDT 2008,124100,38.628631,-121.488097 3729 BAINBRIDGE DR,NORTH HIGHLANDS,95660,CA,3,2,901,Residential,Wed May 21 00:00:00 EDT 2008,125000,38.701499,-121.37622 3828 BLACKFOOT WAY,ANTELOPE,95843,CA,3,2,1088,Residential,Wed May 21 00:00:00 EDT 2008,126640,38.70974,-121.37377 4108 NORTON WAY,SACRAMENTO,95820,CA,3,1,963,Residential,Wed May 21 00:00:00 EDT 2008,127281,38.537526,-121.478315 1469 JANRICK AVE,SACRAMENTO,95832,CA,3,2,1119,Residential,Wed May 21 00:00:00 EDT 2008,129000,38.476472,-121.501711 9861 CULP WAY,SACRAMENTO,95827,CA,4,2,1380,Residential,Wed May 21 00:00:00 EDT 2008,131200,38.558423,-121.327948 7825 CREEK VALLEY CIR,SACRAMENTO,95828,CA,3,2,1248,Residential,Wed May 21 00:00:00 EDT 2008,132000,38.472122,-121.404199 5201 LAGUNA OAKS DR Unit 140,ELK GROVE,95758,CA,2,2,1039,Condo,Wed May 21 00:00:00 EDT 2008,133000,38.423251,-121.444489 6768 MEDORA DR,NORTH HIGHLANDS,95660,CA,3,2,1152,Residential,Wed May 21 00:00:00 EDT 2008,134555,38.691161,-121.37192 3100 EXPLORER DR,SACRAMENTO,95827,CA,3,2,1380,Residential,Wed May 21 00:00:00 EDT 2008,136500,38.566663,-121.332644 7944 DOMINION WAY,ELVERTA,95626,CA,3,2,1116,Residential,Wed May 21 00:00:00 EDT 2008,138750,38.713182,-121.411227 5201 LAGUNA OAKS DR Unit 162,ELK GROVE,95758,CA,2,2,1039,Condo,Wed May 21 00:00:00 EDT 2008,141000,38.423251,-121.444489 3920 SHINING STAR DR,SACRAMENTO,95823,CA,3,2,1418,Residential,Wed May 21 00:00:00 EDT 2008,146250,38.48742,-121.462459 5031 CORVAIR ST,NORTH HIGHLANDS,95660,CA,3,2,1082,Residential,Wed May 21 00:00:00 EDT 2008,147308,38.658246,-121.375469 7661 NIXOS WAY,SACRAMENTO,95823,CA,4,2,1472,Residential,Wed May 21 00:00:00 EDT 2008,148750,38.479553,-121.463317 7044 CARTHY WAY,SACRAMENTO,95828,CA,4,2,1146,Residential,Wed May 21 00:00:00 EDT 2008,149593,38.49857,-121.420925 2442 LARKSPUR LN,SACRAMENTO,95825,CA,1,1,760,Condo,Wed May 21 00:00:00 EDT 2008,150000,38.58514,-121.403736 4800 WESTLAKE PKWY Unit 2109,SACRAMENTO,95835,CA,2,2,1304,Condo,Wed May 21 00:00:00 EDT 2008,152000,38.658812,-121.542345 2178 63RD AVE,SACRAMENTO,95822,CA,3,2,1207,Residential,Wed May 21 00:00:00 EDT 2008,154000,38.493955,-121.48966 8718 ELK WAY,ELK GROVE,95624,CA,3,2,1056,Residential,Wed May 21 00:00:00 EDT 2008,156896,38.41653,-121.379653 5708 RIDGEPOINT DR,ANTELOPE,95843,CA,2,2,1043,Residential,Wed May 21 00:00:00 EDT 2008,161250,38.72027,-121.331555 7315 KOALA CT,NORTH HIGHLANDS,95660,CA,4,2,1587,Residential,Wed May 21 00:00:00 EDT 2008,161500,38.699251,-121.371414 2622 ERIN DR,SACRAMENTO,95833,CA,4,1,1120,Residential,Wed May 21 00:00:00 EDT 2008,164000,38.613765,-121.488694 8421 SUNBLAZE WAY,SACRAMENTO,95823,CA,4,2,1580,Residential,Wed May 21 00:00:00 EDT 2008,165000,38.450543,-121.432538 7420 ALIX PKWY,SACRAMENTO,95823,CA,4,1,1955,Residential,Wed May 21 00:00:00 EDT 2008,166357,38.489405,-121.452811 3820 NATOMA WAY,SACRAMENTO,95838,CA,4,2,1656,Residential,Wed May 21 00:00:00 EDT 2008,166357,38.636748,-121.422159 4431 GREEN TREE DR,SACRAMENTO,95823,CA,3,2,1477,Residential,Wed May 21 00:00:00 EDT 2008,168000,38.499954,-121.454469 9417 SARA ST,ELK GROVE,95624,CA,3,2,1188,Residential,Wed May 21 00:00:00 EDT 2008,170000,38.415518,-121.370527 8299 HALBRITE WAY,SACRAMENTO,95828,CA,4,2,1590,Residential,Wed May 21 00:00:00 EDT 2008,173000,38.473814,-121.4 7223 KALLIE KAY LN,SACRAMENTO,95823,CA,3,2,1463,Residential,Wed May 21 00:00:00 EDT 2008,174250,38.477553,-121.419463 8156 STEINBECK WAY,SACRAMENTO,95828,CA,4,2,1714,Residential,Wed May 21 00:00:00 EDT 2008,174313,38.474853,-121.406326 7957 VALLEY GREEN DR,SACRAMENTO,95823,CA,3,2,1185,Residential,Wed May 21 00:00:00 EDT 2008,178480,38.465184,-121.434925 1122 WILD POPPY CT,GALT,95632,CA,3,2,1406,Residential,Wed May 21 00:00:00 EDT 2008,178760,38.287789,-121.294715 4520 BOMARK WAY,SACRAMENTO,95842,CA,4,2,1943,Multi-Family,Wed May 21 00:00:00 EDT 2008,179580,38.665724,-121.358576 9012 KIEFER BLVD,SACRAMENTO,95826,CA,3,2,1172,Residential,Wed May 21 00:00:00 EDT 2008,181000,38.547011,-121.366217 5332 SANDSTONE ST,CARMICHAEL,95608,CA,3,1,1152,Residential,Wed May 21 00:00:00 EDT 2008,181872,38.662105,-121.313945 5993 SAWYER CIR,SACRAMENTO,95823,CA,4,3,1851,Residential,Wed May 21 00:00:00 EDT 2008,182587,38.4473,-121.435218 4844 CLYDEBANK WAY,ANTELOPE,95843,CA,3,2,1215,Residential,Wed May 21 00:00:00 EDT 2008,182716,38.714609,-121.347887 306 CAMELLIA WAY,GALT,95632,CA,3,2,1130,Residential,Wed May 21 00:00:00 EDT 2008,182750,38.260443,-121.297864 9021 MADISON AVE,ORANGEVALE,95662,CA,4,2,1603,Residential,Wed May 21 00:00:00 EDT 2008,183200,38.664186,-121.217511 404 6TH ST,GALT,95632,CA,3,1,1479,Residential,Wed May 21 00:00:00 EDT 2008,188741,38.251808,-121.302493 8317 SUNNY CREEK WAY,SACRAMENTO,95823,CA,3,2,1420,Residential,Wed May 21 00:00:00 EDT 2008,189000,38.459041,-121.424644 2617 BASS CT,SACRAMENTO,95826,CA,3,2,1280,Residential,Wed May 21 00:00:00 EDT 2008,192067,38.560767,-121.377471 7005 TIANT WAY,ELK GROVE,95758,CA,3,2,1586,Residential,Wed May 21 00:00:00 EDT 2008,194000,38.422811,-121.423285 7895 CABER WAY,ANTELOPE,95843,CA,3,2,1362,Residential,Wed May 21 00:00:00 EDT 2008,194818,38.711279,-121.393449 7624 BOGEY CT,SACRAMENTO,95828,CA,4,4,2162,Multi-Family,Wed May 21 00:00:00 EDT 2008,195000,38.48009,-121.415102 6930 HAMPTON COVE WAY,SACRAMENTO,95823,CA,3,2,1266,Residential,Wed May 21 00:00:00 EDT 2008,198000,38.44004,-121.421012 8708 MESA BROOK WAY,ELK GROVE,95624,CA,4,2,1715,Residential,Wed May 21 00:00:00 EDT 2008,199500,38.44076,-121.385792 120 GRANT LN,FOLSOM,95630,CA,3,2,1820,Residential,Wed May 21 00:00:00 EDT 2008,200000,38.687742,-121.17104 5907 ELLERSLEE DR,CARMICHAEL,95608,CA,3,1,936,Residential,Wed May 21 00:00:00 EDT 2008,200000,38.664468,-121.32683 17 SERASPI CT,SACRAMENTO,95834,CA,0,0,0,Residential,Wed May 21 00:00:00 EDT 2008,206000,38.631481,-121.50188 170 PENHOW CIR,SACRAMENTO,95834,CA,3,2,1511,Residential,Wed May 21 00:00:00 EDT 2008,208000,38.653439,-121.535169 8345 STAR THISTLE WAY,SACRAMENTO,95823,CA,4,2,1590,Residential,Wed May 21 00:00:00 EDT 2008,212864,38.454349,-121.439239 9080 FRESCA WAY,ELK GROVE,95758,CA,4,2,1596,Residential,Wed May 21 00:00:00 EDT 2008,221000,38.427818,-121.424026 391 NATALINO CIR,SACRAMENTO,95835,CA,2,2,1341,Residential,Wed May 21 00:00:00 EDT 2008,221000,38.67307,-121.506373 8373 BLACKMAN WAY,ELK GROVE,95624,CA,5,3,2136,Residential,Wed May 21 00:00:00 EDT 2008,223058,38.435436,-121.394536 9837 CORTE DORADO CT,ELK GROVE,95624,CA,4,2,1616,Residential,Wed May 21 00:00:00 EDT 2008,227887,38.400676,-121.38101 5037 J PKWY,SACRAMENTO,95823,CA,3,2,1478,Residential,Wed May 21 00:00:00 EDT 2008,231477,38.491399,-121.443547 10245 LOS PALOS DR,RANCHO CORDOVA,95670,CA,3,2,1287,Residential,Wed May 21 00:00:00 EDT 2008,234697,38.593699,-121.31089 6613 NAVION DR,CITRUS HEIGHTS,95621,CA,4,2,1277,Residential,Wed May 21 00:00:00 EDT 2008,235000,38.702855,-121.31308 2887 AZEVEDO DR,SACRAMENTO,95833,CA,4,2,1448,Residential,Wed May 21 00:00:00 EDT 2008,236000,38.618457,-121.509439 9186 KINBRACE CT,SACRAMENTO,95829,CA,4,3,2235,Residential,Wed May 21 00:00:00 EDT 2008,236685,38.463355,-121.358936 4243 MIDDLEBURY WAY,MATHER,95655,CA,3,2,2093,Residential,Wed May 21 00:00:00 EDT 2008,237800,38.547991,-121.280483 1028 FALLON PLACE CT,RIO LINDA,95673,CA,3,2,1193,Residential,Wed May 21 00:00:00 EDT 2008,240122,38.693818,-121.441153 4804 NORIKER DR,ELK GROVE,95757,CA,3,2,2163,Residential,Wed May 21 00:00:00 EDT 2008,242638,38.400974,-121.448424 7713 HARVEST WOODS DR,SACRAMENTO,95828,CA,3,2,1269,Residential,Wed May 21 00:00:00 EDT 2008,244000,38.478198,-121.412911 2866 KARITSA AVE,SACRAMENTO,95833,CA,0,0,0,Residential,Wed May 21 00:00:00 EDT 2008,244500,38.626671,-121.52597 6913 RICHEVE WAY,SACRAMENTO,95828,CA,3,1,958,Residential,Wed May 21 00:00:00 EDT 2008,244960,38.502519,-121.420769 8636 TEGEA WAY,ELK GROVE,95624,CA,5,3,2508,Residential,Wed May 21 00:00:00 EDT 2008,245918,38.443832,-121.382087 5448 MAIDSTONE WAY,CITRUS HEIGHTS,95621,CA,3,2,1305,Residential,Wed May 21 00:00:00 EDT 2008,250000,38.665395,-121.293288 18 OLLIE CT,ELK GROVE,95758,CA,4,2,1591,Residential,Wed May 21 00:00:00 EDT 2008,250000,38.444909,-121.412345 4010 ALEX LN,CARMICHAEL,95608,CA,2,2,1326,Condo,Wed May 21 00:00:00 EDT 2008,250134,38.637028,-121.312963 4901 MILLNER WAY,ELK GROVE,95757,CA,3,2,1843,Residential,Wed May 21 00:00:00 EDT 2008,254200,38.38692,-121.447349 4818 BRITTNEY LEE CT,SACRAMENTO,95841,CA,4,2,1921,Residential,Wed May 21 00:00:00 EDT 2008,254200,38.653917,-121.34218 5529 LAGUNA PARK DR,ELK GROVE,95758,CA,5,3,2790,Residential,Wed May 21 00:00:00 EDT 2008,258000,38.42568,-121.438062 230 CANDELA CIR,SACRAMENTO,95835,CA,3,2,1541,Residential,Wed May 21 00:00:00 EDT 2008,260000,38.656251,-121.547572 4900 71ST ST,SACRAMENTO,95820,CA,3,1,1018,Residential,Wed May 21 00:00:00 EDT 2008,260014,38.53151,-121.421089 12209 CONSERVANCY WAY,RANCHO CORDOVA,95742,CA,0,0,0,Residential,Wed May 21 00:00:00 EDT 2008,263500,38.553867,-121.219141 4236 NATOMAS CENTRAL DR,SACRAMENTO,95834,CA,3,2,1672,Condo,Wed May 21 00:00:00 EDT 2008,265000,38.648879,-121.544023 5615 LUPIN LN,POLLOCK PINES,95726,CA,3,2,1380,Residential,Wed May 21 00:00:00 EDT 2008,265000,38.708315,-120.603872 5625 JAMES WAY,SACRAMENTO,95822,CA,3,1,975,Residential,Wed May 21 00:00:00 EDT 2008,271742,38.523947,-121.484946 7842 LAHONTAN CT,SACRAMENTO,95829,CA,4,3,2372,Residential,Wed May 21 00:00:00 EDT 2008,273750,38.472976,-121.318633 6850 21ST ST,SACRAMENTO,95822,CA,3,2,1446,Residential,Wed May 21 00:00:00 EDT 2008,275086,38.502194,-121.490795 2900 BLAIR RD,POLLOCK PINES,95726,CA,2,2,1284,Residential,Wed May 21 00:00:00 EDT 2008,280908,38.75485,-120.60476 2064 EXPEDITION WAY,SACRAMENTO,95832,CA,4,3,3009,Residential,Wed May 21 00:00:00 EDT 2008,280987,38.474099,-121.490711 2912 NORCADE CIR,SACRAMENTO,95826,CA,8,4,3612,Multi-Family,Wed May 21 00:00:00 EDT 2008,282400,38.559505,-121.364839 9507 SEA CLIFF WAY,ELK GROVE,95758,CA,4,2,2056,Residential,Wed May 21 00:00:00 EDT 2008,285000,38.410992,-121.479043 8882 AUTUMN GOLD CT,ELK GROVE,95624,CA,4,2,1993,Residential,Wed May 21 00:00:00 EDT 2008,287417,38.4439,-121.37255 5322 WHITE LOTUS WAY,ELK GROVE,95757,CA,3,2,1857,Residential,Wed May 21 00:00:00 EDT 2008,291000,38.391538,-121.442596 1838 CASTRO WAY,SACRAMENTO,95818,CA,2,1,1126,Residential,Wed May 21 00:00:00 EDT 2008,292024,38.556098,-121.490787 10158 CRAWFORD WAY,SACRAMENTO,95827,CA,4,4,2213,Multi-Family,Wed May 21 00:00:00 EDT 2008,297000,38.5703,-121.315735 7731 MASTERS ST,ELK GROVE,95758,CA,5,3,2494,Residential,Wed May 21 00:00:00 EDT 2008,297000,38.442031,-121.410873 4925 PERCHERON DR,ELK GROVE,95757,CA,3,2,1843,Residential,Wed May 21 00:00:00 EDT 2008,298000,38.40154,-121.447649 2010 PROMONTORY POINT LN,GOLD RIVER,95670,CA,2,2,1520,Residential,Wed May 21 00:00:00 EDT 2008,299000,38.62869,-121.261669 4727 SAVOIE WAY,SACRAMENTO,95835,CA,5,3,2800,Residential,Wed May 21 00:00:00 EDT 2008,304037,38.658182,-121.549521 8664 MAGNOLIA HILL WAY,ELK GROVE,95624,CA,4,2,2309,Residential,Wed May 21 00:00:00 EDT 2008,311000,38.442352,-121.389675 9570 HARVEST ROSE WAY,SACRAMENTO,95827,CA,5,3,2367,Residential,Wed May 21 00:00:00 EDT 2008,315537,38.555993,-121.340352 4359 CREGAN CT,RANCHO CORDOVA,95742,CA,5,4,3516,Residential,Wed May 21 00:00:00 EDT 2008,320000,38.545128,-121.224922 5337 DUSTY ROSE WAY,RANCHO CORDOVA,95742,CA,0,0,0,Residential,Wed May 21 00:00:00 EDT 2008,320000,38.528575,-121.2286 8929 SUTTERS GOLD DR,SACRAMENTO,95826,CA,4,3,1914,Residential,Wed May 21 00:00:00 EDT 2008,328360,38.550848,-121.370224 8025 PEERLESS AVE,ORANGEVALE,95662,CA,2,1,1690,Residential,Wed May 21 00:00:00 EDT 2008,334150,38.71147,-121.216214 4620 WELERA WAY,ELK GROVE,95757,CA,3,3,2725,Residential,Wed May 21 00:00:00 EDT 2008,335750,38.398609,-121.450148 9723 TERRAPIN CT,ELK GROVE,95757,CA,4,3,2354,Residential,Wed May 21 00:00:00 EDT 2008,335750,38.403492,-121.430224 2115 SMOKESTACK WAY,SACRAMENTO,95833,CA,0,0,0,Residential,Wed May 21 00:00:00 EDT 2008,339500,38.602416,-121.542965 100 REBECCA WAY,FOLSOM,95630,CA,3,2,2185,Residential,Wed May 21 00:00:00 EDT 2008,344250,38.68479,-121.149199 9488 OAK VILLAGE WAY,ELK GROVE,95758,CA,4,2,1801,Residential,Wed May 21 00:00:00 EDT 2008,346210,38.41333,-121.404999 8495 DARTFORD DR,SACRAMENTO,95823,CA,3,3,1961,Residential,Wed May 21 00:00:00 EDT 2008,347029,38.448507,-121.421346 6708 PONTA DO SOL WAY,ELK GROVE,95757,CA,4,2,3134,Residential,Wed May 21 00:00:00 EDT 2008,347650,38.380635,-121.425538 4143 SEA MEADOW WAY,SACRAMENTO,95823,CA,4,3,1915,Residential,Wed May 21 00:00:00 EDT 2008,351300,38.46534,-121.457519 3020 RICHARDSON CIR,EL DORADO HILLS,95762,CA,3,2,0,Residential,Wed May 21 00:00:00 EDT 2008,352000,38.691299,-121.081752 8082 LINDA ISLE LN,SACRAMENTO,95831,CA,0,0,0,Residential,Wed May 21 00:00:00 EDT 2008,370000,38.4772,-121.5215 15300 MURIETA SOUTH PKWY,RANCHO MURIETA,95683,CA,4,3,2734,Residential,Wed May 21 00:00:00 EDT 2008,370500,38.4874,-121.075129 11215 SHARRMONT CT,WILTON,95693,CA,3,2,2110,Residential,Wed May 21 00:00:00 EDT 2008,372000,38.35062,-121.228349 7105 DANBERG WAY,ELK GROVE,95757,CA,5,3,3164,Residential,Wed May 21 00:00:00 EDT 2008,375000,38.4019,-121.420388 5579 JERRY LITELL WAY,SACRAMENTO,95835,CA,5,3,3599,Residential,Wed May 21 00:00:00 EDT 2008,381300,38.677126,-121.500519 1050 FOXHALL WAY,SACRAMENTO,95831,CA,4,2,2054,Residential,Wed May 21 00:00:00 EDT 2008,381942,38.509819,-121.519661 7837 ABBINGTON WAY,ANTELOPE,95843,CA,4,2,1830,Residential,Wed May 21 00:00:00 EDT 2008,387731,38.709873,-121.339472 1300 F ST,SACRAMENTO,95814,CA,3,3,1627,Residential,Wed May 21 00:00:00 EDT 2008,391000,38.58355,-121.487289 6801 RAWLEY WAY,ELK GROVE,95757,CA,4,3,3440,Residential,Wed May 21 00:00:00 EDT 2008,394470,38.408351,-121.423925 1693 SHELTER COVE DR,GREENWOOD,95635,CA,3,2,2846,Residential,Wed May 21 00:00:00 EDT 2008,395000,38.945357,-120.908822 9361 WADDELL LN,ELK GROVE,95624,CA,4,3,2359,Residential,Wed May 21 00:00:00 EDT 2008,400186,38.450829,-121.349928 10 SEA FOAM CT,SACRAMENTO,95831,CA,3,3,2052,Residential,Wed May 21 00:00:00 EDT 2008,415000,38.487885,-121.545947 6945 RIO TEJO WAY,ELK GROVE,95757,CA,5,3,3433,Residential,Wed May 21 00:00:00 EDT 2008,425000,38.385638,-121.422616 4186 TULIP PARK WAY,RANCHO CORDOVA,95742,CA,5,3,3615,Residential,Wed May 21 00:00:00 EDT 2008,430000,38.550617,-121.23526 9278 DAIRY CT,ELK GROVE,95624,CA,0,0,0,Residential,Wed May 21 00:00:00 EDT 2008,445000,38.420338,-121.363757 207 ORANGE BLOSSOM CIR Unit C,FOLSOM,95630,CA,5,3,2687,Residential,Wed May 21 00:00:00 EDT 2008,460000,38.646273,-121.175322 6507 RIO DE ONAR WAY,ELK GROVE,95757,CA,4,3,2724,Residential,Wed May 21 00:00:00 EDT 2008,461000,38.38253,-121.428007 7004 RAWLEY WAY,ELK GROVE,95757,CA,4,3,3440,Residential,Wed May 21 00:00:00 EDT 2008,489332,38.406421,-121.422081 6503 RIO DE ONAR WAY,ELK GROVE,95757,CA,5,4,3508,Residential,Wed May 21 00:00:00 EDT 2008,510000,38.38253,-121.428038 2217 APPALOOSA CT,FOLSOM,95630,CA,4,2,2462,Residential,Wed May 21 00:00:00 EDT 2008,539000,38.655167,-121.090178 868 HILDEBRAND CIR,FOLSOM,95630,CA,0,0,0,Residential,Wed May 21 00:00:00 EDT 2008,585000,38.670947,-121.097727 6030 PALERMO WAY,EL DORADO HILLS,95762,CA,4,3,0,Residential,Wed May 21 00:00:00 EDT 2008,600000,38.672761,-121.050378 4070 REDONDO DR,EL DORADO HILLS,95762,CA,4,3,0,Residential,Wed May 21 00:00:00 EDT 2008,606238,38.666807,-121.06483 4004 CRESTA WAY,SACRAMENTO,95864,CA,3,3,2325,Residential,Wed May 21 00:00:00 EDT 2008,660000,38.591618,-121.370626 315 JUMEL CT,EL DORADO HILLS,95762,CA,6,5,0,Residential,Wed May 21 00:00:00 EDT 2008,830000,38.669931,-121.05958 6272 LONGFORD DR Unit 1,CITRUS HEIGHTS,95621,CA,2,1,795,Condo,Tue May 20 00:00:00 EDT 2008,69000,38.680923,-121.313945 3432 Y ST,SACRAMENTO,95817,CA,4,2,1099,Residential,Tue May 20 00:00:00 EDT 2008,70000,38.554967,-121.468046 9512 EMERALD PARK DR Unit 3,ELK GROVE,95624,CA,2,1,840,Condo,Tue May 20 00:00:00 EDT 2008,71000,38.40573,-121.369832 3132 CLAY ST,SACRAMENTO,95815,CA,2,1,800,Residential,Tue May 20 00:00:00 EDT 2008,78000,38.624678,-121.439203 5221 38TH AVE,SACRAMENTO,95824,CA,2,1,746,Residential,Tue May 20 00:00:00 EDT 2008,78400,38.518044,-121.443555 6112 HERMOSA ST,SACRAMENTO,95822,CA,3,1,1067,Residential,Tue May 20 00:00:00 EDT 2008,80000,38.515125,-121.480416 483 ARCADE BLVD,SACRAMENTO,95815,CA,4,2,1316,Residential,Tue May 20 00:00:00 EDT 2008,89000,38.623571,-121.454884 671 SONOMA AVE,SACRAMENTO,95815,CA,3,1,1337,Residential,Tue May 20 00:00:00 EDT 2008,90000,38.622953,-121.450142 5980 79TH ST,SACRAMENTO,95824,CA,2,1,868,Residential,Tue May 20 00:00:00 EDT 2008,90000,38.518373,-121.411779 7607 ELDER CREEK RD,SACRAMENTO,95824,CA,3,1,924,Residential,Tue May 20 00:00:00 EDT 2008,92000,38.51055,-121.414768 5028 14TH AVE,SACRAMENTO,95820,CA,2,1,610,Residential,Tue May 20 00:00:00 EDT 2008,93675,38.53942,-121.446894 14788 NATCHEZ CT,RANCHO MURIETA,95683,CA,0,0,0,Residential,Tue May 20 00:00:00 EDT 2008,97750,38.492287,-121.100032 1069 ACACIA AVE,SACRAMENTO,95815,CA,2,1,1220,Residential,Tue May 20 00:00:00 EDT 2008,98000,38.621998,-121.442238 5201 LAGUNA OAKS DR Unit 199,ELK GROVE,95758,CA,1,1,722,Condo,Tue May 20 00:00:00 EDT 2008,98000,38.423251,-121.444489 3847 LAS PASAS WAY,SACRAMENTO,95864,CA,3,1,1643,Residential,Tue May 20 00:00:00 EDT 2008,99000,38.588672,-121.373916 5201 LAGUNA OAKS DR Unit 172,ELK GROVE,95758,CA,1,1,722,Condo,Tue May 20 00:00:00 EDT 2008,100000,38.423251,-121.444489 1121 CREEKSIDE WAY,GALT,95632,CA,3,1,1080,Residential,Tue May 20 00:00:00 EDT 2008,106716,38.241514,-121.312199 5307 CABRILLO WAY,SACRAMENTO,95820,CA,3,1,1039,Residential,Tue May 20 00:00:00 EDT 2008,111000,38.52712,-121.435348 3725 DON JULIO BLVD,NORTH HIGHLANDS,95660,CA,3,1,1051,Residential,Tue May 20 00:00:00 EDT 2008,111000,38.67895,-121.379406 4803 MCCLOUD DR,SACRAMENTO,95842,CA,2,2,967,Residential,Tue May 20 00:00:00 EDT 2008,114800,38.682279,-121.352817 10542 SILVERWOOD WAY,RANCHO CORDOVA,95670,CA,3,1,1098,Residential,Tue May 20 00:00:00 EDT 2008,120108,38.587156,-121.295778 6318 39TH AVE,SACRAMENTO,95824,CA,3,1,1050,Residential,Tue May 20 00:00:00 EDT 2008,123225,38.518942,-121.430158 211 MCDANIEL CIR,SACRAMENTO,95838,CA,3,2,1110,Residential,Tue May 20 00:00:00 EDT 2008,123750,38.636565,-121.460383 3800 LYNHURST WAY,NORTH HIGHLANDS,95660,CA,3,1,888,Residential,Tue May 20 00:00:00 EDT 2008,125000,38.650445,-121.374861 6139 HERMOSA ST,SACRAMENTO,95822,CA,3,2,1120,Residential,Tue May 20 00:00:00 EDT 2008,125000,38.514665,-121.480411 2505 RHINE WAY,ELVERTA,95626,CA,3,2,1080,Residential,Tue May 20 00:00:00 EDT 2008,126000,38.717976,-121.407684 3692 PAYNE WAY,NORTH HIGHLANDS,95660,CA,3,1,957,Residential,Tue May 20 00:00:00 EDT 2008,129000,38.66654,-121.378298 604 MORRISON AVE,SACRAMENTO,95838,CA,2,1,952,Residential,Tue May 20 00:00:00 EDT 2008,134000,38.637678,-121.452476 648 SANTA ANA AVE,SACRAMENTO,95838,CA,3,2,1211,Residential,Tue May 20 00:00:00 EDT 2008,135000,38.658478,-121.450409 14 ASHLEY OAKS CT,SACRAMENTO,95815,CA,3,2,1264,Residential,Tue May 20 00:00:00 EDT 2008,135500,38.61779,-121.436765 3174 NORTHVIEW DR,SACRAMENTO,95833,CA,3,1,1080,Residential,Tue May 20 00:00:00 EDT 2008,140000,38.623817,-121.477827 840 TRANQUIL LN,GALT,95632,CA,3,2,1266,Residential,Tue May 20 00:00:00 EDT 2008,140000,38.270617,-121.299205 5333 PRIMROSE DR Unit 19A,FAIR OAKS,95628,CA,2,2,994,Condo,Tue May 20 00:00:00 EDT 2008,142500,38.662785,-121.276272 1035 MILLET WAY,SACRAMENTO,95834,CA,3,2,1202,Residential,Tue May 20 00:00:00 EDT 2008,143500,38.631056,-121.48508 5201 LAGUNA OAKS DR Unit 126,ELK GROVE,95758,CA,0,0,0,Condo,Tue May 20 00:00:00 EDT 2008,145000,38.423251,-121.444489 3328 22ND AVE,SACRAMENTO,95820,CA,2,1,722,Residential,Tue May 20 00:00:00 EDT 2008,145000,38.532727,-121.470783 8001 HARTWICK WAY,SACRAMENTO,95828,CA,4,2,1448,Residential,Tue May 20 00:00:00 EDT 2008,145000,38.488623,-121.410582 7812 HARTWICK WAY,SACRAMENTO,95828,CA,3,2,1188,Residential,Tue May 20 00:00:00 EDT 2008,145000,38.488611,-121.412808 4207 PAINTER WAY,NORTH HIGHLANDS,95660,CA,4,2,1183,Residential,Tue May 20 00:00:00 EDT 2008,146000,38.692915,-121.367497 7458 WINKLEY WAY,SACRAMENTO,95822,CA,3,1,1320,Residential,Tue May 20 00:00:00 EDT 2008,148500,38.487444,-121.491366 8354 SUNRISE WOODS WAY,SACRAMENTO,95828,CA,3,2,1117,Residential,Tue May 20 00:00:00 EDT 2008,149000,38.473288,-121.3963 8116 COTTONMILL CIR,SACRAMENTO,95828,CA,3,2,1364,Residential,Tue May 20 00:00:00 EDT 2008,150000,38.482876,-121.405912 4660 CEDARWOOD WAY,SACRAMENTO,95823,CA,4,2,1310,Residential,Tue May 20 00:00:00 EDT 2008,150000,38.484834,-121.449316 9254 HARROGATE WAY,ELK GROVE,95758,CA,2,2,1006,Residential,Tue May 20 00:00:00 EDT 2008,152000,38.420138,-121.412179 6716 TAREYTON WAY,CITRUS HEIGHTS,95621,CA,3,2,1104,Residential,Tue May 20 00:00:00 EDT 2008,156000,38.693724,-121.307169 2028 ROBERT WAY,SACRAMENTO,95825,CA,2,1,810,Residential,Tue May 20 00:00:00 EDT 2008,156000,38.609982,-121.419263 9346 AIZENBERG CIR,ELK GROVE,95624,CA,2,2,1123,Residential,Tue May 20 00:00:00 EDT 2008,156000,38.41875,-121.370019 4524 LOCH HAVEN WAY,SACRAMENTO,95842,CA,2,1,904,Residential,Tue May 20 00:00:00 EDT 2008,157788,38.67273,-121.359645 7140 BLUE SPRINGS WAY,CITRUS HEIGHTS,95621,CA,3,2,1156,Residential,Tue May 20 00:00:00 EDT 2008,161653,38.720653,-121.302241 4631 11TH AVE,SACRAMENTO,95820,CA,2,1,1321,Residential,Tue May 20 00:00:00 EDT 2008,161829,38.541965,-121.452132 3228 BAGGAN CT,ANTELOPE,95843,CA,3,2,1392,Residential,Tue May 20 00:00:00 EDT 2008,165000,38.715346,-121.388163 8515 DARTFORD DR,SACRAMENTO,95823,CA,3,2,1439,Residential,Tue May 20 00:00:00 EDT 2008,168000,38.448288,-121.420719 4500 TIPPWOOD WAY,SACRAMENTO,95842,CA,3,2,1159,Residential,Tue May 20 00:00:00 EDT 2008,169000,38.69951,-121.359989 2460 EL ROCCO WAY,RANCHO CORDOVA,95670,CA,3,2,1671,Residential,Tue May 20 00:00:00 EDT 2008,175000,38.591477,-121.31534 8244 SUNBIRD WAY,SACRAMENTO,95823,CA,3,2,1740,Residential,Tue May 20 00:00:00 EDT 2008,176250,38.457654,-121.431381 5841 VALLEY VALE WAY,SACRAMENTO,95823,CA,3,2,1265,Residential,Tue May 20 00:00:00 EDT 2008,179000,38.461283,-121.434322 7863 CRESTLEIGH CT,ANTELOPE,95843,CA,2,2,1007,Residential,Tue May 20 00:00:00 EDT 2008,180000,38.710889,-121.358876 7129 SPRINGMONT DR,ELK GROVE,95758,CA,3,2,1716,Residential,Tue May 20 00:00:00 EDT 2008,180400,38.417649,-121.420294 8284 RED FOX WAY,ELK GROVE,95758,CA,4,2,1685,Residential,Tue May 20 00:00:00 EDT 2008,182000,38.417182,-121.397231 2219 EL CANTO CIR,RANCHO CORDOVA,95670,CA,4,2,1829,Residential,Tue May 20 00:00:00 EDT 2008,184500,38.592383,-121.318669 8907 GEMWOOD WAY,ELK GROVE,95758,CA,3,2,1555,Residential,Tue May 20 00:00:00 EDT 2008,185000,38.435471,-121.441173 5925 MALEVILLE AVE,CARMICHAEL,95608,CA,4,2,1120,Residential,Tue May 20 00:00:00 EDT 2008,189000,38.666564,-121.325717 7031 CANEVALLEY CIR,CITRUS HEIGHTS,95621,CA,3,2,1137,Residential,Tue May 20 00:00:00 EDT 2008,194000,38.718693,-121.303619 3949 WILDROSE WAY,SACRAMENTO,95826,CA,3,1,1174,Residential,Tue May 20 00:00:00 EDT 2008,195000,38.543697,-121.366683 4437 MITCHUM CT,ANTELOPE,95843,CA,3,2,1393,Residential,Tue May 20 00:00:00 EDT 2008,200000,38.704407,-121.36113 2778 KAWEAH CT,CAMERON PARK,95682,CA,3,1,0,Residential,Tue May 20 00:00:00 EDT 2008,201000,38.694052,-120.995589 1636 ALLENWOOD CIR,LINCOLN,95648,CA,4,2,0,Residential,Tue May 20 00:00:00 EDT 2008,202500,38.879192,-121.309477 8151 QUAIL RIDGE CT,SACRAMENTO,95828,CA,3,2,1289,Residential,Tue May 20 00:00:00 EDT 2008,205000,38.461296,-121.390858 4899 WIND CREEK DR,SACRAMENTO,95838,CA,4,2,1799,Residential,Tue May 20 00:00:00 EDT 2008,205000,38.655887,-121.446119 2370 BIG CANYON CREEK RD,PLACERVILLE,95667,CA,3,2,0,Residential,Tue May 20 00:00:00 EDT 2008,205000,38.74458,-120.794254 6049 HAMBURG WAY,SACRAMENTO,95823,CA,4,3,1953,Residential,Tue May 20 00:00:00 EDT 2008,205000,38.443253,-121.431992 4232 71ST ST,SACRAMENTO,95820,CA,2,1,723,Residential,Tue May 20 00:00:00 EDT 2008,207000,38.536741,-121.42115 3361 BOW MAR CT,CAMERON PARK,95682,CA,2,2,0,Residential,Tue May 20 00:00:00 EDT 2008,210000,38.69437,-120.996602 1889 COLD SPRINGS RD,PLACERVILLE,95667,CA,2,1,948,Residential,Tue May 20 00:00:00 EDT 2008,211500,38.739774,-120.860243 5805 HIMALAYA WAY,CITRUS HEIGHTS,95621,CA,4,2,1578,Residential,Tue May 20 00:00:00 EDT 2008,215000,38.696489,-121.328555 7944 SYLVAN OAK WAY,CITRUS HEIGHTS,95610,CA,3,2,1317,Residential,Tue May 20 00:00:00 EDT 2008,215000,38.710388,-121.261096 3139 SPOONWOOD WAY Unit 1,SACRAMENTO,95833,CA,0,0,0,Residential,Tue May 20 00:00:00 EDT 2008,215500,38.626582,-121.52151 6217 LEOLA WAY,SACRAMENTO,95824,CA,3,1,1360,Residential,Tue May 20 00:00:00 EDT 2008,222381,38.513066,-121.451909 2340 HURLEY WAY,SACRAMENTO,95825,CA,0,0,0,Condo,Tue May 20 00:00:00 EDT 2008,225000,38.588816,-121.408549 3035 BRUNNET LN,SACRAMENTO,95833,CA,3,2,1522,Residential,Tue May 20 00:00:00 EDT 2008,225000,38.624762,-121.522775 3025 EL PRADO WAY,SACRAMENTO,95825,CA,4,2,1751,Residential,Tue May 20 00:00:00 EDT 2008,225000,38.606603,-121.394147 9387 GRANITE FALLS CT,ELK GROVE,95624,CA,3,2,1465,Residential,Tue May 20 00:00:00 EDT 2008,225000,38.419214,-121.348533 9257 CALDERA WAY,SACRAMENTO,95826,CA,4,2,1605,Residential,Tue May 20 00:00:00 EDT 2008,228000,38.55821,-121.355022 441 ARLINGDALE CIR,RIO LINDA,95673,CA,4,2,1475,Residential,Tue May 20 00:00:00 EDT 2008,229665,38.702893,-121.454949 2284 LOS ROBLES RD,MEADOW VISTA,95722,CA,3,1,1216,Residential,Tue May 20 00:00:00 EDT 2008,230000,39.008159,-121.03623 8164 CHENIN BLANC LN,FAIR OAKS,95628,CA,2,2,1315,Residential,Tue May 20 00:00:00 EDT 2008,230000,38.665644,-121.259969 4620 CHAMBERLIN CIR,ELK GROVE,95757,CA,3,2,1567,Residential,Tue May 20 00:00:00 EDT 2008,230000,38.390557,-121.449805 5340 BIRK WAY,SACRAMENTO,95835,CA,3,2,1776,Residential,Tue May 20 00:00:00 EDT 2008,234000,38.672495,-121.515251 51 ANJOU CIR,SACRAMENTO,95835,CA,3,2,2187,Residential,Tue May 20 00:00:00 EDT 2008,235000,38.661658,-121.540633 2125 22ND AVE,SACRAMENTO,95822,CA,3,1,1291,Residential,Tue May 20 00:00:00 EDT 2008,236250,38.534596,-121.493121 611 BLOSSOM ROCK LN,FOLSOM,95630,CA,0,0,0,Condo,Tue May 20 00:00:00 EDT 2008,240000,38.6457,-121.1197 8830 ADUR RD,ELK GROVE,95624,CA,0,0,0,Residential,Tue May 20 00:00:00 EDT 2008,242000,38.43742,-121.372876 7344 BUTTERBALL WAY,SACRAMENTO,95842,CA,3,2,1503,Residential,Tue May 20 00:00:00 EDT 2008,245000,38.699489,-121.361828 8219 GWINHURST CIR,SACRAMENTO,95828,CA,4,3,2491,Residential,Tue May 20 00:00:00 EDT 2008,245000,38.459711,-121.384283 3240 S ST,SACRAMENTO,95816,CA,2,1,1269,Residential,Tue May 20 00:00:00 EDT 2008,245000,38.562296,-121.467489 221 PICASSO CIR,SACRAMENTO,95835,CA,0,0,0,Residential,Tue May 20 00:00:00 EDT 2008,250000,38.676658,-121.528128 5706 GREENACRES WAY,ORANGEVALE,95662,CA,3,2,1176,Residential,Tue May 20 00:00:00 EDT 2008,250000,38.669882,-121.213533 6900 LONICERA DR,ORANGEVALE,95662,CA,4,2,1456,Residential,Tue May 20 00:00:00 EDT 2008,250000,38.692199,-121.250975 419 DAWNRIDGE RD,ROSEVILLE,95678,CA,3,2,1498,Residential,Tue May 20 00:00:00 EDT 2008,250000,38.725283,-121.297953 5312 MARBURY WAY,ANTELOPE,95843,CA,3,2,1574,Residential,Tue May 20 00:00:00 EDT 2008,255000,38.710221,-121.341651 6344 BONHAM CIR,CITRUS HEIGHTS,95610,CA,5,4,2085,Multi-Family,Tue May 20 00:00:00 EDT 2008,256054,38.682358,-121.272876 8207 YORKTON WAY,SACRAMENTO,95829,CA,3,2,2170,Residential,Tue May 20 00:00:00 EDT 2008,257729,38.45967,-121.360461 7922 MANSELL WAY,ELK GROVE,95758,CA,4,2,1595,Residential,Tue May 20 00:00:00 EDT 2008,260000,38.409634,-121.410787 5712 MELBURY CIR,ANTELOPE,95843,CA,3,2,1567,Residential,Tue May 20 00:00:00 EDT 2008,261000,38.705849,-121.334701 632 NEWBRIDGE LN,LINCOLN,95648,CA,4,2,0,Residential,Tue May 20 00:00:00 EDT 2008,261800,38.879084,-121.298586 1570 GLIDDEN AVE,SACRAMENTO,95822,CA,4,2,1253,Residential,Tue May 20 00:00:00 EDT 2008,264469,38.482704,-121.500433 8108 FILIFERA WAY,ANTELOPE,95843,CA,4,3,1768,Residential,Tue May 20 00:00:00 EDT 2008,265000,38.717042,-121.35468 230 BANKSIDE WAY,SACRAMENTO,95835,CA,0,0,0,Residential,Tue May 20 00:00:00 EDT 2008,270000,38.676937,-121.529244 5342 CALABRIA WAY,SACRAMENTO,95835,CA,4,3,2030,Residential,Tue May 20 00:00:00 EDT 2008,270000,38.671807,-121.498274 47 NAPONEE CT,SACRAMENTO,95835,CA,3,2,1531,Residential,Tue May 20 00:00:00 EDT 2008,270000,38.665704,-121.529096 4236 ADRIATIC SEA WAY,SACRAMENTO,95834,CA,0,0,0,Residential,Tue May 20 00:00:00 EDT 2008,270000,38.647961,-121.543162 8864 REMBRANT CT,ELK GROVE,95624,CA,4,3,1653,Residential,Tue May 20 00:00:00 EDT 2008,275000,38.435288,-121.375703 9455 SEA CLIFF WAY,ELK GROVE,95758,CA,4,2,2056,Residential,Tue May 20 00:00:00 EDT 2008,275000,38.411522,-121.481406 9720 LITTLE HARBOR WAY,ELK GROVE,95624,CA,4,3,2494,Residential,Tue May 20 00:00:00 EDT 2008,280000,38.404934,-121.352405 8806 PHOENIX AVE,FAIR OAKS,95628,CA,3,2,1450,Residential,Tue May 20 00:00:00 EDT 2008,286013,38.660322,-121.230101 3578 LOGGERHEAD WAY,SACRAMENTO,95834,CA,4,2,2169,Residential,Tue May 20 00:00:00 EDT 2008,292000,38.633028,-121.526755 1416 LOCKHART WAY,ROSEVILLE,95747,CA,3,2,1440,Residential,Tue May 20 00:00:00 EDT 2008,292000,38.752399,-121.330328 5413 BUENA VENTURA WAY,FAIR OAKS,95628,CA,3,2,1527,Residential,Tue May 20 00:00:00 EDT 2008,293993,38.664552,-121.255937 37 WHITE BIRCH CT,ROSEVILLE,95678,CA,3,2,1401,Residential,Tue May 20 00:00:00 EDT 2008,294000,38.776327,-121.284514 405 MARLIN SPIKE WAY,SACRAMENTO,95838,CA,3,2,1411,Residential,Tue May 20 00:00:00 EDT 2008,296769,38.65783,-121.456842 1102 CHESLEY LN,LINCOLN,95648,CA,4,4,0,Residential,Tue May 20 00:00:00 EDT 2008,297500,38.864864,-121.313988 11281 STANFORD COURT LN Unit 604,GOLD RIVER,95670,CA,0,0,0,Condo,Tue May 20 00:00:00 EDT 2008,300000,38.625289,-121.260286 7320 6TH ST,RIO LINDA,95673,CA,3,1,1284,Residential,Tue May 20 00:00:00 EDT 2008,300000,38.700553,-121.452223 993 MANTON CT,GALT,95632,CA,4,3,2307,Residential,Tue May 20 00:00:00 EDT 2008,300000,38.272942,-121.289148 4487 PANORAMA DR,PLACERVILLE,95667,CA,3,2,1329,Residential,Tue May 20 00:00:00 EDT 2008,300000,38.694559,-120.848157 5651 OVERLEAF WAY,SACRAMENTO,95835,CA,4,2,1910,Residential,Tue May 20 00:00:00 EDT 2008,300500,38.677454,-121.494791 2015 PROMONTORY POINT LN,GOLD RIVER,95670,CA,3,2,1981,Residential,Tue May 20 00:00:00 EDT 2008,305000,38.628732,-121.261149 3224 PARKHAM DR,ROSEVILLE,95747,CA,0,0,0,Residential,Tue May 20 00:00:00 EDT 2008,306500,38.772771,-121.364877 15 VANESSA PL,SACRAMENTO,95835,CA,0,0,0,Residential,Tue May 20 00:00:00 EDT 2008,312500,38.668692,-121.54549 1312 RENISON LN,LINCOLN,95648,CA,5,3,0,Residential,Tue May 20 00:00:00 EDT 2008,315000,38.866409,-121.308485 8 RIVER RAFT CT,SACRAMENTO,95823,CA,4,2,2205,Residential,Tue May 20 00:00:00 EDT 2008,319789,38.447353,-121.434969 2251 LAMPLIGHT LN,LINCOLN,95648,CA,2,2,1449,Residential,Tue May 20 00:00:00 EDT 2008,330000,38.849924,-121.275729 106 FARHAM DR,FOLSOM,95630,CA,3,2,1258,Residential,Tue May 20 00:00:00 EDT 2008,330000,38.667834,-121.168578 5405 NECTAR CIR,ELK GROVE,95757,CA,3,2,2575,Residential,Tue May 20 00:00:00 EDT 2008,331000,38.387014,-121.440967 5411 10TH AVE,SACRAMENTO,95820,CA,2,1,539,Residential,Tue May 20 00:00:00 EDT 2008,334000,38.542727,-121.442449 3512 RAINSONG CIR,RANCHO CORDOVA,95670,CA,4,3,2208,Residential,Tue May 20 00:00:00 EDT 2008,336000,38.573488,-121.282809 1106 55TH ST,SACRAMENTO,95819,CA,3,1,1108,Residential,Tue May 20 00:00:00 EDT 2008,339000,38.563805,-121.436395 411 ILLSLEY WAY,FOLSOM,95630,CA,4,2,1595,Residential,Tue May 20 00:00:00 EDT 2008,339000,38.652002,-121.129504 796 BUTTERCUP CIR,GALT,95632,CA,4,2,2159,Residential,Tue May 20 00:00:00 EDT 2008,345000,38.279581,-121.300828 1230 SANDRA CIR,PLACERVILLE,95667,CA,4,3,2295,Residential,Tue May 20 00:00:00 EDT 2008,350000,38.738141,-120.784145 318 ANACAPA DR,ROSEVILLE,95678,CA,3,2,1838,Residential,Tue May 20 00:00:00 EDT 2008,356000,38.782094,-121.297133 3975 SHINING STAR DR,SACRAMENTO,95823,CA,4,2,1900,Residential,Tue May 20 00:00:00 EDT 2008,361745,38.487409,-121.461413 1620 BASLER ST,SACRAMENTO,95811,CA,4,2,1718,Residential,Tue May 20 00:00:00 EDT 2008,361948,38.591822,-121.478644 9688 NATURE TRAIL WAY,ELK GROVE,95757,CA,5,3,3389,Residential,Tue May 20 00:00:00 EDT 2008,370000,38.405224,-121.479275 5924 TANUS CIR,ROCKLIN,95677,CA,4,2,0,Residential,Tue May 20 00:00:00 EDT 2008,380000,38.778691,-121.204292 9629 CEDAR OAK WAY,ELK GROVE,95757,CA,5,4,3260,Residential,Tue May 20 00:00:00 EDT 2008,385000,38.405527,-121.431746 3429 FERNBROOK CT,CAMERON PARK,95682,CA,3,2,2016,Residential,Tue May 20 00:00:00 EDT 2008,399000,38.664225,-121.007173 2121 HANNAH WAY,ROCKLIN,95765,CA,4,2,2607,Residential,Tue May 20 00:00:00 EDT 2008,402000,38.805749,-121.280931 10104 ANNIE ST,ELK GROVE,95757,CA,4,3,2724,Residential,Tue May 20 00:00:00 EDT 2008,406026,38.390465,-121.443479 1092 MAUGHAM CT,GALT,95632,CA,5,4,3746,Residential,Tue May 20 00:00:00 EDT 2008,420000,38.271646,-121.286848 5404 ALMOND FALLS WAY,RANCHO CORDOVA,95742,CA,0,0,0,Residential,Tue May 20 00:00:00 EDT 2008,425000,38.527502,-121.233492 6306 CONEJO,RANCHO MURIETA,95683,CA,4,2,3192,Residential,Tue May 20 00:00:00 EDT 2008,425000,38.512602,-121.087233 14 CASA VATONI PL,SACRAMENTO,95834,CA,0,0,0,Residential,Tue May 20 00:00:00 EDT 2008,433500,38.650221,-121.551704 1456 EAGLESFIELD LN,LINCOLN,95648,CA,4,3,0,Residential,Tue May 20 00:00:00 EDT 2008,436746,38.857635,-121.311375 4100 BOTHWELL CIR,EL DORADO HILLS,95762,CA,5,3,0,Residential,Tue May 20 00:00:00 EDT 2008,438700,38.679136,-121.034329 427 21ST ST,SACRAMENTO,95811,CA,2,1,1247,Residential,Tue May 20 00:00:00 EDT 2008,445000,38.582604,-121.47576 1044 GALSTON DR,FOLSOM,95630,CA,4,2,2581,Residential,Tue May 20 00:00:00 EDT 2008,450000,38.676306,-121.09954 4440 SYCAMORE AVE,SACRAMENTO,95841,CA,3,1,2068,Residential,Tue May 20 00:00:00 EDT 2008,460000,38.646374,-121.353658 1032 SOUZA DR,EL DORADO HILLS,95762,CA,3,2,0,Residential,Tue May 20 00:00:00 EDT 2008,460000,38.668239,-121.064437 9760 LAZULITE CT,ELK GROVE,95624,CA,4,3,3992,Residential,Tue May 20 00:00:00 EDT 2008,460000,38.403609,-121.335541 241 LANFRANCO CIR,SACRAMENTO,95835,CA,4,4,3397,Residential,Tue May 20 00:00:00 EDT 2008,465000,38.665696,-121.549437 5559 NORTHBOROUGH DR,SACRAMENTO,95835,CA,5,3,3881,Residential,Tue May 20 00:00:00 EDT 2008,471750,38.677225,-121.519687 2125 BIG SKY DR,ROCKLIN,95765,CA,5,3,0,Residential,Tue May 20 00:00:00 EDT 2008,480000,38.801637,-121.278798 2109 HAMLET PL,CARMICHAEL,95608,CA,2,2,1598,Residential,Tue May 20 00:00:00 EDT 2008,484000,38.602754,-121.329326 9970 STATE HIGHWAY 193,PLACERVILLE,95667,CA,4,3,1929,Residential,Tue May 20 00:00:00 EDT 2008,485000,38.787877,-120.816676 2901 PINTAIL WAY,ELK GROVE,95757,CA,4,3,3070,Residential,Tue May 20 00:00:00 EDT 2008,495000,38.398488,-121.473424 201 FIRESTONE DR,ROSEVILLE,95678,CA,0,0,0,Residential,Tue May 20 00:00:00 EDT 2008,500500,38.770153,-121.300039 1740 HIGH ST,AUBURN,95603,CA,3,3,0,Residential,Tue May 20 00:00:00 EDT 2008,504000,38.891935,-121.08434 2733 DANA LOOP,EL DORADO HILLS,95762,CA,0,0,0,Residential,Tue May 20 00:00:00 EDT 2008,541000,38.628459,-121.055078 9741 SADDLEBRED CT,WILTON,95693,CA,0,0,0,Residential,Tue May 20 00:00:00 EDT 2008,560000,38.408841,-121.198039 7756 TIGERWOODS DR,SACRAMENTO,95829,CA,5,3,3984,Residential,Tue May 20 00:00:00 EDT 2008,572500,38.47643,-121.309243 5709 RIVER OAK WAY,CARMICHAEL,95608,CA,4,2,2222,Residential,Tue May 20 00:00:00 EDT 2008,582000,38.602461,-121.330979 2981 WRINGER DR,ROSEVILLE,95661,CA,4,3,3838,Residential,Tue May 20 00:00:00 EDT 2008,613401,38.735373,-121.227072 8616 ROCKPORTE CT,ROSEVILLE,95747,CA,4,2,0,Residential,Tue May 20 00:00:00 EDT 2008,614000,38.742118,-121.359909 4128 HILL ST,FAIR OAKS,95628,CA,5,5,2846,Residential,Tue May 20 00:00:00 EDT 2008,680000,38.64167,-121.262099 1409 47TH ST,SACRAMENTO,95819,CA,5,2,2484,Residential,Tue May 20 00:00:00 EDT 2008,699000,38.563244,-121.446876 3935 EL MONTE DR,LOOMIS,95650,CA,4,4,1624,Residential,Tue May 20 00:00:00 EDT 2008,839000,38.813337,-121.133348 5840 WALERGA RD,SACRAMENTO,95842,CA,2,1,840,Condo,Mon May 19 00:00:00 EDT 2008,40000,38.673678,-121.357471 923 FULTON AVE,SACRAMENTO,95825,CA,1,1,484,Condo,Mon May 19 00:00:00 EDT 2008,48000,38.582279,-121.401482 261 REDONDO AVE,SACRAMENTO,95815,CA,3,1,970,Residential,Mon May 19 00:00:00 EDT 2008,61500,38.620685,-121.460539 4030 BROADWAY,SACRAMENTO,95817,CA,2,1,623,Residential,Mon May 19 00:00:00 EDT 2008,62050,38.546798,-121.460038 3660 22ND AVE,SACRAMENTO,95820,CA,2,1,932,Residential,Mon May 19 00:00:00 EDT 2008,65000,38.532718,-121.46747 3924 HIGH ST,SACRAMENTO,95838,CA,2,1,796,Residential,Mon May 19 00:00:00 EDT 2008,65000,38.638797,-121.435049 4734 14TH AVE,SACRAMENTO,95820,CA,2,1,834,Residential,Mon May 19 00:00:00 EDT 2008,68000,38.539447,-121.450858 4734 14TH AVE,SACRAMENTO,95820,CA,2,1,834,Residential,Mon May 19 00:00:00 EDT 2008,68000,38.539447,-121.450858 5050 RHODE ISLAND DR Unit 4,SACRAMENTO,95841,CA,2,1,924,Condo,Mon May 19 00:00:00 EDT 2008,77000,38.658739,-121.333561 4513 GREENHOLME DR,SACRAMENTO,95842,CA,2,1,795,Condo,Mon May 19 00:00:00 EDT 2008,82732,38.669104,-121.359008 3845 ELM ST,SACRAMENTO,95838,CA,3,1,1250,Residential,Mon May 19 00:00:00 EDT 2008,84000,38.637337,-121.432835 3908 17TH AVE,SACRAMENTO,95820,CA,2,1,984,Residential,Mon May 19 00:00:00 EDT 2008,84675,38.53728,-121.463531 7109 CHANDLER DR,SACRAMENTO,95828,CA,3,1,1013,Residential,Mon May 19 00:00:00 EDT 2008,85000,38.497237,-121.424187 7541 SKELTON WAY,SACRAMENTO,95822,CA,3,1,1012,Residential,Mon May 19 00:00:00 EDT 2008,90000,38.484274,-121.488851 9058 MONTOYA ST,SACRAMENTO,95826,CA,2,1,795,Condo,Mon May 19 00:00:00 EDT 2008,90000,38.559144,-121.368387 1016 CONGRESS AVE,SACRAMENTO,95838,CA,2,2,918,Residential,Mon May 19 00:00:00 EDT 2008,91000,38.630151,-121.442789 540 MORRISON AVE,SACRAMENTO,95838,CA,3,1,1082,Residential,Mon May 19 00:00:00 EDT 2008,95000,38.637704,-121.453946 5303 JERRETT WAY,SACRAMENTO,95842,CA,2,1,964,Residential,Mon May 19 00:00:00 EDT 2008,97500,38.663282,-121.359631 2820 DEL PASO BLVD,SACRAMENTO,95815,CA,4,2,1404,Multi-Family,Mon May 19 00:00:00 EDT 2008,100000,38.617718,-121.440089 3715 TALLYHO DR Unit 78HIGH,SACRAMENTO,95826,CA,1,1,625,Condo,Mon May 19 00:00:00 EDT 2008,100000,38.544627,-121.35796 6013 ROWAN WAY,CITRUS HEIGHTS,95621,CA,2,1,888,Residential,Mon May 19 00:00:00 EDT 2008,101000,38.675893,-121.2963 2987 PONDEROSA LN,SACRAMENTO,95815,CA,4,2,1120,Residential,Mon May 19 00:00:00 EDT 2008,102750,38.622243,-121.457863 3732 LANKERSHIM WAY,NORTH HIGHLANDS,95660,CA,3,1,1331,Residential,Mon May 19 00:00:00 EDT 2008,112500,38.68972,-121.378399 2216 DUNLAP DR,SACRAMENTO,95821,CA,3,1,1014,Residential,Mon May 19 00:00:00 EDT 2008,113000,38.623738,-121.41305 3503 21ST AVE,SACRAMENTO,95820,CA,4,2,1448,Residential,Mon May 19 00:00:00 EDT 2008,114000,38.53361,-121.469308 523 EXCHANGE ST,SACRAMENTO,95838,CA,3,1,966,Residential,Mon May 19 00:00:00 EDT 2008,114000,38.659414,-121.45408 8101 PORT ROYALE WAY,SACRAMENTO,95823,CA,2,1,779,Residential,Mon May 19 00:00:00 EDT 2008,114750,38.463929,-121.438667 8020 WALERGA RD,ANTELOPE,95843,CA,2,2,836,Condo,Mon May 19 00:00:00 EDT 2008,115000,38.71607,-121.364468 167 VALLEY OAK DR,ROSEVILLE,95678,CA,2,2,1100,Condo,Mon May 19 00:00:00 EDT 2008,115000,38.732429,-121.288069 7876 BURLINGTON WAY,SACRAMENTO,95832,CA,3,1,1174,Residential,Mon May 19 00:00:00 EDT 2008,116100,38.470093,-121.468347 3726 JONKO AVE,NORTH HIGHLANDS,95660,CA,3,2,1207,Residential,Mon May 19 00:00:00 EDT 2008,119250,38.656131,-121.377265 7342 GIGI PL,SACRAMENTO,95828,CA,4,4,1995,Multi-Family,Mon May 19 00:00:00 EDT 2008,120000,38.490704,-121.410176 2610 PHYLLIS AVE,SACRAMENTO,95820,CA,2,1,804,Residential,Mon May 19 00:00:00 EDT 2008,120000,38.53105,-121.479574 4200 COMMERCE WAY Unit 711,SACRAMENTO,95834,CA,2,2,958,Condo,Mon May 19 00:00:00 EDT 2008,120000,38.647523,-121.523217 4621 COUNTRY SCENE WAY,SACRAMENTO,95823,CA,3,2,1366,Residential,Mon May 19 00:00:00 EDT 2008,120108,38.470187,-121.448149 5380 VILLAGE WOOD DR,SACRAMENTO,95823,CA,2,2,901,Residential,Mon May 19 00:00:00 EDT 2008,121500,38.454949,-121.440578 2621 EVERGREEN ST,SACRAMENTO,95815,CA,3,1,696,Residential,Mon May 19 00:00:00 EDT 2008,121725,38.613103,-121.444085 201 CARLO CT,GALT,95632,CA,3,2,1080,Residential,Mon May 19 00:00:00 EDT 2008,122000,38.24227,-121.31032 6743 21ST ST,SACRAMENTO,95822,CA,3,2,1104,Residential,Mon May 19 00:00:00 EDT 2008,123000,38.50372,-121.490657 3128 VIA GRANDE,SACRAMENTO,95825,CA,2,1,972,Residential,Mon May 19 00:00:00 EDT 2008,125000,38.598321,-121.39161 2847 BELGRADE WAY,SACRAMENTO,95833,CA,4,2,1390,Residential,Mon May 19 00:00:00 EDT 2008,125573,38.617173,-121.482541 7741 MILLDALE CIR,ELVERTA,95626,CA,4,2,1354,Residential,Mon May 19 00:00:00 EDT 2008,126714,38.705834,-121.43919 9013 CASALS ST,SACRAMENTO,95826,CA,2,1,795,Condo,Mon May 19 00:00:00 EDT 2008,126960,38.557045,-121.37167 227 MAHAN CT Unit 1,ROSEVILLE,95678,CA,2,1,780,Condo,Mon May 19 00:00:00 EDT 2008,127000,38.749723,-121.27008 7349 FLETCHER FARM DR,SACRAMENTO,95828,CA,4,2,1587,Residential,Mon May 19 00:00:00 EDT 2008,127500,38.49069,-121.382619 7226 LARCHMONT DR,NORTH HIGHLANDS,95660,CA,3,2,1209,Residential,Mon May 19 00:00:00 EDT 2008,130000,38.699269,-121.376334 4114 35TH AVE,SACRAMENTO,95824,CA,2,1,1139,Residential,Mon May 19 00:00:00 EDT 2008,133105,38.520941,-121.459355 617 M ST,RIO LINDA,95673,CA,2,2,1690,Residential,Mon May 19 00:00:00 EDT 2008,136500,38.691104,-121.451832 7032 FAIR OAKS BLVD,CARMICHAEL,95608,CA,3,2,1245,Condo,Mon May 19 00:00:00 EDT 2008,139500,38.628563,-121.328297 2421 SANTINA WAY,ELVERTA,95626,CA,3,2,1416,Residential,Mon May 19 00:00:00 EDT 2008,140000,38.71865,-121.407763 2368 CRAIG AVE,SACRAMENTO,95832,CA,3,2,1300,Residential,Mon May 19 00:00:00 EDT 2008,140800,38.47807,-121.48114 2123 AMANDA WAY,SACRAMENTO,95822,CA,3,2,1120,Residential,Mon May 19 00:00:00 EDT 2008,145000,38.484896,-121.486948 7620 DARLA WAY,SACRAMENTO,95828,CA,4,2,1590,Residential,Mon May 19 00:00:00 EDT 2008,147000,38.478502,-121.403517 8344 FIELDPOPPY CIR,SACRAMENTO,95828,CA,3,2,1407,Residential,Mon May 19 00:00:00 EDT 2008,149600,38.479083,-121.400702 3624 20TH AVE,SACRAMENTO,95820,CA,5,2,1516,Residential,Mon May 19 00:00:00 EDT 2008,150000,38.534508,-121.467907 10001 WOODCREEK OAKS BLVD Unit 1415,ROSEVILLE,95747,CA,2,2,0,Condo,Mon May 19 00:00:00 EDT 2008,150000,38.795529,-121.328819 2848 PROVO WAY,SACRAMENTO,95822,CA,3,2,1646,Residential,Mon May 19 00:00:00 EDT 2008,150000,38.489759,-121.474754 6045 EHRHARDT AVE,SACRAMENTO,95823,CA,3,2,1676,Residential,Mon May 19 00:00:00 EDT 2008,155000,38.457157,-121.433065 1223 LAMBERTON CIR,SACRAMENTO,95838,CA,3,2,1370,Residential,Mon May 19 00:00:00 EDT 2008,155435,38.646677,-121.437573 1223 LAMBERTON CIR,SACRAMENTO,95838,CA,3,2,1370,Residential,Mon May 19 00:00:00 EDT 2008,155500,38.646677,-121.437573 6000 BIRCHGLADE WAY,CITRUS HEIGHTS,95621,CA,4,2,1351,Residential,Mon May 19 00:00:00 EDT 2008,158000,38.70166,-121.323249 7204 THOMAS DR,NORTH HIGHLANDS,95660,CA,3,2,1152,Residential,Mon May 19 00:00:00 EDT 2008,158000,38.697898,-121.377687 8363 LANGTREE WAY,SACRAMENTO,95823,CA,3,2,1452,Residential,Mon May 19 00:00:00 EDT 2008,160000,38.45356,-121.435959 1675 VERNON ST Unit 8,ROSEVILLE,95678,CA,2,1,990,Residential,Mon May 19 00:00:00 EDT 2008,160000,38.734136,-121.299639 6632 IBEX WOODS CT,CITRUS HEIGHTS,95621,CA,2,2,1162,Residential,Mon May 19 00:00:00 EDT 2008,164000,38.720868,-121.309855 117 EVCAR WAY,RIO LINDA,95673,CA,3,2,1182,Residential,Mon May 19 00:00:00 EDT 2008,164000,38.687659,-121.4633 6485 LAGUNA MIRAGE LN,ELK GROVE,95758,CA,2,2,1112,Residential,Mon May 19 00:00:00 EDT 2008,165000,38.42465,-121.430137 746 MOOSE CREEK WAY,GALT,95632,CA,3,2,1100,Residential,Mon May 19 00:00:00 EDT 2008,167000,38.283085,-121.302071 8306 CURLEW CT,CITRUS HEIGHTS,95621,CA,4,2,1280,Residential,Mon May 19 00:00:00 EDT 2008,167293,38.715781,-121.298519 8306 CURLEW CT,CITRUS HEIGHTS,95621,CA,4,2,1280,Residential,Mon May 19 00:00:00 EDT 2008,167293,38.715781,-121.298519 5217 ARGO WAY,SACRAMENTO,95820,CA,3,1,1039,Residential,Mon May 19 00:00:00 EDT 2008,168000,38.52774,-121.433669 7108 HEATHER TREE DR,SACRAMENTO,95842,CA,3,2,1159,Residential,Mon May 19 00:00:00 EDT 2008,170000,38.695677,-121.36022 2956 DAVENPORT WAY,SACRAMENTO,95833,CA,4,2,1917,Residential,Mon May 19 00:00:00 EDT 2008,170000,38.620687,-121.482619 10062 LINCOLN VILLAGE DR,SACRAMENTO,95827,CA,3,2,1520,Residential,Mon May 19 00:00:00 EDT 2008,170000,38.564,-121.320023 332 PALIN AVE,GALT,95632,CA,3,2,1204,Residential,Mon May 19 00:00:00 EDT 2008,174000,38.260467,-121.302636 4649 FREEWAY CIR,SACRAMENTO,95841,CA,3,2,1120,Residential,Mon May 19 00:00:00 EDT 2008,178000,38.658734,-121.357196 8593 DERLIN WAY,SACRAMENTO,95823,CA,3,2,1436,Residential,Mon May 19 00:00:00 EDT 2008,180000,38.447585,-121.426627 9273 PREMIER WAY,SACRAMENTO,95826,CA,3,2,1451,Residential,Mon May 19 00:00:00 EDT 2008,180000,38.55992,-121.352539 8032 DUSENBERG CT,SACRAMENTO,95828,CA,4,2,1638,Residential,Mon May 19 00:00:00 EDT 2008,180000,38.466499,-121.381119 7110 STELLA LN Unit 15,CARMICHAEL,95608,CA,2,2,1000,Condo,Mon May 19 00:00:00 EDT 2008,182000,38.637396,-121.300055 1786 PIEDMONT WAY,ROSEVILLE,95661,CA,3,1,1152,Residential,Mon May 19 00:00:00 EDT 2008,188325,38.72748,-121.256537 1347 HIDALGO CIR,ROSEVILLE,95747,CA,3,2,1154,Residential,Mon May 19 00:00:00 EDT 2008,191500,38.747878,-121.311279 212 CAPPUCINO WAY,SACRAMENTO,95838,CA,3,2,1353,Residential,Mon May 19 00:00:00 EDT 2008,192000,38.657811,-121.465327 5938 WOODBRIAR WAY,CITRUS HEIGHTS,95621,CA,3,2,1329,Residential,Mon May 19 00:00:00 EDT 2008,192700,38.706152,-121.325399 3801 WILDROSE WAY,SACRAMENTO,95826,CA,3,1,1356,Residential,Mon May 19 00:00:00 EDT 2008,195000,38.544368,-121.369979 508 SAMUEL WAY,SACRAMENTO,95838,CA,3,2,1505,Residential,Mon May 19 00:00:00 EDT 2008,197654,38.645689,-121.452766 6128 CARL SANDBURG CIR,SACRAMENTO,95842,CA,3,1,1009,Residential,Mon May 19 00:00:00 EDT 2008,198000,38.681541,-121.355616 1 KENNELFORD CIR,SACRAMENTO,95823,CA,3,2,1144,Residential,Mon May 19 00:00:00 EDT 2008,200345,38.46452,-121.427606 909 SINGINGWOOD RD,SACRAMENTO,95864,CA,2,1,930,Residential,Mon May 19 00:00:00 EDT 2008,203000,38.581471,-121.38839 6671 FOXWOOD CT,SACRAMENTO,95841,CA,4,2,1766,Residential,Mon May 19 00:00:00 EDT 2008,207000,38.687943,-121.328883 8165 AYN RAND CT,SACRAMENTO,95828,CA,4,3,1940,Residential,Mon May 19 00:00:00 EDT 2008,208000,38.468639,-121.403265 9474 VILLAGE TREE DR,ELK GROVE,95758,CA,4,2,1776,Residential,Mon May 19 00:00:00 EDT 2008,210000,38.413947,-121.408276 7213 CALVIN DR,CITRUS HEIGHTS,95621,CA,3,1,1258,Residential,Mon May 19 00:00:00 EDT 2008,212000,38.698154,-121.298375 8167 DERBY PARK CT,SACRAMENTO,95828,CA,4,2,1872,Residential,Mon May 19 00:00:00 EDT 2008,213675,38.460492,-121.373379 6344 LAGUNA MIRAGE LN,ELK GROVE,95758,CA,2,2,1112,Residential,Mon May 19 00:00:00 EDT 2008,213697,38.423963,-121.428875 2945 RED HAWK WAY,SACRAMENTO,95833,CA,4,2,1856,Residential,Mon May 19 00:00:00 EDT 2008,215000,38.619675,-121.496903 3228 I ST,SACRAMENTO,95816,CA,4,3,1939,Residential,Mon May 19 00:00:00 EDT 2008,215000,38.573844,-121.462839 308 ATKINSON ST,ROSEVILLE,95678,CA,3,1,998,Residential,Mon May 19 00:00:00 EDT 2008,215100,38.746794,-121.29971 624 HOVEY WAY,ROSEVILLE,95678,CA,3,2,1758,Residential,Mon May 19 00:00:00 EDT 2008,217500,38.756149,-121.306479 110 COPPER LEAF WAY,SACRAMENTO,95838,CA,3,2,2142,Residential,Mon May 19 00:00:00 EDT 2008,218000,38.658466,-121.460661 7535 ALMA VISTA WAY,SACRAMENTO,95831,CA,2,1,950,Residential,Mon May 19 00:00:00 EDT 2008,220000,38.48403,-121.507641 7423 WILSALL CT,ELK GROVE,95758,CA,4,3,1739,Residential,Mon May 19 00:00:00 EDT 2008,221000,38.417026,-121.416821 8629 VIA ALTA WAY,ELK GROVE,95624,CA,3,2,1516,Residential,Mon May 19 00:00:00 EDT 2008,222900,38.398245,-121.380615 3318 DAVIDSON DR,ANTELOPE,95843,CA,3,1,988,Residential,Mon May 19 00:00:00 EDT 2008,223139,38.705753,-121.388917 913 COBDEN CT,GALT,95632,CA,4,2,1555,Residential,Mon May 19 00:00:00 EDT 2008,225500,38.282001,-121.295902 4419 79TH ST,SACRAMENTO,95820,CA,3,2,1212,Residential,Mon May 19 00:00:00 EDT 2008,228327,38.534827,-121.412545 3012 SPOONWOOD WAY,SACRAMENTO,95833,CA,4,2,1871,Residential,Mon May 19 00:00:00 EDT 2008,230000,38.62478,-121.523474 8728 CRYSTAL RIVER WAY,SACRAMENTO,95828,CA,3,2,1302,Residential,Mon May 19 00:00:00 EDT 2008,230000,38.47547,-121.380055 4709 AMBER LN Unit 1,SACRAMENTO,95841,CA,2,1,756,Condo,Mon May 19 00:00:00 EDT 2008,230522,38.657789,-121.354994 4508 OLD DAIRY DR,ANTELOPE,95843,CA,4,3,2026,Residential,Mon May 19 00:00:00 EDT 2008,231200,38.72286,-121.358939 312 RIVER ISLE WAY,SACRAMENTO,95831,CA,3,2,1375,Residential,Mon May 19 00:00:00 EDT 2008,232000,38.49026,-121.550527 301 OLIVADI WAY,SACRAMENTO,95834,CA,2,2,1250,Condo,Mon May 19 00:00:00 EDT 2008,232500,38.644406,-121.549049 5636 25TH ST,SACRAMENTO,95822,CA,3,1,1058,Residential,Mon May 19 00:00:00 EDT 2008,233641,38.523828,-121.481139 8721 SPRUCE RIDGE WAY,ANTELOPE,95843,CA,3,2,1187,Residential,Mon May 19 00:00:00 EDT 2008,234000,38.727657,-121.391028 7461 WINDBRIDGE DR,SACRAMENTO,95831,CA,2,2,1324,Residential,Mon May 19 00:00:00 EDT 2008,234500,38.48797,-121.530229 8101 LEMON COVE CT,SACRAMENTO,95828,CA,4,3,1936,Residential,Mon May 19 00:00:00 EDT 2008,235000,38.462981,-121.408288 10949 SCOTSMAN WAY,RANCHO CORDOVA,95670,CA,5,4,2382,Multi-Family,Mon May 19 00:00:00 EDT 2008,236000,38.603686,-121.277844 617 WILLOW CREEK DR,FOLSOM,95630,CA,3,2,1427,Residential,Mon May 19 00:00:00 EDT 2008,236073,38.679626,-121.142609 3301 PARK DR Unit 1914,SACRAMENTO,95835,CA,3,2,1678,Condo,Mon May 19 00:00:00 EDT 2008,238000,38.665296,-121.531993 709 CIMMARON CT,GALT,95632,CA,4,2,1798,Residential,Mon May 19 00:00:00 EDT 2008,238861,38.277177,-121.303747 3305 RIO ROCA CT,ANTELOPE,95843,CA,4,3,2652,Residential,Mon May 19 00:00:00 EDT 2008,239700,38.725079,-121.387698 9080 BEDROCK CT,SACRAMENTO,95829,CA,4,2,1816,Residential,Mon May 19 00:00:00 EDT 2008,240000,38.456939,-121.362965 100 TOURMALINE CIR,SACRAMENTO,95834,CA,5,3,3076,Residential,Mon May 19 00:00:00 EDT 2008,240000,38.63437,-121.510779 6411 RED BIRCH WAY,ELK GROVE,95758,CA,4,2,1844,Residential,Mon May 19 00:00:00 EDT 2008,241000,38.43461,-121.429316 4867 LAGUNA DR,SACRAMENTO,95823,CA,3,2,1306,Residential,Mon May 19 00:00:00 EDT 2008,245000,38.46179,-121.445371 3662 RIVER DR,SACRAMENTO,95833,CA,4,3,2447,Residential,Mon May 19 00:00:00 EDT 2008,246000,38.604969,-121.54255 6943 WOLFGRAM WAY,SACRAMENTO,95828,CA,4,2,1176,Residential,Mon May 19 00:00:00 EDT 2008,247234,38.489215,-121.419546 77 RINETTI WAY,RIO LINDA,95673,CA,4,2,1182,Residential,Mon May 19 00:00:00 EDT 2008,247480,38.687021,-121.463151 1316 I ST,RIO LINDA,95673,CA,3,1,1160,Residential,Mon May 19 00:00:00 EDT 2008,249862,38.683674,-121.435204 2130 CATHERWOOD WAY,SACRAMENTO,95835,CA,3,2,1424,Residential,Mon May 19 00:00:00 EDT 2008,251000,38.675506,-121.510987 8304 JUGLANS DR,ORANGEVALE,95662,CA,4,2,1574,Residential,Mon May 19 00:00:00 EDT 2008,252155,38.691829,-121.249033 5308 MARBURY WAY,ANTELOPE,95843,CA,3,2,1830,Residential,Mon May 19 00:00:00 EDT 2008,254172,38.710221,-121.341707 9182 LAKEMONT DR,ELK GROVE,95624,CA,4,2,1724,Residential,Mon May 19 00:00:00 EDT 2008,258000,38.451353,-121.358776 2231 COUNTRY VILLA CT,AUBURN,95603,CA,2,2,1255,Condo,Mon May 19 00:00:00 EDT 2008,260000,38.931671,-121.097862 8491 CRYSTAL WALK CIR,ELK GROVE,95758,CA,0,0,0,Residential,Mon May 19 00:00:00 EDT 2008,261000,38.416916,-121.407554 361 MAHONIA CIR,SACRAMENTO,95835,CA,4,3,2175,Residential,Mon May 19 00:00:00 EDT 2008,261000,38.676172,-121.509761 3427 LA CADENA WAY,SACRAMENTO,95835,CA,4,2,1904,Residential,Mon May 19 00:00:00 EDT 2008,261000,38.681194,-121.537351 955 BIG SUR CT,EL DORADO HILLS,95762,CA,4,2,1808,Residential,Mon May 19 00:00:00 EDT 2008,262500,38.664347,-121.076529 11826 DIONYSUS WAY,RANCHO CORDOVA,95742,CA,4,2,2711,Residential,Mon May 19 00:00:00 EDT 2008,266000,38.551046,-121.239411 5847 DEL CAMPO LN,CARMICHAEL,95608,CA,3,1,1713,Residential,Mon May 19 00:00:00 EDT 2008,266000,38.671995,-121.324339 5635 FOXVIEW WAY,ELK GROVE,95757,CA,3,2,1457,Residential,Mon May 19 00:00:00 EDT 2008,270000,38.395256,-121.438249 10372 VIA CINTA CT,ELK GROVE,95757,CA,4,3,2724,Residential,Mon May 19 00:00:00 EDT 2008,274425,38.380089,-121.428186 6286 LONETREE BLVD,ROCKLIN,95765,CA,0,0,0,Residential,Mon May 19 00:00:00 EDT 2008,274500,38.805036,-121.293608 7744 SOUTHBREEZE DR,SACRAMENTO,95828,CA,3,2,1468,Residential,Mon May 19 00:00:00 EDT 2008,275336,38.476932,-121.378349 2242 ABLE WAY,SACRAMENTO,95835,CA,4,3,2550,Residential,Mon May 19 00:00:00 EDT 2008,277980,38.666074,-121.509743 1042 STARBROOK DR,GALT,95632,CA,4,2,1928,Residential,Mon May 19 00:00:00 EDT 2008,280000,38.285611,-121.293063 1219 G ST,SACRAMENTO,95814,CA,3,3,1922,Residential,Mon May 19 00:00:00 EDT 2008,284686,38.582818,-121.489096 6220 OPUS CT,CITRUS HEIGHTS,95621,CA,3,2,1343,Residential,Mon May 19 00:00:00 EDT 2008,284893,38.715853,-121.317095 5419 HAVENHURST CIR,ROCKLIN,95677,CA,3,2,1510,Residential,Mon May 19 00:00:00 EDT 2008,285000,38.786746,-121.209957 220 OLD AIRPORT RD,AUBURN,95603,CA,2,2,960,Multi-Family,Mon May 19 00:00:00 EDT 2008,285000,38.939802,-121.054575 4622 MEYER WAY,CARMICHAEL,95608,CA,4,2,1559,Residential,Mon May 19 00:00:00 EDT 2008,285000,38.64913,-121.310667 4885 SUMMIT VIEW DR,EL DORADO,95623,CA,3,2,1624,Residential,Mon May 19 00:00:00 EDT 2008,289000,38.673285,-120.879176 26 JEANROSS CT,SACRAMENTO,95832,CA,5,3,2992,Residential,Mon May 19 00:00:00 EDT 2008,295000,38.473162,-121.491085 4800 MAPLEPLAIN AVE,ELK GROVE,95758,CA,4,2,2109,Residential,Mon May 19 00:00:00 EDT 2008,296000,38.432848,-121.449237 10629 BASIE WAY,RANCHO CORDOVA,95670,CA,4,2,1524,Residential,Mon May 19 00:00:00 EDT 2008,296056,38.579,-121.292627 8612 WILLOW GROVE WAY,SACRAMENTO,95828,CA,3,2,1248,Residential,Mon May 19 00:00:00 EDT 2008,297359,38.464994,-121.386962 62 DE FER CIR,SACRAMENTO,95823,CA,4,2,1876,Residential,Mon May 19 00:00:00 EDT 2008,299940,38.49254,-121.463316 2513 OLD KENMARE RD,LINCOLN,95648,CA,5,3,0,Residential,Mon May 19 00:00:00 EDT 2008,304000,38.847396,-121.259586 3253 ABOTO WAY,RANCHO CORDOVA,95670,CA,4,3,1851,Residential,Mon May 19 00:00:00 EDT 2008,305000,38.57727,-121.285591 3072 VILLAGE PLAZA DR,ROSEVILLE,95747,CA,0,0,0,Residential,Mon May 19 00:00:00 EDT 2008,307000,38.773094,-121.365905 251 CHANGO CIR,SACRAMENTO,95835,CA,4,2,2218,Residential,Mon May 19 00:00:00 EDT 2008,311328,38.68237,-121.539147 8205 WEYBURN CT,SACRAMENTO,95828,CA,3,2,1394,Residential,Mon May 19 00:00:00 EDT 2008,313138,38.47316,-121.403893 8788 LA MARGARITA WAY,SACRAMENTO,95828,CA,3,2,1410,Residential,Mon May 19 00:00:00 EDT 2008,316630,38.468185,-121.375694 5912 DEEPDALE WAY,ELK GROVE,95758,CA,5,3,3468,Residential,Mon May 19 00:00:00 EDT 2008,320000,38.439565,-121.436606 4712 PISMO BEACH DR,ANTELOPE,95843,CA,5,3,2346,Residential,Mon May 19 00:00:00 EDT 2008,320000,38.707705,-121.354153 4741 PACIFIC PARK DR,ANTELOPE,95843,CA,5,3,2347,Residential,Mon May 19 00:00:00 EDT 2008,325000,38.709299,-121.353056 310 GROTH CIR,SACRAMENTO,95834,CA,4,2,1659,Residential,Mon May 19 00:00:00 EDT 2008,328578,38.638764,-121.531827 6121 WILD FOX CT,ELK GROVE,95757,CA,3,3,2442,Residential,Mon May 19 00:00:00 EDT 2008,331000,38.406758,-121.431669 12241 CANYONLANDS DR,RANCHO CORDOVA,95742,CA,0,0,0,Residential,Mon May 19 00:00:00 EDT 2008,331500,38.557293,-121.217611 29 COOL FOUNTAIN CT,SACRAMENTO,95833,CA,4,2,2155,Residential,Mon May 19 00:00:00 EDT 2008,340000,38.606906,-121.54132 907 RIO ROBLES AVE,SACRAMENTO,95838,CA,0,0,0,Residential,Mon May 19 00:00:00 EDT 2008,344755,38.664765,-121.445006 8909 BILLFISH WAY,SACRAMENTO,95828,CA,3,2,1810,Residential,Mon May 19 00:00:00 EDT 2008,345746,38.475433,-121.372584 6232 GUS WAY,ELK GROVE,95757,CA,4,2,2789,Residential,Mon May 19 00:00:00 EDT 2008,351000,38.388129,-121.43117 200 OAKWILDE ST,GALT,95632,CA,4,2,1606,Residential,Mon May 19 00:00:00 EDT 2008,353767,38.2535,-121.31812 1033 PARK STREAM DR,GALT,95632,CA,0,0,0,Residential,Mon May 19 00:00:00 EDT 2008,355000,38.287785,-121.289903 200 ALLAIRE CIR,SACRAMENTO,95835,CA,4,2,2166,Residential,Mon May 19 00:00:00 EDT 2008,356035,38.68318,-121.53484 1322 SUTTER WALK,SACRAMENTO,95816,CA,0,0,0,Condo,Mon May 19 00:00:00 EDT 2008,360000,38.53805,-121.5047 5479 NICKMAN WAY,SACRAMENTO,95835,CA,4,2,1871,Residential,Mon May 19 00:00:00 EDT 2008,360552,38.672966,-121.502748 2103 BURBERRY WAY,SACRAMENTO,95835,CA,3,2,1800,Residential,Mon May 19 00:00:00 EDT 2008,362305,38.67342,-121.508542 2450 SAN JOSE WAY,SACRAMENTO,95817,CA,3,1,1683,Residential,Mon May 19 00:00:00 EDT 2008,365000,38.553596,-121.459483 7641 ROSEHALL DR,ROSEVILLE,95678,CA,3,2,0,Residential,Mon May 19 00:00:00 EDT 2008,367554,38.791617,-121.286147 1336 LAYSAN TEAL DR,ROSEVILLE,95747,CA,0,0,0,Residential,Mon May 19 00:00:00 EDT 2008,368500,38.796121,-121.319963 2802 BLACK OAK DR,ROCKLIN,95765,CA,2,2,1596,Residential,Mon May 19 00:00:00 EDT 2008,370000,38.837006,-121.232024 2113 FALL TRAIL CT,PLACERVILLE,95667,CA,4,2,0,Residential,Mon May 19 00:00:00 EDT 2008,371086,38.733155,-120.748039 10112 LAMBEAU CT,ELK GROVE,95757,CA,3,2,1179,Residential,Mon May 19 00:00:00 EDT 2008,378000,38.390328,-121.448022 6313 CASTRO VERDE WAY,ELK GROVE,95757,CA,0,0,0,Residential,Mon May 19 00:00:00 EDT 2008,383000,38.381102,-121.42901 3622 CURTIS DR,SACRAMENTO,95818,CA,3,1,1639,Residential,Mon May 19 00:00:00 EDT 2008,388000,38.541735,-121.480098 11817 OPAL RIDGE WAY,RANCHO CORDOVA,95742,CA,5,3,3281,Residential,Mon May 19 00:00:00 EDT 2008,395100,38.551083,-121.237476 170 LAGOMARSINO WAY,SACRAMENTO,95819,CA,3,2,1697,Residential,Mon May 19 00:00:00 EDT 2008,400000,38.574894,-121.435806 2743 DEAKIN PL,EL DORADO HILLS,95762,CA,3,2,0,Residential,Mon May 19 00:00:00 EDT 2008,400000,38.69288,-121.073551 3361 ALDER CANYON WAY,ANTELOPE,95843,CA,4,3,2085,Residential,Mon May 19 00:00:00 EDT 2008,408431,38.727649,-121.385656 2148 RANCH VIEW DR,ROCKLIN,95765,CA,0,0,0,Residential,Mon May 19 00:00:00 EDT 2008,413000,38.837455,-121.289337 398 LINDLEY DR,SACRAMENTO,95815,CA,4,2,1744,Multi-Family,Mon May 19 00:00:00 EDT 2008,416767,38.622359,-121.457582 3013 BRIDLEWOOD DR,EL DORADO HILLS,95762,CA,4,3,0,Residential,Mon May 19 00:00:00 EDT 2008,420000,38.675519,-121.015862 169 BAURER CIR,FOLSOM,95630,CA,4,3,1939,Residential,Mon May 19 00:00:00 EDT 2008,423000,38.66695,-121.120729 2809 LOON CT,CAMERON PARK,95682,CA,4,2,0,Residential,Mon May 19 00:00:00 EDT 2008,423000,38.687072,-121.004729 1315 KONDOS AVE,SACRAMENTO,95814,CA,2,3,1788,Residential,Mon May 19 00:00:00 EDT 2008,427500,38.571943,-121.492106 4966 CHARTER RD,ROCKLIN,95765,CA,3,2,1691,Residential,Mon May 19 00:00:00 EDT 2008,430922,38.82553,-121.254698 9516 LAGUNA LAKE WAY,ELK GROVE,95758,CA,4,2,2002,Residential,Mon May 19 00:00:00 EDT 2008,445000,38.411258,-121.431348 5201 BLOSSOM RANCH DR,ELK GROVE,95757,CA,4,4,4303,Residential,Mon May 19 00:00:00 EDT 2008,450000,38.399436,-121.444041 3027 PALMATE WAY,SACRAMENTO,95834,CA,5,3,4246,Residential,Mon May 19 00:00:00 EDT 2008,452000,38.628955,-121.529269 500 WINCHESTER CT,ROSEVILLE,95661,CA,3,2,2274,Residential,Mon May 19 00:00:00 EDT 2008,470000,38.73988,-121.248929 5746 GELSTON WAY,EL DORADO HILLS,95762,CA,4,3,0,Residential,Mon May 19 00:00:00 EDT 2008,471000,38.677015,-121.034083 6935 ELM TREE LN,ORANGEVALE,95662,CA,4,4,3056,Residential,Mon May 19 00:00:00 EDT 2008,475000,38.693041,-121.23294 9605 GOLF COURSE LN,ELK GROVE,95758,CA,3,3,2503,Residential,Mon May 19 00:00:00 EDT 2008,484500,38.409689,-121.446059 719 BAYWOOD CT,EL DORADO HILLS,95762,CA,5,3,0,Residential,Mon May 19 00:00:00 EDT 2008,487500,38.647598,-121.077801 5954 TANUS CIR,ROCKLIN,95677,CA,3,3,0,Residential,Mon May 19 00:00:00 EDT 2008,488750,38.777585,-121.2036 100 CHELSEA CT,FOLSOM,95630,CA,3,2,1905,Residential,Mon May 19 00:00:00 EDT 2008,500000,38.69435,-121.177259 1500 ORANGE HILL LN,PENRYN,95663,CA,3,2,1320,Residential,Mon May 19 00:00:00 EDT 2008,506688,38.862708,-121.162092 408 KIRKWOOD CT,LINCOLN,95648,CA,2,2,0,Residential,Mon May 19 00:00:00 EDT 2008,512000,38.861615,-121.26869 1732 TUSCAN GROVE CIR,ROSEVILLE,95747,CA,5,3,0,Residential,Mon May 19 00:00:00 EDT 2008,520000,38.796683,-121.342555 2049 EMPIRE MINE CIR,GOLD RIVER,95670,CA,4,2,3037,Residential,Mon May 19 00:00:00 EDT 2008,528000,38.629299,-121.249021 9360 MAGOS RD,WILTON,95693,CA,5,2,3741,Residential,Mon May 19 00:00:00 EDT 2008,579093,38.416809,-121.240628 104 CATLIN CT,FOLSOM,95630,CA,4,3,2660,Residential,Mon May 19 00:00:00 EDT 2008,636000,38.684459,-121.145935 4734 GIBBONS DR,CARMICHAEL,95608,CA,4,3,3357,Residential,Mon May 19 00:00:00 EDT 2008,668365,38.63558,-121.353639 4629 DORCHESTER LN,GRANITE BAY,95746,CA,5,3,2896,Residential,Mon May 19 00:00:00 EDT 2008,676200,38.723545,-121.216025 2400 COUNTRYSIDE DR,PLACERVILLE,95667,CA,3,2,2025,Residential,Mon May 19 00:00:00 EDT 2008,677048,38.737452,-120.910963 12901 FURLONG DR,WILTON,95693,CA,5,3,3788,Residential,Mon May 19 00:00:00 EDT 2008,691659,38.413535,-121.188211 6222 CALLE MONTALVO CIR,GRANITE BAY,95746,CA,5,3,3670,Residential,Mon May 19 00:00:00 EDT 2008,760000,38.779435,-121.146676 20 CRYSTALWOOD CIR,LINCOLN,95648,CA,0,0,0,Residential,Mon May 19 00:00:00 EDT 2008,4897,38.885327,-121.289412 24 CRYSTALWOOD CIR,LINCOLN,95648,CA,0,0,0,Residential,Mon May 19 00:00:00 EDT 2008,4897,38.885132,-121.289405 28 CRYSTALWOOD CIR,LINCOLN,95648,CA,0,0,0,Residential,Mon May 19 00:00:00 EDT 2008,4897,38.884936,-121.289397 32 CRYSTALWOOD CIR,LINCOLN,95648,CA,0,0,0,Residential,Mon May 19 00:00:00 EDT 2008,4897,38.884741,-121.28939 36 CRYSTALWOOD CIR,LINCOLN,95648,CA,0,0,0,Residential,Mon May 19 00:00:00 EDT 2008,4897,38.884599,-121.289406 40 CRYSTALWOOD CIR,LINCOLN,95648,CA,0,0,0,Residential,Mon May 19 00:00:00 EDT 2008,4897,38.884535,-121.289619 44 CRYSTALWOOD CIR,LINCOLN,95648,CA,0,0,0,Residential,Mon May 19 00:00:00 EDT 2008,4897,38.88459,-121.289835 48 CRYSTALWOOD CIR,LINCOLN,95648,CA,0,0,0,Residential,Mon May 19 00:00:00 EDT 2008,4897,38.884667,-121.289896 52 CRYSTALWOOD CIR,LINCOLN,95648,CA,0,0,0,Residential,Mon May 19 00:00:00 EDT 2008,4897,38.88478,-121.289911 68 CRYSTALWOOD CIR,LINCOLN,95648,CA,0,0,0,Residential,Mon May 19 00:00:00 EDT 2008,4897,38.885236,-121.289928 72 CRYSTALWOOD CIR,LINCOLN,95648,CA,0,0,0,Residential,Mon May 19 00:00:00 EDT 2008,4897,38.88535,-121.289926 76 CRYSTALWOOD CIR,LINCOLN,95648,CA,0,0,0,Residential,Mon May 19 00:00:00 EDT 2008,4897,38.885464,-121.289922 80 CRYSTALWOOD CIR,LINCOLN,95648,CA,0,0,0,Residential,Mon May 19 00:00:00 EDT 2008,4897,38.885578,-121.289919 84 CRYSTALWOOD CIR,LINCOLN,95648,CA,0,0,0,Residential,Mon May 19 00:00:00 EDT 2008,4897,38.885692,-121.289915 88 CRYSTALWOOD CIR,LINCOLN,95648,CA,0,0,0,Residential,Mon May 19 00:00:00 EDT 2008,4897,38.885806,-121.289911 92 CRYSTALWOOD CIR,LINCOLN,95648,CA,0,0,0,Residential,Mon May 19 00:00:00 EDT 2008,4897,38.88592,-121.289908 96 CRYSTALWOOD CIR,LINCOLN,95648,CA,0,0,0,Residential,Mon May 19 00:00:00 EDT 2008,4897,38.886024,-121.289859 100 CRYSTALWOOD CIR,LINCOLN,95648,CA,0,0,0,Residential,Mon May 19 00:00:00 EDT 2008,4897,38.886091,-121.289744 434 1ST ST,LINCOLN,95648,CA,0,0,0,Residential,Mon May 19 00:00:00 EDT 2008,4897,38.88653,-121.289406 3 E ST,LINCOLN,95648,CA,0,0,0,Residential,Mon May 19 00:00:00 EDT 2008,4897,38.884692,-121.290288 11 E ST,LINCOLN,95648,CA,0,0,0,Residential,Mon May 19 00:00:00 EDT 2008,4897,38.884879,-121.290257 19 E ST,LINCOLN,95648,CA,0,0,0,Residential,Mon May 19 00:00:00 EDT 2008,4897,38.885017,-121.290262 27 E ST,LINCOLN,95648,CA,0,0,0,Residential,Mon May 19 00:00:00 EDT 2008,4897,38.885173,-121.29027 35 E ST,LINCOLN,95648,CA,0,0,0,Residential,Mon May 19 00:00:00 EDT 2008,4897,38.885328,-121.290275 43 E ST,LINCOLN,95648,CA,0,0,0,Residential,Mon May 19 00:00:00 EDT 2008,4897,38.885483,-121.290277 51 E ST,LINCOLN,95648,CA,4,2,0,Residential,Mon May 19 00:00:00 EDT 2008,4897,38.885638,-121.290279 59 E ST,LINCOLN,95648,CA,3,2,0,Residential,Mon May 19 00:00:00 EDT 2008,4897,38.885794,-121.290281 75 E ST,LINCOLN,95648,CA,3,2,0,Residential,Mon May 19 00:00:00 EDT 2008,4897,38.886104,-121.290285 63 CRYSTALWOOD CIR,LINCOLN,95648,CA,0,0,0,Residential,Mon May 19 00:00:00 EDT 2008,4897,38.885093,-121.289932 398 1ST ST,LINCOLN,95648,CA,0,0,0,Residential,Mon May 19 00:00:00 EDT 2008,4897,38.88653,-121.288952 386 1ST ST,LINCOLN,95648,CA,0,0,0,Residential,Mon May 19 00:00:00 EDT 2008,4897,38.886528,-121.288869 374 1ST ST,LINCOLN,95648,CA,0,0,0,Residential,Mon May 19 00:00:00 EDT 2008,4897,38.886525,-121.288787 116 CRYSTALWOOD WAY,LINCOLN,95648,CA,0,0,0,Residential,Mon May 19 00:00:00 EDT 2008,4897,38.886282,-121.289586 108 CRYSTALWOOD WAY,LINCOLN,95648,CA,0,0,0,Residential,Mon May 19 00:00:00 EDT 2008,4897,38.886282,-121.289646 100 CRYSTALWOOD WAY,LINCOLN,95648,CA,0,0,0,Residential,Mon May 19 00:00:00 EDT 2008,4897,38.886282,-121.289706 55 CRYSTALWOOD CIR,LINCOLN,95648,CA,0,0,0,Residential,Mon May 19 00:00:00 EDT 2008,4897,38.884865,-121.289922 51 CRYSTALWOOD CIR,LINCOLN,95648,CA,0,0,0,Residential,Mon May 19 00:00:00 EDT 2008,4897,38.884752,-121.289907 47 CRYSTALWOOD CIR,LINCOLN,95648,CA,0,0,0,Residential,Mon May 19 00:00:00 EDT 2008,4897,38.884638,-121.289893 43 CRYSTALWOOD CIR,LINCOLN,95648,CA,0,0,0,Residential,Mon May 19 00:00:00 EDT 2008,4897,38.884568,-121.289784 39 CRYSTALWOOD CIR,LINCOLN,95648,CA,0,0,0,Residential,Mon May 19 00:00:00 EDT 2008,4897,38.884546,-121.289562 35 CRYSTALWOOD CIR,LINCOLN,95648,CA,0,0,0,Residential,Mon May 19 00:00:00 EDT 2008,4897,38.884645,-121.289397 31 CRYSTALWOOD CIR,LINCOLN,95648,CA,0,0,0,Residential,Mon May 19 00:00:00 EDT 2008,4897,38.88479,-121.289392 27 CRYSTALWOOD CIR,LINCOLN,95648,CA,0,0,0,Residential,Mon May 19 00:00:00 EDT 2008,4897,38.884985,-121.289399 23 CRYSTALWOOD CIR,LINCOLN,95648,CA,0,0,0,Residential,Mon May 19 00:00:00 EDT 2008,4897,38.885181,-121.289406 19 CRYSTALWOOD CIR,LINCOLN,95648,CA,0,0,0,Residential,Mon May 19 00:00:00 EDT 2008,4897,38.885376,-121.289414 15 CRYSTALWOOD CIR,LINCOLN,95648,CA,0,0,0,Residential,Mon May 19 00:00:00 EDT 2008,4897,38.885571,-121.289421 7 CRYSTALWOOD CIR,LINCOLN,95648,CA,0,0,0,Residential,Mon May 19 00:00:00 EDT 2008,4897,38.885962,-121.289436 7 CRYSTALWOOD CIR,LINCOLN,95648,CA,0,0,0,Residential,Mon May 19 00:00:00 EDT 2008,4897,38.885962,-121.289436 3 CRYSTALWOOD CIR,LINCOLN,95648,CA,0,0,0,Residential,Mon May 19 00:00:00 EDT 2008,4897,38.886093,-121.289584 8208 WOODYARD WAY,CITRUS HEIGHTS,95621,CA,3,2,1166,Residential,Fri May 16 00:00:00 EDT 2008,30000,38.715322,-121.314787 113 RINETTI WAY,RIO LINDA,95673,CA,0,0,0,Residential,Fri May 16 00:00:00 EDT 2008,30000,38.687172,-121.463933 15 LOORZ CT,SACRAMENTO,95823,CA,2,1,838,Residential,Fri May 16 00:00:00 EDT 2008,55422,38.471646,-121.435158 5805 DOTMAR WAY,NORTH HIGHLANDS,95660,CA,2,1,904,Residential,Fri May 16 00:00:00 EDT 2008,63000,38.672642,-121.380343 2332 CAMBRIDGE ST,SACRAMENTO,95815,CA,2,1,1032,Residential,Fri May 16 00:00:00 EDT 2008,65000,38.608085,-121.449651 3812 BELDEN ST,SACRAMENTO,95838,CA,2,1,904,Residential,Fri May 16 00:00:00 EDT 2008,65000,38.636833,-121.44164 3348 40TH ST,SACRAMENTO,95817,CA,2,1,1080,Residential,Fri May 16 00:00:00 EDT 2008,65000,38.544162,-121.460652 127 QUASAR CIR,SACRAMENTO,95822,CA,2,2,990,Residential,Fri May 16 00:00:00 EDT 2008,66500,38.493504,-121.475304 3812 CYPRESS ST,SACRAMENTO,95838,CA,2,1,900,Residential,Fri May 16 00:00:00 EDT 2008,71000,38.636877,-121.444948 5821 64TH ST,SACRAMENTO,95824,CA,2,1,861,Residential,Fri May 16 00:00:00 EDT 2008,75000,38.521202,-121.428146 8248 CENTER PKWY,SACRAMENTO,95823,CA,2,1,906,Condo,Fri May 16 00:00:00 EDT 2008,77000,38.459002,-121.428794 1171 SONOMA AVE,SACRAMENTO,95815,CA,2,1,1011,Residential,Fri May 16 00:00:00 EDT 2008,85000,38.6238,-121.439872 4250 ARDWELL WAY,SACRAMENTO,95823,CA,3,2,1089,Residential,Fri May 16 00:00:00 EDT 2008,95625,38.466938,-121.455631 3104 CLAY ST,SACRAMENTO,95815,CA,2,1,832,Residential,Fri May 16 00:00:00 EDT 2008,96140,38.62391,-121.439208 6063 LAND PARK DR,SACRAMENTO,95822,CA,2,1,800,Condo,Fri May 16 00:00:00 EDT 2008,104250,38.517029,-121.513809 4738 OAKHOLLOW DR,SACRAMENTO,95842,CA,4,2,1292,Residential,Fri May 16 00:00:00 EDT 2008,105000,38.679598,-121.356035 1401 STERLING ST,SACRAMENTO,95822,CA,2,1,810,Residential,Fri May 16 00:00:00 EDT 2008,108000,38.520319,-121.504727 3715 DIDCOT CIR,SACRAMENTO,95838,CA,4,2,1064,Residential,Fri May 16 00:00:00 EDT 2008,109000,38.635232,-121.460098 2426 RASHAWN DR,RANCHO CORDOVA,95670,CA,2,1,911,Residential,Fri May 16 00:00:00 EDT 2008,115000,38.610852,-121.273278 4800 WESTLAKE PKWY Unit 410,SACRAMENTO,95835,CA,1,1,846,Condo,Fri May 16 00:00:00 EDT 2008,115000,38.658812,-121.542345 3409 VIRGO ST,SACRAMENTO,95827,CA,3,2,1320,Residential,Fri May 16 00:00:00 EDT 2008,115500,38.563402,-121.327747 1110 PINEDALE AVE,SACRAMENTO,95838,CA,3,2,1410,Residential,Fri May 16 00:00:00 EDT 2008,115620,38.660173,-121.440216 2361 LA LOMA DR,RANCHO CORDOVA,95670,CA,3,2,1115,Residential,Fri May 16 00:00:00 EDT 2008,116000,38.59368,-121.316054 1455 64TH AVE,SACRAMENTO,95822,CA,3,2,1169,Residential,Fri May 16 00:00:00 EDT 2008,122000,38.492177,-121.503392 7328 SPRINGMAN ST,SACRAMENTO,95822,CA,3,2,1164,Residential,Fri May 16 00:00:00 EDT 2008,122500,38.491991,-121.477636 119 SAINT MARIE CIR,SACRAMENTO,95823,CA,4,2,1341,Residential,Fri May 16 00:00:00 EDT 2008,123000,38.481454,-121.446644 12 COSTA BRASE CT,SACRAMENTO,95838,CA,3,2,1219,Residential,Fri May 16 00:00:00 EDT 2008,124000,38.655554,-121.464275 6813 SCOTER WAY,SACRAMENTO,95842,CA,4,2,1127,Residential,Fri May 16 00:00:00 EDT 2008,124000,38.69043,-121.361035 6548 GRAYLOCK LN,NORTH HIGHLANDS,95660,CA,3,2,1272,Residential,Fri May 16 00:00:00 EDT 2008,124413,38.686061,-121.369949 1630 GLIDDEN AVE,SACRAMENTO,95822,CA,4,2,1253,Residential,Fri May 16 00:00:00 EDT 2008,125000,38.482717,-121.499683 7825 DALEWOODS WAY,SACRAMENTO,95828,CA,3,2,1120,Residential,Fri May 16 00:00:00 EDT 2008,130000,38.477297,-121.411513 4073 TRESLER AVE,NORTH HIGHLANDS,95660,CA,2,2,1118,Residential,Fri May 16 00:00:00 EDT 2008,131750,38.659016,-121.370457 4288 DYMIC WAY,SACRAMENTO,95838,CA,4,3,1890,Residential,Fri May 16 00:00:00 EDT 2008,137721,38.646541,-121.441139 1158 SAN IGNACIO WAY,SACRAMENTO,95833,CA,3,2,1260,Residential,Fri May 16 00:00:00 EDT 2008,137760,38.623045,-121.486279 4904 J PKWY,SACRAMENTO,95823,CA,3,2,1400,Residential,Fri May 16 00:00:00 EDT 2008,138000,38.487297,-121.44295 2931 HOWE AVE,SACRAMENTO,95821,CA,3,1,1264,Residential,Fri May 16 00:00:00 EDT 2008,140000,38.619012,-121.415329 5531 JANSEN DR,SACRAMENTO,95824,CA,3,1,1060,Residential,Fri May 16 00:00:00 EDT 2008,145000,38.522015,-121.438713 7836 ORCHARD WOODS CIR,SACRAMENTO,95828,CA,2,2,1132,Residential,Fri May 16 00:00:00 EDT 2008,145000,38.47955,-121.410867 4055 DEERBROOK DR,SACRAMENTO,95823,CA,3,2,1466,Residential,Fri May 16 00:00:00 EDT 2008,150000,38.472117,-121.459589 9937 BURLINE ST,SACRAMENTO,95827,CA,3,2,1092,Residential,Fri May 16 00:00:00 EDT 2008,150000,38.559641,-121.32316 6948 MIRADOR WAY,SACRAMENTO,95828,CA,4,2,1628,Residential,Fri May 16 00:00:00 EDT 2008,151000,38.493484,-121.42035 4909 RUGER CT,SACRAMENTO,95842,CA,3,2,960,Residential,Fri May 16 00:00:00 EDT 2008,155000,38.68747,-121.349234 7204 KERSTEN ST,CITRUS HEIGHTS,95621,CA,3,2,1075,Residential,Fri May 16 00:00:00 EDT 2008,155800,38.695863,-121.300814 3150 ROSEMONT DR,SACRAMENTO,95826,CA,3,2,1428,Residential,Fri May 16 00:00:00 EDT 2008,156142,38.554927,-121.35521 8200 STEINBECK WAY,SACRAMENTO,95828,CA,4,2,1358,Residential,Fri May 16 00:00:00 EDT 2008,158000,38.474854,-121.404726 8198 STEVENSON AVE,SACRAMENTO,95828,CA,6,4,2475,Multi-Family,Fri May 16 00:00:00 EDT 2008,159900,38.465271,-121.40426 6824 OLIVE TREE WAY,CITRUS HEIGHTS,95610,CA,3,2,1410,Residential,Fri May 16 00:00:00 EDT 2008,160000,38.689239,-121.267737 3536 SUN MAIDEN WAY,ANTELOPE,95843,CA,3,2,1711,Residential,Fri May 16 00:00:00 EDT 2008,161500,38.70968,-121.382328 4517 OLYMPIAD WAY,SACRAMENTO,95826,CA,4,2,1483,Residential,Fri May 16 00:00:00 EDT 2008,161600,38.536751,-121.359154 925 COBDEN CT,GALT,95632,CA,3,2,1140,Residential,Fri May 16 00:00:00 EDT 2008,162000,38.282047,-121.295812 8225 SCOTTSDALE DR,SACRAMENTO,95828,CA,4,2,1549,Residential,Fri May 16 00:00:00 EDT 2008,165000,38.487864,-121.402476 8758 LEMAS RD,SACRAMENTO,95828,CA,3,2,1410,Residential,Fri May 16 00:00:00 EDT 2008,165000,38.467487,-121.377055 6121 ALPINESPRING WAY,ELK GROVE,95758,CA,3,2,1240,Residential,Fri May 16 00:00:00 EDT 2008,167293,38.434075,-121.432623 5937 YORK GLEN WAY,SACRAMENTO,95842,CA,5,2,1712,Residential,Fri May 16 00:00:00 EDT 2008,168000,38.677003,-121.354454 6417 SUNNYFIELD WAY,SACRAMENTO,95823,CA,4,2,1580,Residential,Fri May 16 00:00:00 EDT 2008,168000,38.449153,-121.428272 4008 GREY LIVERY WAY,ANTELOPE,95843,CA,3,2,1669,Residential,Fri May 16 00:00:00 EDT 2008,168750,38.71846,-121.370862 8920 ROSETTA CIR,SACRAMENTO,95826,CA,3,1,1029,Residential,Fri May 16 00:00:00 EDT 2008,168750,38.544374,-121.370874 8300 LICHEN DR,CITRUS HEIGHTS,95621,CA,3,1,1103,Residential,Fri May 16 00:00:00 EDT 2008,170000,38.71641,-121.306239 8884 AMBERJACK WAY,SACRAMENTO,95828,CA,3,2,2161,Residential,Fri May 16 00:00:00 EDT 2008,170250,38.479343,-121.372553 4480 VALLEY HI DR,SACRAMENTO,95823,CA,3,2,1650,Residential,Fri May 16 00:00:00 EDT 2008,173000,38.466781,-121.450955 2250 FOREBAY RD,POLLOCK PINES,95726,CA,3,1,1320,Residential,Fri May 16 00:00:00 EDT 2008,175000,38.77491,-120.597599 3529 FABERGE WAY,SACRAMENTO,95826,CA,3,2,1200,Residential,Fri May 16 00:00:00 EDT 2008,176095,38.553275,-121.346218 1792 DAWNELLE WAY,SACRAMENTO,95835,CA,3,2,1170,Residential,Fri May 16 00:00:00 EDT 2008,176250,38.68271,-121.501697 7800 TABARE CT,CITRUS HEIGHTS,95621,CA,3,2,1199,Residential,Fri May 16 00:00:00 EDT 2008,178000,38.70799,-121.302979 8531 HERMITAGE WAY,SACRAMENTO,95823,CA,4,2,1695,Residential,Fri May 16 00:00:00 EDT 2008,179000,38.448452,-121.428536 2421 BERRYWOOD DR,RANCHO CORDOVA,95670,CA,3,2,1157,Residential,Fri May 16 00:00:00 EDT 2008,180000,38.60868,-121.27849 1005 MORENO WAY,SACRAMENTO,95838,CA,3,2,1410,Residential,Fri May 16 00:00:00 EDT 2008,180000,38.646206,-121.442767 1675 VERNON ST Unit 24,ROSEVILLE,95678,CA,3,2,1174,Residential,Fri May 16 00:00:00 EDT 2008,180000,38.734136,-121.299639 24 WINDCHIME CT,SACRAMENTO,95823,CA,3,2,1593,Residential,Fri May 16 00:00:00 EDT 2008,181000,38.44617,-121.427824 540 HARLING CT,RIO LINDA,95673,CA,3,2,1093,Residential,Fri May 16 00:00:00 EDT 2008,182000,38.68279,-121.453509 1207 CRESCENDO DR,ROSEVILLE,95678,CA,3,2,1770,Residential,Fri May 16 00:00:00 EDT 2008,182587,38.72446,-121.292829 7577 EDDYLEE WAY,SACRAMENTO,95822,CA,4,2,1436,Residential,Fri May 16 00:00:00 EDT 2008,185074,38.48291,-121.491509 8369 FOPPIANO WAY,SACRAMENTO,95829,CA,3,2,1124,Residential,Fri May 16 00:00:00 EDT 2008,185833,38.453839,-121.357919 8817 SAWTELLE WAY,SACRAMENTO,95826,CA,4,2,1139,Residential,Fri May 16 00:00:00 EDT 2008,186785,38.565322,-121.374251 1910 BONAVISTA WAY,SACRAMENTO,95832,CA,3,2,1638,Residential,Fri May 16 00:00:00 EDT 2008,187000,38.476048,-121.494961 8 TIDE CT,SACRAMENTO,95833,CA,3,2,1328,Residential,Fri May 16 00:00:00 EDT 2008,188335,38.609864,-121.492304 8952 ROCKY CREEK CT,ELK GROVE,95758,CA,3,2,1273,Residential,Fri May 16 00:00:00 EDT 2008,190000,38.431239,-121.44001 435 EXCHANGE ST,SACRAMENTO,95838,CA,3,1,1082,Residential,Fri May 16 00:00:00 EDT 2008,190000,38.659434,-121.455236 10105 MONTE VALLO CT,SACRAMENTO,95827,CA,4,2,1578,Residential,Fri May 16 00:00:00 EDT 2008,190000,38.573917,-121.316916 3930 ANNABELLE AVE,ROSEVILLE,95661,CA,2,1,796,Residential,Fri May 16 00:00:00 EDT 2008,190000,38.727609,-121.226494 4854 TANGERINE AVE,SACRAMENTO,95823,CA,3,2,1386,Residential,Fri May 16 00:00:00 EDT 2008,191250,38.478239,-121.446326 2909 SHAWN WAY,RANCHO CORDOVA,95670,CA,3,2,1452,Residential,Fri May 16 00:00:00 EDT 2008,193000,38.589925,-121.299059 4290 BLACKFORD WAY,SACRAMENTO,95823,CA,3,2,1513,Residential,Fri May 16 00:00:00 EDT 2008,193500,38.470494,-121.454162 5890 TT TRAK,FORESTHILL,95631,CA,0,0,0,Residential,Fri May 16 00:00:00 EDT 2008,194818,39.020808,-120.821518 7015 WOODSIDE DR,SACRAMENTO,95842,CA,4,2,1578,Residential,Fri May 16 00:00:00 EDT 2008,195000,38.693071,-121.332365 6019 CHESHIRE WAY,CITRUS HEIGHTS,95610,CA,4,3,1736,Residential,Fri May 16 00:00:00 EDT 2008,195000,38.676437,-121.279165 3330 VILLAGE CT,CAMERON PARK,95682,CA,2,2,0,Residential,Fri May 16 00:00:00 EDT 2008,195000,38.690504,-120.996245 2561 VERNA WAY,SACRAMENTO,95821,CA,3,1,1473,Residential,Fri May 16 00:00:00 EDT 2008,195000,38.611055,-121.369964 3522 22ND AVE,SACRAMENTO,95820,CA,3,1,1150,Residential,Fri May 16 00:00:00 EDT 2008,198000,38.532725,-121.469078 2880 CANDIDO DR,SACRAMENTO,95833,CA,3,2,1127,Residential,Fri May 16 00:00:00 EDT 2008,199900,38.618019,-121.510215 6908 PIN OAK CT,FAIR OAKS,95628,CA,3,1,1144,Residential,Fri May 16 00:00:00 EDT 2008,200000,38.66424,-121.303675 5733 ANGELINA AVE,CARMICHAEL,95608,CA,3,1,972,Residential,Fri May 16 00:00:00 EDT 2008,201000,38.622634,-121.330846 7849 BONNY DOWNS WAY,ELK GROVE,95758,CA,4,2,2306,Residential,Fri May 16 00:00:00 EDT 2008,204918,38.42139,-121.411339 8716 LONGSPUR WAY,ANTELOPE,95843,CA,3,2,1479,Residential,Fri May 16 00:00:00 EDT 2008,205000,38.724083,-121.3584 6320 EL DORADO ST,EL DORADO,95623,CA,2,1,1040,Residential,Fri May 16 00:00:00 EDT 2008,205000,38.678758,-120.844118 2328 DOROTHY JUNE WAY,SACRAMENTO,95838,CA,3,2,1430,Residential,Fri May 16 00:00:00 EDT 2008,205878,38.641727,-121.412703 1986 DANVERS WAY,SACRAMENTO,95832,CA,4,2,1800,Residential,Fri May 16 00:00:00 EDT 2008,207000,38.47723,-121.492568 7901 GAZELLE TRAIL WAY,ANTELOPE,95843,CA,4,2,1953,Residential,Fri May 16 00:00:00 EDT 2008,207744,38.71174,-121.342675 6080 BRIDGECROSS DR,SACRAMENTO,95835,CA,3,2,1120,Residential,Fri May 16 00:00:00 EDT 2008,209000,38.681952,-121.505009 20 GROTH CIR,SACRAMENTO,95834,CA,3,2,1232,Residential,Fri May 16 00:00:00 EDT 2008,210000,38.640807,-121.533522 1900 DANBROOK DR,SACRAMENTO,95835,CA,1,1,984,Condo,Fri May 16 00:00:00 EDT 2008,210944,38.668433,-121.503471 140 VENTO CT,ROSEVILLE,95678,CA,3,2,0,Condo,Fri May 16 00:00:00 EDT 2008,212500,38.793533,-121.289685 8442 KEUSMAN ST,ELK GROVE,95758,CA,4,2,2329,Residential,Fri May 16 00:00:00 EDT 2008,213750,38.449651,-121.414704 9552 SUNLIGHT LN,ELK GROVE,95758,CA,3,2,1351,Residential,Fri May 16 00:00:00 EDT 2008,215000,38.410561,-121.404327 2733 YUMA CT,CAMERON PARK,95682,CA,2,2,0,Residential,Fri May 16 00:00:00 EDT 2008,215000,38.691215,-120.994949 1407 TIFFANY CIR,ROSEVILLE,95661,CA,4,1,1376,Residential,Fri May 16 00:00:00 EDT 2008,215000,38.736392,-121.2664 636 CRESTVIEW DR,DIAMOND SPRINGS,95619,CA,3,2,1300,Residential,Fri May 16 00:00:00 EDT 2008,216033,38.688255,-120.810235 1528 HESKET WAY,SACRAMENTO,95825,CA,4,2,1566,Residential,Fri May 16 00:00:00 EDT 2008,220000,38.593598,-121.403637 2327 32ND ST,SACRAMENTO,95817,CA,2,1,1115,Residential,Fri May 16 00:00:00 EDT 2008,220000,38.557433,-121.47034 1833 2ND AVE,SACRAMENTO,95818,CA,2,1,1032,Residential,Fri May 16 00:00:00 EDT 2008,220000,38.556818,-121.490669 7252 CARRIAGE DR,CITRUS HEIGHTS,95621,CA,4,2,1419,Residential,Fri May 16 00:00:00 EDT 2008,220000,38.698058,-121.294893 9815 PASO FINO WAY,ELK GROVE,95757,CA,3,2,1261,Residential,Fri May 16 00:00:00 EDT 2008,220000,38.404888,-121.443998 5532 ENGLE RD,CARMICHAEL,95608,CA,2,2,1637,Residential,Fri May 16 00:00:00 EDT 2008,220702,38.63173,-121.335286 1139 CLINTON RD,SACRAMENTO,95825,CA,4,2,1776,Multi-Family,Fri May 16 00:00:00 EDT 2008,221250,38.585291,-121.406824 9176 SAGE GLEN WAY,ELK GROVE,95758,CA,3,2,1338,Residential,Fri May 16 00:00:00 EDT 2008,222000,38.423913,-121.439115 9967 HATHERTON WAY,ELK GROVE,95757,CA,0,0,0,Residential,Fri May 16 00:00:00 EDT 2008,222500,38.3052,-121.4033 9264 BOULDER RIVER WAY,ELK GROVE,95624,CA,5,2,2254,Residential,Fri May 16 00:00:00 EDT 2008,222750,38.421713,-121.345191 320 GROTH CIR,SACRAMENTO,95834,CA,3,2,1441,Residential,Fri May 16 00:00:00 EDT 2008,225000,38.638882,-121.531883 137 GUNNISON AVE,SACRAMENTO,95838,CA,4,2,1991,Residential,Fri May 16 00:00:00 EDT 2008,225000,38.650729,-121.466483 8209 RIVALLO WAY,SACRAMENTO,95829,CA,4,3,2126,Residential,Fri May 16 00:00:00 EDT 2008,228750,38.459524,-121.3501 8637 PERIWINKLE CIR,ELK GROVE,95624,CA,3,2,1094,Residential,Fri May 16 00:00:00 EDT 2008,229000,38.443184,-121.364388 3425 MEADOW WAY,ROCKLIN,95677,CA,3,2,1462,Residential,Fri May 16 00:00:00 EDT 2008,230095,38.798028,-121.235364 107 JARVIS CIR,SACRAMENTO,95834,CA,5,3,2258,Residential,Fri May 16 00:00:00 EDT 2008,232500,38.639891,-121.537603 2319 THORES ST,RANCHO CORDOVA,95670,CA,3,2,1074,Residential,Fri May 16 00:00:00 EDT 2008,233000,38.59675,-121.312716 8935 MOUNTAIN HOME CT,ELK GROVE,95624,CA,4,2,2111,Residential,Fri May 16 00:00:00 EDT 2008,233500,38.38751,-121.370276 2566 SERENATA WAY,SACRAMENTO,95835,CA,3,2,1686,Residential,Fri May 16 00:00:00 EDT 2008,239000,38.671556,-121.520916 4085 COUNTRY DR,ANTELOPE,95843,CA,4,3,1915,Residential,Fri May 16 00:00:00 EDT 2008,240000,38.706209,-121.369509 9297 TROUT WAY,ELK GROVE,95624,CA,4,2,2367,Residential,Fri May 16 00:00:00 EDT 2008,240000,38.420637,-121.375798 7 ARCHIBALD CT,SACRAMENTO,95823,CA,3,2,1962,Residential,Fri May 16 00:00:00 EDT 2008,240971,38.443305,-121.435296 11130 EEL RIVER CT,RANCHO CORDOVA,95670,CA,2,2,1406,Residential,Fri May 16 00:00:00 EDT 2008,242000,38.625932,-121.271517 8323 REDBANK WAY,SACRAMENTO,95829,CA,3,2,1789,Residential,Fri May 16 00:00:00 EDT 2008,243450,38.455753,-121.349273 16 BRONCO CREEK CT,SACRAMENTO,95835,CA,4,2,1876,Residential,Fri May 16 00:00:00 EDT 2008,243500,38.674226,-121.525497 8316 NORTHAM DR,ANTELOPE,95843,CA,3,2,1235,Residential,Fri May 16 00:00:00 EDT 2008,246544,38.720767,-121.376678 4240 WINJE DR,ANTELOPE,95843,CA,4,2,2504,Residential,Fri May 16 00:00:00 EDT 2008,246750,38.70884,-121.359559 3569 SODA WAY,SACRAMENTO,95834,CA,0,0,0,Residential,Fri May 16 00:00:00 EDT 2008,247000,38.631139,-121.501879 5118 ROBANDER ST,CARMICHAEL,95608,CA,3,2,1676,Residential,Fri May 16 00:00:00 EDT 2008,247000,38.657267,-121.310352 5976 KYLENCH CT,CITRUS HEIGHTS,95621,CA,3,2,1367,Residential,Fri May 16 00:00:00 EDT 2008,249000,38.708966,-121.32467 9247 DELAIR WAY,ELK GROVE,95758,CA,4,3,1899,Residential,Fri May 16 00:00:00 EDT 2008,249000,38.422241,-121.458022 9054 DESCENDANT DR,ELK GROVE,95758,CA,3,2,1636,Residential,Fri May 16 00:00:00 EDT 2008,250000,38.428852,-121.415628 3450 WHITNOR CT,SACRAMENTO,95821,CA,3,2,1828,Residential,Fri May 16 00:00:00 EDT 2008,250000,38.627698,-121.369698 6288 LONETREE BLVD,ROCKLIN,95765,CA,0,0,0,Residential,Fri May 16 00:00:00 EDT 2008,250000,38.804993,-121.293609 9355 MATADOR WAY,SACRAMENTO,95826,CA,4,2,1438,Residential,Fri May 16 00:00:00 EDT 2008,252000,38.555633,-121.350691 8671 SUMMER SUN WAY,ELK GROVE,95624,CA,3,2,1451,Residential,Fri May 16 00:00:00 EDT 2008,255000,38.442845,-121.373272 1890 GENEVA PL,SACRAMENTO,95825,CA,3,1,1520,Residential,Fri May 16 00:00:00 EDT 2008,255000,38.599449,-121.400305 1813 AVENIDA MARTINA,ROSEVILLE,95747,CA,3,2,1506,Residential,Fri May 16 00:00:00 EDT 2008,255000,38.776649,-121.339589 191 BARNHART CIR,SACRAMENTO,95835,CA,4,2,2605,Residential,Fri May 16 00:00:00 EDT 2008,257200,38.675594,-121.515878 6221 GREEN TOP WAY,ORANGEVALE,95662,CA,3,2,1196,Residential,Fri May 16 00:00:00 EDT 2008,260000,38.679409,-121.219107 2298 PRIMROSE LN,LINCOLN,95648,CA,3,2,1621,Residential,Fri May 16 00:00:00 EDT 2008,260000,38.89918,-121.322514 5635 LOS PUEBLOS WAY,SACRAMENTO,95835,CA,3,2,1811,Residential,Fri May 16 00:00:00 EDT 2008,263500,38.679191,-121.537622 10165 LOFTON WAY,ELK GROVE,95757,CA,3,2,1540,Residential,Fri May 16 00:00:00 EDT 2008,266510,38.387708,-121.436522 1251 GREEN RAVINE DR,LINCOLN,95648,CA,4,2,0,Residential,Fri May 16 00:00:00 EDT 2008,267750,38.88156,-121.301343 6001 SHOO FLY RD,PLACERVILLE,95667,CA,0,0,0,Residential,Fri May 16 00:00:00 EDT 2008,270000,38.813546,-120.809254 3040 PARKHAM DR,ROSEVILLE,95747,CA,0,0,0,Residential,Fri May 16 00:00:00 EDT 2008,271000,38.770835,-121.366996 2674 TAM O SHANTER DR,EL DORADO HILLS,95762,CA,4,2,0,Residential,Fri May 16 00:00:00 EDT 2008,272700,38.695801,-121.079216 6007 MARYBELLE LN,SHINGLE SPRINGS,95682,CA,0,0,0,Unkown,Fri May 16 00:00:00 EDT 2008,275000,38.64347,-120.888183 9949 NESTLING CIR,ELK GROVE,95757,CA,3,2,1543,Residential,Fri May 16 00:00:00 EDT 2008,275000,38.397455,-121.468391 2915 HOLDREGE WAY,SACRAMENTO,95835,CA,5,3,2494,Residential,Fri May 16 00:00:00 EDT 2008,276000,38.663728,-121.525833 2678 BRIARTON DR,LINCOLN,95648,CA,3,2,1650,Residential,Fri May 16 00:00:00 EDT 2008,276500,38.844116,-121.274806 294 SPARROW DR,GALT,95632,CA,4,3,2214,Residential,Fri May 16 00:00:00 EDT 2008,278000,38.258976,-121.321266 2987 DIORITE WAY,SACRAMENTO,95835,CA,5,3,2280,Residential,Fri May 16 00:00:00 EDT 2008,279000,38.667332,-121.528276 6326 APPIAN WAY,CARMICHAEL,95608,CA,3,2,1443,Residential,Fri May 16 00:00:00 EDT 2008,280000,38.66266,-121.316858 6905 COBALT WAY,CITRUS HEIGHTS,95621,CA,4,2,1582,Residential,Fri May 16 00:00:00 EDT 2008,280000,38.691393,-121.305215 8986 HAFLINGER WAY,ELK GROVE,95757,CA,3,2,1857,Residential,Fri May 16 00:00:00 EDT 2008,285000,38.397923,-121.450219 2916 BABSON DR,ELK GROVE,95758,CA,3,2,1735,Residential,Fri May 16 00:00:00 EDT 2008,288000,38.417191,-121.473897 10133 NEBBIOLO CT,ELK GROVE,95624,CA,4,3,2096,Residential,Fri May 16 00:00:00 EDT 2008,289000,38.391085,-121.347231 1103 COMMONS DR,SACRAMENTO,95825,CA,3,2,1720,Residential,Fri May 16 00:00:00 EDT 2008,290000,38.567865,-121.410699 4636 TEAL BAY CT,ANTELOPE,95843,CA,4,2,2160,Residential,Fri May 16 00:00:00 EDT 2008,290000,38.704554,-121.354753 1524 YOUNGS AVE,SACRAMENTO,95838,CA,4,2,1382,Residential,Fri May 16 00:00:00 EDT 2008,293996,38.644927,-121.43054 865 CONRAD CT,PLACERVILLE,95667,CA,3,2,0,Residential,Fri May 16 00:00:00 EDT 2008,294000,38.729993,-120.802458 8463 TERRACOTTA CT,ELK GROVE,95624,CA,4,2,1721,Residential,Fri May 16 00:00:00 EDT 2008,294173,38.450548,-121.363002 5747 KING RD,LOOMIS,95650,CA,4,2,1328,Residential,Fri May 16 00:00:00 EDT 2008,295000,38.825096,-121.198432 8253 KEEGAN WAY,ELK GROVE,95624,CA,0,0,0,Residential,Fri May 16 00:00:00 EDT 2008,298000,38.446286,-121.400817 9204 TROUT WAY,ELK GROVE,95624,CA,4,2,1982,Residential,Fri May 16 00:00:00 EDT 2008,298000,38.422221,-121.375799 1828 2ND AVE,SACRAMENTO,95818,CA,2,1,1144,Residential,Fri May 16 00:00:00 EDT 2008,299000,38.556844,-121.490769 1113 COMMONS DR,SACRAMENTO,95825,CA,2,2,1623,Residential,Fri May 16 00:00:00 EDT 2008,300000,38.567795,-121.410703 2341 BIG STRIKE TRL,COOL,95614,CA,3,2,1457,Residential,Fri May 16 00:00:00 EDT 2008,300000,38.905927,-120.975169 9452 RED SPRUCE WAY,ELK GROVE,95624,CA,6,3,2555,Residential,Fri May 16 00:00:00 EDT 2008,300000,38.404505,-121.346938 5776 TERRACE DR,ROCKLIN,95765,CA,3,2,1577,Residential,Fri May 16 00:00:00 EDT 2008,300567,38.800539,-121.260979 5908 MCLEAN DR,ELK GROVE,95757,CA,5,3,2592,Residential,Fri May 16 00:00:00 EDT 2008,303000,38.38912,-121.434389 8215 PEREGRINE WAY,CITRUS HEIGHTS,95610,CA,3,2,1401,Residential,Fri May 16 00:00:00 EDT 2008,305000,38.715493,-121.26293 1104 HILLSDALE LN,LINCOLN,95648,CA,4,2,0,Residential,Fri May 16 00:00:00 EDT 2008,306000,38.865017,-121.32302 2949 PANAMA AVE,CARMICHAEL,95608,CA,3,2,1502,Residential,Fri May 16 00:00:00 EDT 2008,310000,38.618369,-121.326187 1356 HARTLEY WAY,FOLSOM,95630,CA,3,2,1327,Residential,Fri May 16 00:00:00 EDT 2008,310000,38.651617,-121.131674 633 HANISCH DR,ROSEVILLE,95678,CA,4,3,1800,Residential,Fri May 16 00:00:00 EDT 2008,310000,38.76349,-121.275881 63 ANGEL ISLAND CIR,SACRAMENTO,95831,CA,4,2,2169,Residential,Fri May 16 00:00:00 EDT 2008,311518,38.490408,-121.547664 1571 WILD OAK LN,LINCOLN,95648,CA,5,3,2457,Residential,Fri May 16 00:00:00 EDT 2008,312000,38.844144,-121.274174 5222 COPPER SUNSET WAY,RANCHO CORDOVA,95742,CA,0,0,0,Residential,Fri May 16 00:00:00 EDT 2008,313000,38.529181,-121.224755 5601 SPINDRIFT LN,ORANGEVALE,95662,CA,4,2,2004,Residential,Fri May 16 00:00:00 EDT 2008,315000,38.668289,-121.192316 652 FIFTEEN MILE DR,ROSEVILLE,95678,CA,4,3,2212,Residential,Fri May 16 00:00:00 EDT 2008,315000,38.775872,-121.298864 7921 DOE TRAIL WAY,ANTELOPE,95843,CA,5,3,3134,Residential,Fri May 16 00:00:00 EDT 2008,315000,38.711927,-121.343608 4204 LUSK DR,SACRAMENTO,95864,CA,3,2,1360,Residential,Fri May 16 00:00:00 EDT 2008,315000,38.606569,-121.368424 5321 DELTA DR,ROCKLIN,95765,CA,4,2,0,Residential,Fri May 16 00:00:00 EDT 2008,315000,38.815493,-121.262908 5608 ROSEDALE WAY,SACRAMENTO,95822,CA,3,2,1276,Residential,Fri May 16 00:00:00 EDT 2008,320000,38.525115,-121.518689 3372 BERETANIA WAY,SACRAMENTO,95834,CA,4,3,2962,Residential,Fri May 16 00:00:00 EDT 2008,322000,38.64977,-121.53448 2422 STEFANIE DR,ROCKLIN,95765,CA,4,2,1888,Residential,Fri May 16 00:00:00 EDT 2008,325000,38.82273,-121.26424 3232 PARKHAM DR,ROSEVILLE,95747,CA,0,0,0,Residential,Fri May 16 00:00:00 EDT 2008,325500,38.772821,-121.364821 448 ELMWOOD CT,ROSEVILLE,95678,CA,3,2,0,Residential,Fri May 16 00:00:00 EDT 2008,326951,38.771917,-121.304439 1214 DAWNWOOD DR,GALT,95632,CA,3,2,1548,Residential,Fri May 16 00:00:00 EDT 2008,328370,38.290119,-121.286023 1440 EMERALD LN,LINCOLN,95648,CA,2,2,0,Residential,Fri May 16 00:00:00 EDT 2008,330000,38.861864,-121.267478 3349 CORVINA DR,RANCHO CORDOVA,95670,CA,4,3,2109,Residential,Fri May 16 00:00:00 EDT 2008,330000,38.580545,-121.279016 10254 JULIANA WAY,SACRAMENTO,95827,CA,4,2,2484,Residential,Fri May 16 00:00:00 EDT 2008,331200,38.56803,-121.309966 149 OPUS CIR,SACRAMENTO,95834,CA,4,3,2258,Residential,Fri May 16 00:00:00 EDT 2008,332000,38.6354,-121.53499 580 REGENCY PARK CIR,SACRAMENTO,95835,CA,3,3,2212,Residential,Fri May 16 00:00:00 EDT 2008,334000,38.674864,-121.4958 5544 CAMAS CT,ORANGEVALE,95662,CA,3,2,1616,Residential,Fri May 16 00:00:00 EDT 2008,335000,38.667703,-121.209456 5102 ARCHCREST WAY,SACRAMENTO,95835,CA,4,2,2372,Residential,Fri May 16 00:00:00 EDT 2008,341000,38.66841,-121.494639 5725 BALFOR RD,ROCKLIN,95765,CA,5,3,2606,Residential,Fri May 16 00:00:00 EDT 2008,346375,38.807816,-121.270008 7697 ROSEHALL DR,ROSEVILLE,95678,CA,5,3,0,Residential,Fri May 16 00:00:00 EDT 2008,347225,38.79218,-121.28595 4821 HUTSON WAY,ELK GROVE,95757,CA,5,3,2877,Residential,Fri May 16 00:00:00 EDT 2008,349000,38.386239,-121.448159 4509 WINJE DR,ANTELOPE,95843,CA,3,2,2960,Residential,Fri May 16 00:00:00 EDT 2008,350000,38.709513,-121.359357 1965 LAURELHURST LN,LINCOLN,95648,CA,2,2,0,Residential,Fri May 16 00:00:00 EDT 2008,350000,38.853869,-121.271742 6709 ROSE BRIDGE DR,ROSEVILLE,95678,CA,3,2,2172,Residential,Fri May 16 00:00:00 EDT 2008,350000,38.792461,-121.275711 281 SPYGLASS HL,ROSEVILLE,95678,CA,3,2,2100,Condo,Fri May 16 00:00:00 EDT 2008,350000,38.762153,-121.283451 7709 RIVER VILLAGE DR,SACRAMENTO,95831,CA,3,2,1795,Residential,Fri May 16 00:00:00 EDT 2008,351000,38.483212,-121.54019 4165 BRISBANE CIR,EL DORADO HILLS,95762,CA,3,2,0,Residential,Fri May 16 00:00:00 EDT 2008,356200,38.686067,-121.073413 506 BEDFORD CT,ROSEVILLE,95661,CA,4,2,2295,Residential,Fri May 16 00:00:00 EDT 2008,360000,38.733985,-121.236766 9048 PINTO CANYON WAY,ROSEVILLE,95747,CA,4,3,2577,Residential,Fri May 16 00:00:00 EDT 2008,367463,38.792493,-121.331899 2274 IVY BRIDGE DR,ROSEVILLE,95747,CA,0,0,0,Residential,Fri May 16 00:00:00 EDT 2008,375000,38.778561,-121.362008 14004 WALNUT AVE,WALNUT GROVE,95690,CA,3,1,1727,Residential,Fri May 16 00:00:00 EDT 2008,380000,38.247659,-121.515129 6905 FRANKFORT CT,ELK GROVE,95758,CA,3,2,1485,Residential,Fri May 16 00:00:00 EDT 2008,380578,38.429139,-121.423444 3621 WINTUN DR,CARMICHAEL,95608,CA,3,2,1655,Residential,Fri May 16 00:00:00 EDT 2008,386222,38.629929,-121.323086 201 KIRKLAND CT,LINCOLN,95648,CA,0,0,0,Residential,Fri May 16 00:00:00 EDT 2008,389000,38.867125,-121.319085 12075 APPLESBURY CT,RANCHO CORDOVA,95742,CA,0,0,0,Residential,Fri May 16 00:00:00 EDT 2008,390000,38.5357,-121.2249 1975 SIDESADDLE WAY,ROSEVILLE,95661,CA,3,2,2049,Residential,Fri May 16 00:00:00 EDT 2008,395500,38.737872,-121.249025 5420 ALMOND FALLS WAY,RANCHO CORDOVA,95742,CA,0,0,0,Residential,Fri May 16 00:00:00 EDT 2008,396000,38.527384,-121.233531 9677 PILLITERI CT,ELK GROVE,95757,CA,5,3,2875,Residential,Fri May 16 00:00:00 EDT 2008,397000,38.405571,-121.445186 1515 EL CAMINO VERDE DR,LINCOLN,95648,CA,0,0,0,Residential,Fri May 16 00:00:00 EDT 2008,400000,38.904869,-121.32075 556 PLATT CIR,EL DORADO HILLS,95762,CA,4,2,2199,Residential,Fri May 16 00:00:00 EDT 2008,400000,38.656299,-121.079783 1792 DIAMOND WOODS CIR,ROSEVILLE,95747,CA,4,3,0,Residential,Fri May 16 00:00:00 EDT 2008,412500,38.808581,-121.32785 1124 PERKINS WAY,SACRAMENTO,95818,CA,2,1,1304,Residential,Fri May 16 00:00:00 EDT 2008,413500,38.551611,-121.504437 4748 SALEM WAY,CARMICHAEL,95608,CA,3,2,2334,Residential,Fri May 16 00:00:00 EDT 2008,415000,38.634111,-121.353376 1484 RADCLIFFE WAY,AUBURN,95603,CA,4,3,2278,Residential,Fri May 16 00:00:00 EDT 2008,420454,38.935579,-121.079018 51 AIKEN WAY,SACRAMENTO,95819,CA,3,1,1493,Residential,Fri May 16 00:00:00 EDT 2008,425000,38.579326,-121.44252 2818 KNOLLWOOD DR,CAMERON PARK,95682,CA,3,2,0,Residential,Fri May 16 00:00:00 EDT 2008,425000,38.669805,-120.999007 1536 STONEY CROSS LN,LINCOLN,95648,CA,0,0,0,Residential,Fri May 16 00:00:00 EDT 2008,433500,38.860007,-121.310946 509 CASTILLIAN CT,ROSEVILLE,95747,CA,5,3,0,Residential,Fri May 16 00:00:00 EDT 2008,438000,38.804773,-121.341195 700 HUNTER PL,FOLSOM,95630,CA,5,3,2787,Residential,Fri May 16 00:00:00 EDT 2008,441000,38.66051,-121.163689 1240 FAY CIR,SACRAMENTO,95831,CA,5,3,2824,Residential,Fri May 16 00:00:00 EDT 2008,445000,38.506371,-121.514456 1113 SANDWICK WAY,FOLSOM,95630,CA,4,3,3261,Residential,Fri May 16 00:00:00 EDT 2008,446000,38.673882,-121.105077 3108 DELWOOD WAY,SACRAMENTO,95821,CA,4,2,2053,Residential,Fri May 16 00:00:00 EDT 2008,450000,38.621566,-121.370882 3212 CORNICHE LN,ROSEVILLE,95661,CA,4,3,2379,Residential,Fri May 16 00:00:00 EDT 2008,455000,38.750577,-121.232768 2159 BECKETT DR,EL DORADO HILLS,95762,CA,3,2,0,Residential,Fri May 16 00:00:00 EDT 2008,460000,38.680092,-121.036467 4320 FOUR SEASONS RD,PLACERVILLE,95667,CA,3,2,0,Residential,Fri May 16 00:00:00 EDT 2008,475000,38.690867,-120.693641 6401 MARSHALL RD,GARDEN VALLEY,95633,CA,3,2,0,Residential,Fri May 16 00:00:00 EDT 2008,490000,38.84255,-120.8754 2089 BECKETT DR,EL DORADO HILLS,95762,CA,4,2,0,Residential,Fri May 16 00:00:00 EDT 2008,493000,38.681778,-121.035838 6196 EDGEHILL DR,EL DORADO HILLS,95762,CA,5,4,0,Residential,Fri May 16 00:00:00 EDT 2008,508000,38.676131,-121.038931 200 HILLSFORD CT,ROSEVILLE,95747,CA,0,0,0,Residential,Fri May 16 00:00:00 EDT 2008,511000,38.780051,-121.378718 8217 PLUMERIA AVE,FAIR OAKS,95628,CA,3,2,3173,Residential,Fri May 16 00:00:00 EDT 2008,525000,38.650735,-121.258628 4841 VILLAGE GREEN DR,EL DORADO HILLS,95762,CA,4,3,0,Residential,Fri May 16 00:00:00 EDT 2008,533000,38.664066,-121.056735 3863 LAS PASAS WAY,SACRAMENTO,95864,CA,3,1,1348,Residential,Fri May 16 00:00:00 EDT 2008,545000,38.588936,-121.373606 820 DANA CT,AUBURN,95603,CA,4,3,0,Residential,Fri May 16 00:00:00 EDT 2008,560000,38.865246,-121.094869 1165 37TH ST,SACRAMENTO,95816,CA,2,1,1252,Residential,Fri May 16 00:00:00 EDT 2008,575000,38.568438,-121.457854 203 CASCADE FALLS DR,FOLSOM,95630,CA,4,3,3229,Residential,Fri May 16 00:00:00 EDT 2008,575000,38.703962,-121.1871 9880 IZILDA CT,SACRAMENTO,95829,CA,5,4,3863,Residential,Fri May 16 00:00:00 EDT 2008,598695,38.45326,-121.32573 1800 AVONDALE DR,ROSEVILLE,95747,CA,5,3,0,Residential,Fri May 16 00:00:00 EDT 2008,600000,38.798448,-121.344054 4620 BROMWICH CT,ROCKLIN,95677,CA,4,3,0,Residential,Fri May 16 00:00:00 EDT 2008,600000,38.772672,-121.220232 620 KESWICK CT,GRANITE BAY,95746,CA,4,3,2356,Residential,Fri May 16 00:00:00 EDT 2008,600000,38.732096,-121.219142 4478 GREENBRAE RD,ROCKLIN,95677,CA,0,0,0,Residential,Fri May 16 00:00:00 EDT 2008,600000,38.781134,-121.222801 8432 BRIGGS DR,ROSEVILLE,95747,CA,5,3,3579,Residential,Fri May 16 00:00:00 EDT 2008,610000,38.78861,-121.339495 200 CRADLE MOUNTAIN CT,EL DORADO HILLS,95762,CA,0,0,0,Residential,Fri May 16 00:00:00 EDT 2008,622500,38.6478,-121.0309 2065 IMPRESSIONIST WAY,EL DORADO HILLS,95762,CA,0,0,0,Residential,Fri May 16 00:00:00 EDT 2008,680000,38.682961,-121.033253 2982 ABERDEEN LN,EL DORADO HILLS,95762,CA,4,3,0,Residential,Fri May 16 00:00:00 EDT 2008,879000,38.706692,-121.058869 9401 BARREL RACER CT,WILTON,95693,CA,4,3,4400,Residential,Fri May 16 00:00:00 EDT 2008,884790,38.415298,-121.194858 3720 VISTA DE MADERA,LINCOLN,95648,CA,3,3,0,Residential,Fri May 16 00:00:00 EDT 2008,1551,38.851645,-121.231742 14151 INDIO DR,SLOUGHHOUSE,95683,CA,3,4,5822,Residential,Fri May 16 00:00:00 EDT 2008,2000,38.490447,-121.129337 7401 TOULON LN,SACRAMENTO,95828,CA,4,2,1512,Residential,Thu May 15 00:00:00 EDT 2008,56950,38.488628,-121.387759 9127 NEWHALL DR Unit 34,SACRAMENTO,95826,CA,1,1,611,Condo,Thu May 15 00:00:00 EDT 2008,60000,38.542419,-121.359904 5937 BAMFORD DR,SACRAMENTO,95823,CA,2,1,876,Residential,Thu May 15 00:00:00 EDT 2008,61000,38.471139,-121.432255 5672 HILLSDALE BLVD,SACRAMENTO,95842,CA,2,1,933,Condo,Thu May 15 00:00:00 EDT 2008,62000,38.670467,-121.359799 3920 39TH ST,SACRAMENTO,95820,CA,2,1,864,Residential,Thu May 15 00:00:00 EDT 2008,68566,38.539213,-121.46393 701 JESSIE AVE,SACRAMENTO,95838,CA,2,1,1011,Residential,Thu May 15 00:00:00 EDT 2008,70000,38.643978,-121.449562 83 ARCADE BLVD,SACRAMENTO,95815,CA,4,2,1158,Residential,Thu May 15 00:00:00 EDT 2008,80000,38.618716,-121.466327 601 REGGINALD WAY,SACRAMENTO,95838,CA,3,2,1092,Residential,Thu May 15 00:00:00 EDT 2008,85500,38.64472,-121.452228 550 DEL VERDE CIR,SACRAMENTO,95833,CA,2,1,956,Condo,Thu May 15 00:00:00 EDT 2008,92000,38.627147,-121.500799 4113 DAYSTAR CT,SACRAMENTO,95824,CA,2,2,1139,Residential,Thu May 15 00:00:00 EDT 2008,93600,38.520469,-121.458606 7374 TISDALE WAY,SACRAMENTO,95822,CA,3,1,1058,Residential,Thu May 15 00:00:00 EDT 2008,95000,38.488238,-121.472561 3348 RIO LINDA BLVD,SACRAMENTO,95838,CA,3,2,1040,Residential,Thu May 15 00:00:00 EDT 2008,97750,38.628842,-121.446127 3935 LIMESTONE WAY,SACRAMENTO,95823,CA,3,2,1354,Residential,Thu May 15 00:00:00 EDT 2008,104000,38.484374,-121.463157 6208 GRATTAN WAY,NORTH HIGHLANDS,95660,CA,3,1,1051,Residential,Thu May 15 00:00:00 EDT 2008,105000,38.679279,-121.376615 739 E WOODSIDE LN Unit E,SACRAMENTO,95825,CA,1,1,682,Condo,Thu May 15 00:00:00 EDT 2008,107666,38.578675,-121.409951 4225 46TH AVE,SACRAMENTO,95824,CA,3,1,1161,Residential,Thu May 15 00:00:00 EDT 2008,109000,38.511893,-121.457676 1434 BELL AVE,SACRAMENTO,95838,CA,3,1,1004,Residential,Thu May 15 00:00:00 EDT 2008,110000,38.647398,-121.432914 5628 GEORGIA DR,NORTH HIGHLANDS,95660,CA,3,1,1229,Residential,Thu May 15 00:00:00 EDT 2008,110000,38.669587,-121.379879 7629 BETH ST,SACRAMENTO,95832,CA,3,2,1249,Residential,Thu May 15 00:00:00 EDT 2008,112500,38.480126,-121.487869 2277 BABETTE WAY,SACRAMENTO,95832,CA,3,2,1161,Residential,Thu May 15 00:00:00 EDT 2008,114800,38.479593,-121.48434 6561 WEATHERFORD WAY,SACRAMENTO,95823,CA,3,1,1010,Residential,Thu May 15 00:00:00 EDT 2008,116000,38.465551,-121.42661 3035 ESTEPA DR Unit 5C,CAMERON PARK,95682,CA,0,0,0,Condo,Thu May 15 00:00:00 EDT 2008,119000,38.681393,-120.996713 5136 CABOT CIR,SACRAMENTO,95820,CA,4,2,1462,Residential,Thu May 15 00:00:00 EDT 2008,121500,38.528479,-121.411806 7730 ROBINETTE RD,SACRAMENTO,95828,CA,3,2,1269,Residential,Thu May 15 00:00:00 EDT 2008,122000,38.47709,-121.410569 87 LACAM CIR,SACRAMENTO,95820,CA,2,2,1188,Residential,Thu May 15 00:00:00 EDT 2008,123675,38.532359,-121.41167 1691 NOGALES ST,SACRAMENTO,95838,CA,4,2,1570,Residential,Thu May 15 00:00:00 EDT 2008,126854,38.631925,-121.427775 3118 42ND ST,SACRAMENTO,95817,CA,3,2,1093,Residential,Thu May 15 00:00:00 EDT 2008,127059,38.546091,-121.457745 7517 50TH AVE,SACRAMENTO,95828,CA,3,1,962,Residential,Thu May 15 00:00:00 EDT 2008,128687,38.507339,-121.416267 4071 EVALITA WAY,SACRAMENTO,95823,CA,3,2,1089,Residential,Thu May 15 00:00:00 EDT 2008,129500,38.466388,-121.458861 7928 36TH AVE,SACRAMENTO,95824,CA,3,2,1127,Residential,Thu May 15 00:00:00 EDT 2008,130000,38.52049,-121.411383 6631 DEMARET DR,SACRAMENTO,95822,CA,4,2,1309,Residential,Thu May 15 00:00:00 EDT 2008,131750,38.506382,-121.483574 7043 9TH AVE,RIO LINDA,95673,CA,2,1,970,Residential,Thu May 15 00:00:00 EDT 2008,132000,38.695589,-121.444133 97 KENNELFORD CIR,SACRAMENTO,95823,CA,3,2,1144,Residential,Thu May 15 00:00:00 EDT 2008,134000,38.462376,-121.426556 2636 TRONERO WAY,RANCHO CORDOVA,95670,CA,3,1,1000,Residential,Thu May 15 00:00:00 EDT 2008,134000,38.593049,-121.30304 1530 TOPANGA LN Unit 204,LINCOLN,95648,CA,0,0,0,Condo,Thu May 15 00:00:00 EDT 2008,138000,38.88415,-121.270277 3604 KODIAK WAY,ANTELOPE,95843,CA,3,2,1206,Residential,Thu May 15 00:00:00 EDT 2008,142000,38.706175,-121.379776 2149 COTTAGE WAY,SACRAMENTO,95825,CA,3,1,1285,Residential,Thu May 15 00:00:00 EDT 2008,143012,38.603593,-121.417011 8632 PRAIRIEWOODS DR,SACRAMENTO,95828,CA,3,2,1543,Residential,Thu May 15 00:00:00 EDT 2008,145846,38.477563,-121.384382 612 STONE BLVD,WEST SACRAMENTO,95691,CA,2,1,884,Residential,Thu May 15 00:00:00 EDT 2008,147000,38.563084,-121.535579 4180 12TH AVE,SACRAMENTO,95817,CA,3,1,1019,Residential,Thu May 15 00:00:00 EDT 2008,148750,38.54117,-121.458129 8025 ARROYO VISTA DR,SACRAMENTO,95823,CA,4,2,1392,Residential,Thu May 15 00:00:00 EDT 2008,150000,38.46654,-121.419029 5754 WALERGA RD Unit 4,SACRAMENTO,95842,CA,2,1,924,Condo,Thu May 15 00:00:00 EDT 2008,150454,38.672567,-121.356754 8 LA ROCAS CT,SACRAMENTO,95823,CA,3,2,1217,Residential,Thu May 15 00:00:00 EDT 2008,151087,38.46616,-121.448283 8636 LONGSPUR WAY,ANTELOPE,95843,CA,3,2,1670,Residential,Thu May 15 00:00:00 EDT 2008,157296,38.725873,-121.35856 1941 EXPEDITION WAY,SACRAMENTO,95832,CA,3,2,1302,Residential,Thu May 15 00:00:00 EDT 2008,157500,38.473775,-121.493777 4351 TURNBRIDGE DR,SACRAMENTO,95823,CA,3,2,1488,Residential,Thu May 15 00:00:00 EDT 2008,160000,38.502034,-121.456027 6513 HOLIDAY WAY,NORTH HIGHLANDS,95660,CA,3,2,1373,Residential,Thu May 15 00:00:00 EDT 2008,160000,38.685361,-121.376938 8321 MISTLETOE WAY,CITRUS HEIGHTS,95621,CA,4,2,1381,Residential,Thu May 15 00:00:00 EDT 2008,161250,38.717738,-121.308322 5920 VALLEY GLEN WAY,SACRAMENTO,95823,CA,3,2,1265,Residential,Thu May 15 00:00:00 EDT 2008,164000,38.462821,-121.433135 2601 SAN FERNANDO WAY,SACRAMENTO,95818,CA,2,1,881,Residential,Thu May 15 00:00:00 EDT 2008,165000,38.556178,-121.476256 501 POPLAR AVE,WEST SACRAMENTO,95691,CA,0,0,0,Residential,Thu May 15 00:00:00 EDT 2008,165000,38.584526,-121.534609 8008 SAINT HELENA CT,SACRAMENTO,95829,CA,4,2,1608,Residential,Thu May 15 00:00:00 EDT 2008,165750,38.467012,-121.359969 6517 DONEGAL DR,CITRUS HEIGHTS,95621,CA,3,1,1344,Residential,Thu May 15 00:00:00 EDT 2008,166000,38.681554,-121.312934 1001 RIO NORTE WAY,SACRAMENTO,95834,CA,3,2,1202,Residential,Thu May 15 00:00:00 EDT 2008,169000,38.634292,-121.485106 604 P ST,LINCOLN,95648,CA,3,2,1104,Residential,Thu May 15 00:00:00 EDT 2008,170000,38.893168,-121.305398 10001 WOODCREEK OAKS BLVD Unit 815,ROSEVILLE,95747,CA,2,2,0,Condo,Thu May 15 00:00:00 EDT 2008,170000,38.795529,-121.328819 7351 GIGI PL,SACRAMENTO,95828,CA,4,2,1859,Multi-Family,Thu May 15 00:00:00 EDT 2008,170000,38.490606,-121.410173 7740 DIXIE LOU ST,SACRAMENTO,95832,CA,3,2,1232,Residential,Thu May 15 00:00:00 EDT 2008,170000,38.475853,-121.477039 7342 DAVE ST,SACRAMENTO,95828,CA,3,1,1638,Residential,Thu May 15 00:00:00 EDT 2008,170725,38.490822,-121.401643 7687 HOWERTON DR,SACRAMENTO,95831,CA,2,2,1177,Residential,Thu May 15 00:00:00 EDT 2008,171750,38.480859,-121.539745 26 KAMSON CT,SACRAMENTO,95833,CA,3,2,1582,Residential,Thu May 15 00:00:00 EDT 2008,172000,38.622794,-121.499173 7045 PEEVEY CT,SACRAMENTO,95823,CA,2,2,904,Residential,Thu May 15 00:00:00 EDT 2008,173056,38.502254,-121.451444 8916 GABLES MILL PL,ELK GROVE,95758,CA,3,2,1340,Residential,Thu May 15 00:00:00 EDT 2008,174000,38.433919,-121.422347 1140 EDMONTON DR,SACRAMENTO,95833,CA,3,2,1204,Residential,Thu May 15 00:00:00 EDT 2008,174250,38.62457,-121.486913 8879 APPLE PEAR CT,ELK GROVE,95624,CA,4,2,1477,Residential,Thu May 15 00:00:00 EDT 2008,176850,38.44574,-121.3725 9 WIND CT,SACRAMENTO,95823,CA,4,2,1497,Residential,Thu May 15 00:00:00 EDT 2008,179500,38.45073,-121.427528 8570 SHERATON DR,FAIR OAKS,95628,CA,3,1,960,Residential,Thu May 15 00:00:00 EDT 2008,185000,38.667254,-121.240708 1550 TOPANGA LN Unit 207,LINCOLN,95648,CA,0,0,0,Condo,Thu May 15 00:00:00 EDT 2008,188000,38.88417,-121.270222 1080 RIO NORTE WAY,SACRAMENTO,95834,CA,3,2,1428,Residential,Thu May 15 00:00:00 EDT 2008,188700,38.634335,-121.486098 5501 VALLETTA WAY,SACRAMENTO,95820,CA,3,1,1039,Residential,Thu May 15 00:00:00 EDT 2008,189000,38.530144,-121.43749 5624 MEMORY LN,FAIR OAKS,95628,CA,3,1,1529,Residential,Thu May 15 00:00:00 EDT 2008,189000,38.66745,-121.2364 6622 WILLOWLEAF DR,CITRUS HEIGHTS,95621,CA,4,3,1892,Residential,Thu May 15 00:00:00 EDT 2008,189836,38.699714,-121.311635 27 MEGAN CT,SACRAMENTO,95838,CA,4,2,1887,Residential,Thu May 15 00:00:00 EDT 2008,190000,38.649258,-121.465308 6601 WOODMORE OAKS DR,ORANGEVALE,95662,CA,3,2,1294,Residential,Thu May 15 00:00:00 EDT 2008,191250,38.687006,-121.254319 1973 DANVERS WAY,SACRAMENTO,95832,CA,3,2,1638,Residential,Thu May 15 00:00:00 EDT 2008,191675,38.477568,-121.492574 8001 ARROYO VISTA DR,SACRAMENTO,95823,CA,3,2,1677,Residential,Thu May 15 00:00:00 EDT 2008,195500,38.46734,-121.419843 7409 VOYAGER WAY,CITRUS HEIGHTS,95621,CA,3,1,1073,Residential,Thu May 15 00:00:00 EDT 2008,198000,38.700717,-121.3133 815 CROSSWIND DR,SACRAMENTO,95838,CA,3,2,1231,Residential,Thu May 15 00:00:00 EDT 2008,200000,38.651386,-121.45042 5509 LAGUNA CREST WAY,ELK GROVE,95758,CA,3,2,1175,Residential,Thu May 15 00:00:00 EDT 2008,200000,38.42442,-121.440357 8424 MERRY HILL WAY,ELK GROVE,95624,CA,3,2,1416,Residential,Thu May 15 00:00:00 EDT 2008,200000,38.452075,-121.366461 1525 PENNSYLVANIA AVE,WEST SACRAMENTO,95691,CA,0,0,0,Residential,Thu May 15 00:00:00 EDT 2008,200100,38.569943,-121.527539 5954 BRIDGECROSS DR,SACRAMENTO,95835,CA,3,2,1358,Residential,Thu May 15 00:00:00 EDT 2008,201528,38.68197,-121.500025 8789 SEQUOIA WOOD CT,ELK GROVE,95624,CA,4,2,1609,Residential,Thu May 15 00:00:00 EDT 2008,204750,38.438818,-121.37443 6600 SILVERTHORNE CIR,SACRAMENTO,95842,CA,4,3,1968,Residential,Thu May 15 00:00:00 EDT 2008,205000,38.68607,-121.342369 2221 2ND AVE,SACRAMENTO,95818,CA,2,2,1089,Residential,Thu May 15 00:00:00 EDT 2008,205000,38.555781,-121.485331 3230 SMATHERS WAY,CARMICHAEL,95608,CA,3,2,1296,Residential,Thu May 15 00:00:00 EDT 2008,205900,38.623372,-121.347665 5209 LAGUNA CREST WAY,ELK GROVE,95758,CA,2,2,1189,Residential,Thu May 15 00:00:00 EDT 2008,207000,38.424421,-121.443915 416 LEITCH AVE,SACRAMENTO,95815,CA,2,1,795,Residential,Thu May 15 00:00:00 EDT 2008,207973,38.612694,-121.456669 2100 BEATTY WAY,ROSEVILLE,95747,CA,3,2,1371,Residential,Thu May 15 00:00:00 EDT 2008,208250,38.737882,-121.308142 6920 GILLINGHAM WAY,NORTH HIGHLANDS,95660,CA,3,1,1310,Residential,Thu May 15 00:00:00 EDT 2008,208318,38.694279,-121.373395 82 WILDFLOWER DR,GALT,95632,CA,3,2,1262,Residential,Thu May 15 00:00:00 EDT 2008,209347,38.259708,-121.311616 8652 BANTON CIR,ELK GROVE,95624,CA,4,2,1740,Residential,Thu May 15 00:00:00 EDT 2008,211500,38.444,-121.370993 8428 MISTY PASS WAY,ANTELOPE,95843,CA,3,2,1517,Residential,Thu May 15 00:00:00 EDT 2008,212000,38.722959,-121.347115 7958 ROSEVIEW WAY,SACRAMENTO,95828,CA,3,2,1450,Residential,Thu May 15 00:00:00 EDT 2008,213000,38.467836,-121.410366 9020 LUKEN CT,ELK GROVE,95624,CA,3,2,1416,Residential,Thu May 15 00:00:00 EDT 2008,216000,38.451398,-121.366614 7809 VALLECITOS WAY,SACRAMENTO,95828,CA,3,1,888,Residential,Thu May 15 00:00:00 EDT 2008,216021,38.508217,-121.411207 8445 OLD AUBURN RD,CITRUS HEIGHTS,95610,CA,3,2,1882,Residential,Thu May 15 00:00:00 EDT 2008,219000,38.715423,-121.246743 10085 ATKINS DR,ELK GROVE,95757,CA,3,2,1302,Residential,Thu May 15 00:00:00 EDT 2008,219794,38.390893,-121.437821 9185 CERROLINDA CIR,ELK GROVE,95758,CA,3,2,1418,Residential,Thu May 15 00:00:00 EDT 2008,220000,38.424497,-121.426595 9197 CORTINA CIR,ROSEVILLE,95678,CA,3,2,0,Condo,Thu May 15 00:00:00 EDT 2008,220000,38.793152,-121.290025 5429 HESPER WAY,CARMICHAEL,95608,CA,4,2,1319,Residential,Thu May 15 00:00:00 EDT 2008,220000,38.665104,-121.315901 1178 WARMWOOD CT,GALT,95632,CA,4,2,1770,Residential,Thu May 15 00:00:00 EDT 2008,220000,38.289544,-121.284607 4900 ELUDE CT,SACRAMENTO,95842,CA,4,2,1627,Residential,Thu May 15 00:00:00 EDT 2008,223000,38.69674,-121.350519 3557 SODA WAY,SACRAMENTO,95834,CA,0,0,0,Residential,Thu May 15 00:00:00 EDT 2008,224000,38.631026,-121.501879 3528 SAINT GEORGE DR,SACRAMENTO,95821,CA,3,1,1040,Residential,Thu May 15 00:00:00 EDT 2008,224000,38.629468,-121.376445 7381 WASHBURN WAY,NORTH HIGHLANDS,95660,CA,3,1,960,Residential,Thu May 15 00:00:00 EDT 2008,224252,38.70355,-121.375103 2181 WINTERHAVEN CIR,CAMERON PARK,95682,CA,3,2,0,Residential,Thu May 15 00:00:00 EDT 2008,224500,38.69757,-120.995739 7540 HICKORY AVE,ORANGEVALE,95662,CA,3,1,1456,Residential,Thu May 15 00:00:00 EDT 2008,225000,38.703056,-121.235221 5024 CHAMBERLIN CIR,ELK GROVE,95757,CA,3,2,1450,Residential,Thu May 15 00:00:00 EDT 2008,228000,38.389756,-121.446246 2400 INVERNESS DR,LINCOLN,95648,CA,3,2,1358,Residential,Thu May 15 00:00:00 EDT 2008,229027,38.897814,-121.324691 5 BISHOPGATE CT,SACRAMENTO,95823,CA,4,2,1329,Residential,Thu May 15 00:00:00 EDT 2008,229500,38.467936,-121.445477 5601 REXLEIGH DR,SACRAMENTO,95823,CA,4,2,1715,Residential,Thu May 15 00:00:00 EDT 2008,230000,38.445342,-121.441504 1909 YARNELL WAY,ELK GROVE,95758,CA,3,2,1262,Residential,Thu May 15 00:00:00 EDT 2008,230000,38.417382,-121.484325 9169 GARLINGTON CT,SACRAMENTO,95829,CA,4,3,2280,Residential,Thu May 15 00:00:00 EDT 2008,232425,38.457679,-121.35962 6932 RUSKUT WAY,SACRAMENTO,95823,CA,3,2,1477,Residential,Thu May 15 00:00:00 EDT 2008,234000,38.499893,-121.45889 7933 DAFFODIL WAY,CITRUS HEIGHTS,95610,CA,3,2,1216,Residential,Thu May 15 00:00:00 EDT 2008,235000,38.708824,-121.256803 8304 RED FOX WAY,ELK GROVE,95758,CA,4,2,1685,Residential,Thu May 15 00:00:00 EDT 2008,235301,38.417,-121.397424 3882 YELLOWSTONE LN,EL DORADO HILLS,95762,CA,3,2,1362,Residential,Thu May 15 00:00:00 EDT 2008,235738,38.655245,-121.075915 snakemake-5.10.0/tests/test_restartable_job_cmd_exit_1/000077500000000000000000000000001361131222100231635ustar00rootroot00000000000000snakemake-5.10.0/tests/test_restartable_job_cmd_exit_1/Snakefile000066400000000000000000000005731361131222100250140ustar00rootroot00000000000000localrules: all rule all: input: '.done' rule fails_sometimes: output: '.done' resources: mem=lambda wildcards, attempt: 100 * attempt shell: r""" echo {resources.mem} if [[ ! -f ".first" ]]; then touch .first exit 1 else echo {resources.mem} > {output} fi """ snakemake-5.10.0/tests/test_restartable_job_cmd_exit_1/expected-results/000077500000000000000000000000001361131222100264635ustar00rootroot00000000000000snakemake-5.10.0/tests/test_restartable_job_cmd_exit_1/expected-results/.done000066400000000000000000000000041361131222100274030ustar00rootroot00000000000000200 snakemake-5.10.0/tests/test_restartable_job_cmd_exit_1/qsub000077500000000000000000000002071361131222100240620ustar00rootroot00000000000000#!/bin/bash echo `date` >> qsub.log tail -n1 $1 >> qsub.log # simulate printing of job id by a random number echo $RANDOM sh $1 exit 0 snakemake-5.10.0/tests/test_restartable_job_cmd_exit_1/qsub.py000077500000000000000000000004771361131222100245220ustar00rootroot00000000000000#!/usr/bin/env python3 import sys import os import random from snakemake.utils import read_job_properties jobscript = sys.argv[1] job_properties = read_job_properties(jobscript) with open("qsub.log", "a") as log: print(job_properties, file=log) print(random.randint(1, 100)) os.system("sh {}".format(jobscript)) snakemake-5.10.0/tests/test_restartable_job_qsub_exit_1/000077500000000000000000000000001361131222100233725ustar00rootroot00000000000000snakemake-5.10.0/tests/test_restartable_job_qsub_exit_1/Snakefile000066400000000000000000000001711361131222100252150ustar00rootroot00000000000000localrules: all rule all: input: '.done' rule fails_sometimes: output: '.done' shell: r""" touch .done """ snakemake-5.10.0/tests/test_restartable_job_qsub_exit_1/expected-results/000077500000000000000000000000001361131222100266725ustar00rootroot00000000000000snakemake-5.10.0/tests/test_restartable_job_qsub_exit_1/expected-results/.done000066400000000000000000000000001361131222100276060ustar00rootroot00000000000000snakemake-5.10.0/tests/test_restartable_job_qsub_exit_1/qsub000077500000000000000000000003451361131222100242740ustar00rootroot00000000000000#!/bin/bash echo `date` >> qsub.log tail -n1 $1 >> qsub.log # ensure to fail on the first submission if [[ ! -f ".first" ]]; then touch .first exit 1 fi # simulate printing of job id by a random number echo $RANDOM sh $1 snakemake-5.10.0/tests/test_restartable_job_qsub_exit_1/qsub.log000066400000000000000000000000351361131222100250450ustar00rootroot00000000000000Mo 12. Dez 14:36:23 CET 2016 snakemake-5.10.0/tests/test_restartable_job_qsub_exit_1/qsub.py000077500000000000000000000004771361131222100247310ustar00rootroot00000000000000#!/usr/bin/env python3 import sys import os import random from snakemake.utils import read_job_properties jobscript = sys.argv[1] job_properties = read_job_properties(jobscript) with open("qsub.log", "a") as log: print(job_properties, file=log) print(random.randint(1, 100)) os.system("sh {}".format(jobscript)) snakemake-5.10.0/tests/test_rule_defined_in_for_loop/000077500000000000000000000000001361131222100227375ustar00rootroot00000000000000snakemake-5.10.0/tests/test_rule_defined_in_for_loop/Snakefile000066400000000000000000000003761361131222100245710ustar00rootroot00000000000000rule all: input: 'iteration-02.txt' for i in range(2, 4): rule: output: fasta='iteration-{nr:02d}.txt'.format(nr=i) input: fasta='iteration-{nr:02d}.txt'.format(nr=i-1) run: shell("cp -p {input.fasta} {output.fasta}") snakemake-5.10.0/tests/test_rule_defined_in_for_loop/expected-results/000077500000000000000000000000001361131222100262375ustar00rootroot00000000000000snakemake-5.10.0/tests/test_rule_defined_in_for_loop/expected-results/iteration-01.txt000066400000000000000000000000001361131222100312020ustar00rootroot00000000000000snakemake-5.10.0/tests/test_rule_defined_in_for_loop/expected-results/iteration-02.txt000066400000000000000000000000001361131222100312030ustar00rootroot00000000000000snakemake-5.10.0/tests/test_rule_defined_in_for_loop/iteration-01.txt000066400000000000000000000000001361131222100257020ustar00rootroot00000000000000snakemake-5.10.0/tests/test_ruledag/000077500000000000000000000000001361131222100173505ustar00rootroot00000000000000snakemake-5.10.0/tests/test_ruledag/1.a000066400000000000000000000000001361131222100176400ustar00rootroot00000000000000snakemake-5.10.0/tests/test_ruledag/2.a000066400000000000000000000000001361131222100176410ustar00rootroot00000000000000snakemake-5.10.0/tests/test_ruledag/3.a000066400000000000000000000000001361131222100176420ustar00rootroot00000000000000snakemake-5.10.0/tests/test_ruledag/4.a000066400000000000000000000000001361131222100176430ustar00rootroot00000000000000snakemake-5.10.0/tests/test_ruledag/5.a000066400000000000000000000000001361131222100176440ustar00rootroot00000000000000snakemake-5.10.0/tests/test_ruledag/Snakefile000066400000000000000000000006051361131222100211750ustar00rootroot00000000000000 rule all: input: expand("{id}.d", id="1 2 3 4 5".split()) rule rule1: input: "{id}.c" output: "{id}.d" shell: "touch {output}" rule rule2: input: lambda wildcards: (expand("{id}.b", id="1 2 3".split()) if wildcards.id == "1" else expand("{id}.b", id=wildcards.id)) output: "{id}.c" shell: "touch {output}" rule rule3: input: "{id}.a" output: "{id}.b" shell: "touch {output}" snakemake-5.10.0/tests/test_ruledeps/000077500000000000000000000000001361131222100175505ustar00rootroot00000000000000snakemake-5.10.0/tests/test_ruledeps/Snakefile000066400000000000000000000005711361131222100213770ustar00rootroot00000000000000 rule all: input: "test.out" rule a: output: "{sample,.+}.in" shell: "touch {output}" rule b: input: rules.a.output output: "{sample}.inter" shell: "touch {output}" rule c: input: rules.a.output output: "{sample}.inter" shell: "exit 1" rule d: input: rules.b.output output: "{sample}.out" shell: "touch {output}" snakemake-5.10.0/tests/test_ruledeps/expected-results/000077500000000000000000000000001361131222100230505ustar00rootroot00000000000000snakemake-5.10.0/tests/test_ruledeps/expected-results/test.out000066400000000000000000000000001361131222100245460ustar00rootroot00000000000000snakemake-5.10.0/tests/test_run_namedlist/000077500000000000000000000000001361131222100205715ustar00rootroot00000000000000snakemake-5.10.0/tests/test_run_namedlist/Snakefile000066400000000000000000000001521361131222100224130ustar00rootroot00000000000000rule: output: txt='file.txt' run: shell('touch {output.txt}') os.stat(output.txt) snakemake-5.10.0/tests/test_run_namedlist/expected-results/000077500000000000000000000000001361131222100240715ustar00rootroot00000000000000snakemake-5.10.0/tests/test_run_namedlist/expected-results/file.txt000066400000000000000000000000001361131222100255370ustar00rootroot00000000000000snakemake-5.10.0/tests/test_same_wildcard/000077500000000000000000000000001361131222100205235ustar00rootroot00000000000000snakemake-5.10.0/tests/test_same_wildcard/Snakefile000066400000000000000000000002121361131222100223420ustar00rootroot00000000000000 rule: input: "test_test.out" rule: input: "{name}_{name}.in" output: "{name}_{name}.out" shell: "echo {wildcards.name} > {output}" snakemake-5.10.0/tests/test_same_wildcard/expected-results/000077500000000000000000000000001361131222100240235ustar00rootroot00000000000000snakemake-5.10.0/tests/test_same_wildcard/expected-results/test_test.out000066400000000000000000000000051361131222100265650ustar00rootroot00000000000000test snakemake-5.10.0/tests/test_same_wildcard/test_test.in000066400000000000000000000000051361131222100230640ustar00rootroot00000000000000test snakemake-5.10.0/tests/test_schema.py000066400000000000000000000070011361131222100175350ustar00rootroot00000000000000import json import pytest from snakemake.utils import validate import pandas as pd CONFIG_SCHEMA = """$schema: "http://json-schema.org/draft-07/schema#" description: Configuration schema type: object properties: param: type: object description: parameter settings # Necessary in case config is empty! default: {} properties: foo: type: string default: bar """ BAR_SCHEMA = """definitions: bar: type: string description: bar entry default: foo """ BAR_JSON_SCHEMA = { "definitions": { "jsonbar": {"type": "string", "description": "bar entry", "default": "foo"} } } DF_SCHEMA = """$schema: "http://json-schema.org/draft-04/schema#" description: an entry in the sample sheet properties: sample: type: string description: sample name/identifier condition: type: string description: sample condition that will be compared during differential expression analysis (e.g. a treatment, a tissue time, a disease) case: type: boolean default: true description: boolean that indicates if sample is case or control date: type: string format: date-time description: collection date default: "2018-10-10" required: - sample - condition """ @pytest.fixture def schemadir(tmpdir): p = tmpdir.mkdir("schema") return p @pytest.fixture def bar_schema(schemadir): p = schemadir.join("bar.schema.yaml") p.write(BAR_SCHEMA) return p @pytest.fixture def json_bar_schema(schemadir): p = schemadir.join("bar.schema.json") p.write(json.dumps(BAR_JSON_SCHEMA)) return p @pytest.fixture def df_schema(schemadir): p = schemadir.join("df.schema.yaml") p.write(DF_SCHEMA) return p @pytest.fixture def config_schema(schemadir): p = schemadir.join("config.schema.yaml") p.write(CONFIG_SCHEMA) return p @pytest.fixture def config_schema_ref(schemadir, bar_schema, json_bar_schema): p = schemadir.join("config.ref.schema.yaml") p.write( CONFIG_SCHEMA + "\n".join( [ " bar:", ' default: "yaml"', ' $ref: "{bar}"'.format( bar=str(bar_schema) + "#/definitions/bar" ), " jsonbar:", ' default: "json"', ' $ref: "{bar}"'.format( bar=str(json_bar_schema) + "#/definitions/jsonbar" ), "", ] ) ) return p def test_config(config_schema): config = {} validate(config, str(config_schema), False) assert config == {} validate(config, str(config_schema)) assert dict(config) == {"param": {"foo": "bar"}} def test_config_ref(config_schema_ref): config = {} validate(config, str(config_schema_ref)) assert config["param"]["foo"] == "bar" assert config["param"]["bar"] == "yaml" assert config["param"]["jsonbar"] == "json" # Make sure regular validator works config["param"]["bar"] = 1 config["param"]["jsonbar"] = 2 from snakemake import WorkflowError with pytest.raises(WorkflowError): validate(config, str(config_schema_ref), False) def test_dataframe(df_schema): df = pd.DataFrame([{"sample": "foo", "condition": "bar"}]) validate(df, str(df_schema), False) assert sorted(df.columns) == sorted(["sample", "condition"]) validate(df, str(df_schema)) assert sorted(df.columns) == sorted(["sample", "condition", "case", "date"]) assert df.case.loc[0] snakemake-5.10.0/tests/test_script/000077500000000000000000000000001361131222100172315ustar00rootroot00000000000000snakemake-5.10.0/tests/test_script/Snakefile000066400000000000000000000015261361131222100210610ustar00rootroot00000000000000 configfile: "config.yaml" rule all: input: "test.out", "test.html", "rel_source.out", "julia.out" rule: input: "test.in" output: txt="test.out" params: xy=True conda: "envs/r.yaml" script: "scripts/test.R" rule: output: "test.in" script: "scripts/test.py" rule: output: "test.html" params: test="testparam" conda: "envs/r.yaml" script: "scripts/test.Rmd" rule: output: "rel_source.out" conda: "envs/r.yaml" script: "scripts/rel_source.R" rule: input: "test.in", named_input="test.in" output: "julia.out" params: integer=123 conda: "envs/julia.yaml" script: "scripts/test.jl" snakemake-5.10.0/tests/test_script/config.yaml000066400000000000000000000000131361131222100213540ustar00rootroot00000000000000test: true snakemake-5.10.0/tests/test_script/envs/000077500000000000000000000000001361131222100202045ustar00rootroot00000000000000snakemake-5.10.0/tests/test_script/envs/julia.yaml000066400000000000000000000000771361131222100222000ustar00rootroot00000000000000channels: - conda-forge - bioconda dependencies: - julia snakemake-5.10.0/tests/test_script/envs/r.yaml000066400000000000000000000002631361131222100213320ustar00rootroot00000000000000channels: - conda-forge - bioconda dependencies: - r-base =3.6.1 - r-rmarkdown =1.17 - xorg-libxrender - xorg-libxext - xorg-libxau - xorg-libxdmcp - xorg-libsm snakemake-5.10.0/tests/test_script/expected-results/000077500000000000000000000000001361131222100225315ustar00rootroot00000000000000snakemake-5.10.0/tests/test_script/expected-results/julia.out000066400000000000000000000000251361131222100243630ustar00rootroot00000000000000Julia test succeded! snakemake-5.10.0/tests/test_script/expected-results/rel_source.out000066400000000000000000000000021361131222100254140ustar00rootroot00000000000000Hisnakemake-5.10.0/tests/test_script/expected-results/test.html000066400000000000000000030307171361131222100244110ustar00rootroot00000000000000 Test Report

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Test include from snakemake testparam.

snakemake-5.10.0/tests/test_script/expected-results/test.in000066400000000000000000000000061361131222100240340ustar00rootroot000000000000001 2 3 snakemake-5.10.0/tests/test_script/expected-results/test.out000066400000000000000000000000061361131222100242350ustar00rootroot000000000000001 2 3 snakemake-5.10.0/tests/test_script/scripts/000077500000000000000000000000001361131222100207205ustar00rootroot00000000000000snakemake-5.10.0/tests/test_script/scripts/rel_source.R000066400000000000000000000001051361131222100232010ustar00rootroot00000000000000snakemake@source("source_me.R") cat(hi(),file=snakemake@output[[1]]) snakemake-5.10.0/tests/test_script/scripts/source_me.R000066400000000000000000000000371361131222100230240ustar00rootroot00000000000000hi <- function(){return("Hi")} snakemake-5.10.0/tests/test_script/scripts/test.R000066400000000000000000000005541361131222100220260ustar00rootroot00000000000000print(snakemake@wildcards) print(snakemake@threads) print(snakemake@log) print(snakemake@config) print(snakemake@params) if(snakemake@params[["xy"]] != TRUE) { stop("Error evaluating param.") } if(snakemake@config[["test"]] != TRUE) { stop("Error evaluating config.") } values <- scan(snakemake@input[[1]]) write(values, file = snakemake@output[["txt"]]) snakemake-5.10.0/tests/test_script/scripts/test.Rmd000066400000000000000000000005471361131222100223510ustar00rootroot00000000000000--- title: "Test Report" author: "Mattias" date: "March 22, 2017" output: html_document: highlight: tango number_sections: no theme: default toc: yes toc_depth: 3 toc_float: collapsed: no smooth_scroll: yes --- ## R Markdown This is an R Markdown document. Test include from snakemake `r snakemake@params[["test"]]`. snakemake-5.10.0/tests/test_script/scripts/test.jl000066400000000000000000000005161361131222100222300ustar00rootroot00000000000000println("Julia script executing!") @assert snakemake.config["test"] == true @assert snakemake.params["integer"] == 123 @assert snakemake.output[1] == "julia.out" @assert snakemake.input[1] == "test.in" @assert snakemake.input["named_input"] == "test.in" f = open(snakemake.output[1], "w") println(f, "Julia test succeded!") close(f)snakemake-5.10.0/tests/test_script/scripts/test.py000066400000000000000000000001111361131222100222420ustar00rootroot00000000000000with open(snakemake.output[0], "w") as out: print(1, 2, 3, file=out) snakemake-5.10.0/tests/test_shadow/000077500000000000000000000000001361131222100172125ustar00rootroot00000000000000snakemake-5.10.0/tests/test_shadow/Snakefile000066400000000000000000000077161361131222100210510ustar00rootroot00000000000000rule all: input: "simple_shallow.out", "simple_full.out", "absolute_exists.out", "touched.out", "log_exists.out", "protected.out", "benchmark_exists.out", "minimal_ok.out" rule shallow: input: "test.in" output: "simple_shallow.out" shadow: "shallow" shell: """ echo 1 > junk.out cat {input} >> {output} echo simple_shallow >> {output} test ! -f more_junk.out """ rule full: input: "test.in" output: "simple_full.out" shadow: "full" shell: """ echo 1 > more_junk.out cat {input} > {output} echo simple_full >> {output} test ! -f junk.out """ rule absolute_link: input: "test.in" output: "absolute.out", "absolute_link.out" shadow: "shallow" shell: """ echo 1 > absolute.out DIRNAME=$(perl -e 'use Cwd "abs_path"; print abs_path(shift)' .) ln -s $DIRNAME/absolute.out absolute_link.out """ # Snakemake has check_broken_symlink so we just need to test existence rule absolute_stat: input: "absolute_link.out" output: touch("absolute_exists.out") shell: """ test -f {input} """ rule log_stat: input: "touched.out" output: touch("log_exists.out") shell: """ test -f shadow.log """ rule touch: output: touch("touched.out") log: "shadow.log" shadow: "shallow" shell: """ echo 1 > {log} """ rule protected: output: protected("protected.out") shadow: "shallow" shell: """ touch {output} """ rule benchmark: output: touch("benchmark.out") benchmark: "benchmark.txt" shadow: "shallow" shell: """ touch {output} """ rule benchmark_stat: input: "benchmark.out" output: touch("benchmark_exists.out") shell: """ test -f benchmark.txt """ # Setup files for testing of shadow: "minimal" rule minimal_setup: input: "test.in" output: "subdir1/subdir2/test.in", "subdir1/subdir2/test.symbolic.in" shell: """ cp -P {input} {output[0]} cd subdir1/subdir2 ln -s test.in test.symbolic.in """ # Tests relative inputs/outputs and in the current dir rule minimal_rel_curdir: input: "test.in" output: protected("simple_minimal.out") benchmark: "benchmark_minimal.txt" log: "minimal.log" shadow: "minimal" shell: """ touch minimal_junk.out cat {input} >> {output} echo simple_minimal >> {output} echo minimal_log > {log} """ # Tests relative inputs/outputs in subdirectories rule minimal_rel_subdir: input: "subdir1/subdir2/test.in" output: "outdir/minimal.out" shadow: "minimal" shell: """ touch outdir/minimal_junk.out touch {output} """ # Tests symbolic input/output rule minimal_symbolic: input: "subdir1/subdir2/test.symbolic.in" output: "outdir/minimal_real.out", "outdir/minimal_symbolic.out" shadow: "minimal" shell: """ touch outdir/minimal_real.out cd outdir ln -s minimal_real.out minimal_symbolic.out """ # Tests absolute input/output rule minimal_absolute: input: os.path.join(os.getcwd(),"test.in") output: os.path.join(os.getcwd(),"outdir/minimal_absolute.out") shadow: "minimal" shell: """ touch {output} """ # Aggregates tests for shadow: "minimal" rule minimal_ok: input: "simple_minimal.out", "outdir/minimal.out", "outdir/minimal_symbolic.out", os.path.join(os.getcwd(),"outdir/minimal_absolute.out") output: "minimal_ok.out" shell: """ #test ! -w {input[0]} test -f benchmark_minimal.txt test -f minimal.log test ! -f minimal_junk.out test ! -f outdir/minimal_junk.out touch {output} """ snakemake-5.10.0/tests/test_shadow/expected-results/000077500000000000000000000000001361131222100225125ustar00rootroot00000000000000snakemake-5.10.0/tests/test_shadow/expected-results/simple_full.out000066400000000000000000000000171361131222100255540ustar00rootroot00000000000000in simple_full snakemake-5.10.0/tests/test_shadow/expected-results/simple_minimal.out000066400000000000000000000000221361131222100262340ustar00rootroot00000000000000in simple_minimal snakemake-5.10.0/tests/test_shadow/expected-results/simple_shallow.out000066400000000000000000000000221361131222100262570ustar00rootroot00000000000000in simple_shallow snakemake-5.10.0/tests/test_shadow/test.in000066400000000000000000000000031361131222100205120ustar00rootroot00000000000000in snakemake-5.10.0/tests/test_shadow_prefix/000077500000000000000000000000001361131222100205675ustar00rootroot00000000000000snakemake-5.10.0/tests/test_shadow_prefix/Snakefile000066400000000000000000000002131361131222100224070ustar00rootroot00000000000000rule all: input: "test.in" output: "shadow_prefix" shadow: "shallow" shell: "test -h shadowdir && cp -L {input} {output}" snakemake-5.10.0/tests/test_shadow_prefix/expected-results/000077500000000000000000000000001361131222100240675ustar00rootroot00000000000000snakemake-5.10.0/tests/test_shadow_prefix/expected-results/shadow_prefix000066400000000000000000000000031361131222100266450ustar00rootroot00000000000000in snakemake-5.10.0/tests/test_shadow_prefix/qsub000077500000000000000000000001751361131222100214720ustar00rootroot00000000000000#!/bin/bash echo `date` >> qsub.log tail -n1 $1 >> qsub.log # simulate printing of job id by a random number echo $RANDOM $1 snakemake-5.10.0/tests/test_shadow_prefix/test.in000066400000000000000000000000031361131222100220670ustar00rootroot00000000000000in snakemake-5.10.0/tests/test_shell/000077500000000000000000000000001361131222100170345ustar00rootroot00000000000000snakemake-5.10.0/tests/test_shell/Snakefile000066400000000000000000000003321361131222100206560ustar00rootroot00000000000000 rule: input: "test.in" output: "test.out" run: test = shell("echo 42;", read=True) assert int(test) == 42 with open(output[0], "w") as f: for l in shell("cat {input}", iterable=True): print(l, file=f) snakemake-5.10.0/tests/test_shell/expected-results/000077500000000000000000000000001361131222100223345ustar00rootroot00000000000000snakemake-5.10.0/tests/test_shell/expected-results/test.out000066400000000000000000000000101361131222100240330ustar00rootroot00000000000000foo bar snakemake-5.10.0/tests/test_shell/test.in000066400000000000000000000000101361131222100203320ustar00rootroot00000000000000foo bar snakemake-5.10.0/tests/test_singularity/000077500000000000000000000000001361131222100202775ustar00rootroot00000000000000snakemake-5.10.0/tests/test_singularity/Snakefile000066400000000000000000000006201361131222100221210ustar00rootroot00000000000000 rule a: input: "test.txt" output: "test.out" singularity: "docker://bash" shell: 'ls {input}; echo "test" > {output}' rule b: output: "test.txt" shell: "touch {output}" rule c: output: "invalid.txt" singularity: "docker://invalid/image url even with whitespace" shell: "touch {output}" snakemake-5.10.0/tests/test_singularity/expected-results/000077500000000000000000000000001361131222100235775ustar00rootroot00000000000000snakemake-5.10.0/tests/test_singularity/expected-results/test.out000066400000000000000000000000051361131222100253020ustar00rootroot00000000000000test snakemake-5.10.0/tests/test_singularity_conda/000077500000000000000000000000001361131222100214435ustar00rootroot00000000000000snakemake-5.10.0/tests/test_singularity_conda/Snakefile000066400000000000000000000003631361131222100232710ustar00rootroot00000000000000 singularity: "docker://continuumio/miniconda3" rule a: output: "test.out" conda: "test-env.yaml" shell: "ls /singularity; " # this fails if not in singularity container "bwa 2> {output} || true" snakemake-5.10.0/tests/test_singularity_conda/expected-results/000077500000000000000000000000001361131222100247435ustar00rootroot00000000000000snakemake-5.10.0/tests/test_singularity_conda/expected-results/test.out000066400000000000000000000022341361131222100264540ustar00rootroot00000000000000 Program: bwa (alignment via Burrows-Wheeler transformation) Version: 0.7.17-r1188 Contact: Heng Li Usage: bwa [options] Command: index index sequences in the FASTA format mem BWA-MEM algorithm fastmap identify super-maximal exact matches pemerge merge overlapping paired ends (EXPERIMENTAL) aln gapped/ungapped alignment samse generate alignment (single ended) sampe generate alignment (paired ended) bwasw BWA-SW for long queries shm manage indices in shared memory fa2pac convert FASTA to PAC format pac2bwt generate BWT from PAC pac2bwtgen alternative algorithm for generating BWT bwtupdate update .bwt to the new format bwt2sa generate SA from BWT and Occ Note: To use BWA, you need to first index the genome with `bwa index'. There are three alignment algorithms in BWA: `mem', `bwasw', and `aln/samse/sampe'. If you are not sure which to use, try `bwa mem' first. Please `man ./bwa.1' for the manual. snakemake-5.10.0/tests/test_singularity_conda/test-env.yaml000066400000000000000000000001061361131222100240710ustar00rootroot00000000000000channels: - bioconda - conda-forge dependencies: - bwa ==0.7.17 snakemake-5.10.0/tests/test_spaces_in_fnames/000077500000000000000000000000001361131222100212225ustar00rootroot00000000000000snakemake-5.10.0/tests/test_spaces_in_fnames/Snakefile000066400000000000000000000011221361131222100230420ustar00rootroot00000000000000rule indelrealigner: input: bam="{base}.bam",intervals="{base}.intervals",bai='{base}.bam.bai' output: bam=temp("{base} realigned.bam") params: batch="-q ccr -l nodes=1:gpfs" threads: 1 shell: "touch {output:q}" rule realignertargetcreator: input: "{base}.bam", "{base}.bam.bai" output: temp("{base}.intervals") params: batch="-q ccr -l nodes=1:gpfs" threads: 32 shell: "touch {output:q}" rule indexbam: threads: 1 input: '{base}.bam' output: temp('{base}.bam.bai') params: batch="-q ccr -l nodes=1:gpfs" shell: 'touch {output:q}' snakemake-5.10.0/tests/test_spaces_in_fnames/expected-results/000077500000000000000000000000001361131222100245225ustar00rootroot00000000000000snakemake-5.10.0/tests/test_spaces_in_fnames/expected-results/test bam file realigned.bam000066400000000000000000000000001361131222100315030ustar00rootroot00000000000000snakemake-5.10.0/tests/test_spaces_in_fnames/qsub000077500000000000000000000001751361131222100221250ustar00rootroot00000000000000#!/bin/bash echo `date` >> qsub.log tail -n1 $1 >> qsub.log # simulate printing of job id by a random number echo $RANDOM $1 snakemake-5.10.0/tests/test_spaces_in_fnames/test bam file.bam000066400000000000000000000000001361131222100242700ustar00rootroot00000000000000snakemake-5.10.0/tests/test_speed/000077500000000000000000000000001361131222100170255ustar00rootroot00000000000000snakemake-5.10.0/tests/test_speed/Snakefile000066400000000000000000000006551361131222100206570ustar00rootroot00000000000000 rule all: input: expand("step3/{sample}.txt", sample=range(100)) rule a: output: "step1/{sample}.txt" shell: "touch {output}" rule b: input: "step1/{sample}.txt" output: "step2/{sample}.txt" shell: "cp {input} {output}" rule c: input: "step2/{sample}.txt" output: "step3/{sample}.txt" shell: "cp {input} {output}" snakemake-5.10.0/tests/test_srcdir/000077500000000000000000000000001361131222100172135ustar00rootroot00000000000000snakemake-5.10.0/tests/test_srcdir/Snakefile000066400000000000000000000001711361131222100210360ustar00rootroot00000000000000rule: output: "test.out" params: srcdir("script.sh") shell: "sh {params} > {output}" snakemake-5.10.0/tests/test_srcdir/expected-results/000077500000000000000000000000001361131222100225135ustar00rootroot00000000000000snakemake-5.10.0/tests/test_srcdir/expected-results/test.out000066400000000000000000000000051361131222100242160ustar00rootroot00000000000000test snakemake-5.10.0/tests/test_srcdir/script.sh000066400000000000000000000000241361131222100210470ustar00rootroot00000000000000#!/bin/sh echo test snakemake-5.10.0/tests/test_static_remote/000077500000000000000000000000001361131222100205675ustar00rootroot00000000000000snakemake-5.10.0/tests/test_static_remote/S3MockedForStaticTest.py000066400000000000000000000115301361131222100252300ustar00rootroot00000000000000__author__ = "Christopher Tomkins-Tinch" __copyright__ = "Copyright 2015, Christopher Tomkins-Tinch" __email__ = "tomkinsc@broadinstitute.org" __license__ = "MIT" # built-ins import os, sys from contextlib import contextmanager import pickle import time import threading import functools # intra-module from snakemake.remote.S3 import RemoteObject as S3RemoteObject, RemoteProvider as S3RemoteProvider from snakemake.remote.S3 import S3Helper from snakemake.decorators import dec_all_methods from snakemake.exceptions import WorkflowError from snakemake.logging import logger try: # third-party import boto3 from moto import mock_s3 import filechunkio except ImportError as e: raise WorkflowError("The Python 3 packages 'moto', boto' and 'filechunkio' " + "need to be installed to use S3Mocked remote() file functionality. %s" % e.msg) def noop(): pass def pickled_moto_wrapper(func): """ This is a class decorator that in turn decorates all methods within a class to mock out boto calls with moto-simulated ones. Since the moto backends are not presistent across calls by default, the wrapper also pickles the bucket state after each function call, and restores it before execution. This way uploaded files are available for follow-on tasks. Since snakemake may execute with multiple threads it also waits for the pickled bucket state file to be available before loading it in. This is a hackey alternative to using proper locks, but works ok in practice. """ def wrapper_func(self, *args, **kwargs): moto_context_file = "motoState.p" moto_context = mock_s3() moto_context.start() moto_context.backends["global"].reset = noop # load moto buckets from pickle if os.path.isfile(moto_context_file) and os.path.getsize(moto_context_file) > 0: with file_lock(moto_context_file): with open( moto_context_file, "rb" ) as f: moto_context.backends["global"].buckets = pickle.load( f ) mocked_function = moto_context(func) retval = mocked_function(self, *args, **kwargs) with file_lock(moto_context_file): with open( moto_context_file, "wb" ) as f: pickle.dump(moto_context.backends["global"].buckets, f) moto_context.stop() return retval functools.update_wrapper(wrapper_func, func) wrapper_func.__wrapped__ = func return wrapper_func @dec_all_methods(pickled_moto_wrapper, prefix=None) class RemoteProvider(S3RemoteProvider): def __init__(self, *args, **kwargs): super(RemoteProvider, self).__init__(*args, **kwargs) @dec_all_methods(pickled_moto_wrapper, prefix=None) class RemoteObject(S3RemoteObject): """ This is a derivative of the S3 remote provider that mocks out boto-based S3 calls using the "moto" Python package. Only the initializer is different; it "uploads" the input test file to the moto-simulated bucket at the start. """ def __init__(self, *args, keep_local=False, provider=None, **kwargs): super(RemoteObject, self).__init__(*args, keep_local=keep_local, provider=provider, **kwargs) bucket_name = 'test-static-remote-bucket' test_files = ('test.txt', 'out1.txt', 'out2.txt') s3 = boto3.resource('s3') s3.create_bucket(Bucket=bucket_name) # "Upload" files that should be in S3 before tests... s3c = S3Helper() for test_file in test_files: if not s3c.exists_in_bucket(bucket_name, test_file): logger.debug("Pre-populating remote bucket {} with file {}".format( bucket_name, test_file)) s3c.upload_to_s3(bucket_name, test_file) def mtime(self): if self.s3_key == 'test.txt': logger.debug("test.txt is new") return float('inf') elif self.s3_key.startswith('out'): logger.debug("{} is old".format(self.s3_key)) # For some reason this breaks if you return 0 return 5 else: logger.debug("Using real mtime for {}".format(self.s3_key)) return super().mtime() # ====== Helpers ===== def touch(fname, mode=0o666, dir_fd=None, **kwargs): # create lock file faster # https://stackoverflow.com/a/1160227 flags = os.O_CREAT | os.O_APPEND with os.fdopen(os.open(fname, flags=flags, mode=mode, dir_fd=dir_fd)) as f: os.utime(f.fileno() if os.utime in os.supports_fd else fname, dir_fd=None if os.supports_fd else dir_fd, **kwargs) @contextmanager def file_lock(filepath): lock_file = filepath + ".lock" while os.path.isfile(lock_file): time.sleep(2) touch(lock_file) try: yield finally: if os.path.isfile(lock_file): os.remove(lock_file) snakemake-5.10.0/tests/test_static_remote/Snakefile000066400000000000000000000027461361131222100224240ustar00rootroot00000000000000#import re, os, sys from S3MockedForStaticTest import RemoteProvider as S3RemoteProvider S3 = S3RemoteProvider() # remote dynamic file test # This makes use of a special provider that mocks up S3 using the moto # library so that boto calls hit local "buckets" rule all: input: # only keeping the files so we can copy them out to the cwd S3.remote("test-static-remote-bucket/out1.txt", keep_local=True), S3.remote("test-static-remote-bucket/out2.txt", keep_local=True) run: shell("for f in {input}; do mv $f ./; done") # This rule should run rule run_no_static: input: S3.remote('test-static-remote-bucket/test.txt', static=False) output: S3.remote('test-static-remote-bucket/out1.txt'), run: shell('''echo '{input} > {output}'; cat {input} | tee {output}''') # This rule should NOT run because Snakemake should assume that the # input file is static and has not changed. rule run_static: input: S3.remote('test-static-remote-bucket/test.txt', static=True) output: S3.remote('test-static-remote-bucket/out2.txt'), run: shell('''echo '{input} > {output}'; cat {input} | tee {output}''') raise Exception("This rule should never run") # after we finish, we need to remove the pickle storing # the local moto "buckets" so we are starting fresh # next time this test is run. This file is created by # the moto wrapper defined in S3Mocked.py onsuccess: shell("rm ./motoState.p") onerror: shell("rm ./motoState.p") snakemake-5.10.0/tests/test_static_remote/__init__.py000066400000000000000000000000001361131222100226660ustar00rootroot00000000000000snakemake-5.10.0/tests/test_static_remote/expected-results/000077500000000000000000000000001361131222100240675ustar00rootroot00000000000000snakemake-5.10.0/tests/test_static_remote/expected-results/out1.txt000066400000000000000000000000661361131222100255220ustar00rootroot00000000000000This file should overwrite out1.txt but not out2.txt. snakemake-5.10.0/tests/test_static_remote/expected-results/out2.txt000066400000000000000000000000621361131222100255170ustar00rootroot00000000000000This file should not be overwritten by the input. snakemake-5.10.0/tests/test_static_remote/out1.txt000066400000000000000000000000421361131222100222140ustar00rootroot00000000000000This file should get overwritten. snakemake-5.10.0/tests/test_static_remote/out2.txt000066400000000000000000000000621361131222100222170ustar00rootroot00000000000000This file should not be overwritten by the input. snakemake-5.10.0/tests/test_static_remote/test.txt000066400000000000000000000000661361131222100223110ustar00rootroot00000000000000This file should overwrite out1.txt but not out2.txt. snakemake-5.10.0/tests/test_subworkflows/000077500000000000000000000000001361131222100204745ustar00rootroot00000000000000snakemake-5.10.0/tests/test_subworkflows/Snakefile000066400000000000000000000004541361131222100223230ustar00rootroot00000000000000import os.path subworkflow test02: workdir: config["subworkdir"] configfile: "subconfig.yaml" # test optional config files rule: input: "test.out" def test_in(wildcards): return test02("test.out") rule: input: test_in output: "test.out" shell: "cp {input} {output}" snakemake-5.10.0/tests/test_subworkflows/expected-results/000077500000000000000000000000001361131222100237745ustar00rootroot00000000000000snakemake-5.10.0/tests/test_subworkflows/expected-results/test.out000066400000000000000000000000101361131222100254730ustar00rootroot00000000000000testz0r snakemake-5.10.0/tests/test_subworkflows/subconfig.yaml000066400000000000000000000000171361131222100233350ustar00rootroot00000000000000test: "xy" snakemake-5.10.0/tests/test_symlink_temp/000077500000000000000000000000001361131222100204405ustar00rootroot00000000000000snakemake-5.10.0/tests/test_symlink_temp/Snakefile000066400000000000000000000011721361131222100222650ustar00rootroot00000000000000rule all: input: 'a.out', 'b.out' rule one: #the first rule in the work-flow input: '{sample}' output: temp('1.{sample}') shell: 'touch {output}' rule two: #this rule simply creates symbol link, following rule one input: '1.{sample}' output: temp('2.{sample}') shell: 'ln -s {input} {output}' rule three: #this rule simply creates symbol link, following rule two input: '2.{sample}' output: temp('3.{sample}') shell: 'ln -s {input} {output}' rule four: #this rule creates the final output, following rule three input: '3.{sample}' output: '{sample}.out' shell: 'touch {output}' snakemake-5.10.0/tests/test_symlink_temp/a000066400000000000000000000000001361131222100205710ustar00rootroot00000000000000snakemake-5.10.0/tests/test_symlink_temp/b000066400000000000000000000000001361131222100205720ustar00rootroot00000000000000snakemake-5.10.0/tests/test_symlink_temp/expected-results/000077500000000000000000000000001361131222100237405ustar00rootroot00000000000000snakemake-5.10.0/tests/test_symlink_temp/expected-results/.gitignore000066400000000000000000000000001361131222100257160ustar00rootroot00000000000000snakemake-5.10.0/tests/test_symlink_time_handling/000077500000000000000000000000001361131222100222755ustar00rootroot00000000000000snakemake-5.10.0/tests/test_symlink_time_handling/Snakefile000066400000000000000000000051201361131222100241170ustar00rootroot00000000000000# vim: ft=python """Snakemake should work where the input/output of a rule is a symlink, no problem. Here we test that updates to symlinks are recognised and that the timestamps on symlinks are updated properly. Unfortunately this does not work on some Python builds where os.supports_follow_symlinks does not include utime(). This includes the Miniconda build used on continuum.io. Therefore this test is an expected failure on those systems. In practise, the impact of the bug is low - lutime() on a link will just be a no-op and users will see a warning message. Anyone for whom this is a real problem should install a fully-working version of Python. """ """Description of the test: input_file is a file that is 1 hour old input_link is a link to input file that is 4 hours old output_link is a symlink to input_link that is 2 hours old So output_link needs to be re-evaluated since the contents of input_file changed. rule main outputs the time difference between inout and output in hours which can be checked by Nose to ensure output_link gets touched by Snakemake but neither input_file nor input_link are changed. """ import os import time #Slightly crude way to stop this running twice if not os.path.exists("input_file"): def timestr(hr_delta=0): return time.strftime("%Y%m%d%H%M", time.localtime(time.time() - (hr_delta * 3600) - 5)) shell("touch -t {} input_file".format(timestr(1))) shell("ln -s input_file input_link") shell("touch -h -t {} input_link".format(timestr(4))) shell("ln -s input_link output_link") shell("touch -h -t {} output_link".format(timestr(2))) shell("ls -lR > /dev/stderr") rule main: output: "time_diff.txt" input: "output_link" run: time_diff1 = int( ( os.stat("output_link", follow_symlinks=False).st_mtime - os.stat("input_link", follow_symlinks=False).st_mtime ) / (60*60) ) time_diff2 = int( ( os.stat("output_link", follow_symlinks=False).st_mtime - os.stat("input_file", follow_symlinks=False).st_mtime ) / (60*60) ) # I expect the result "4 1" shell("ls -lR > /dev/stderr") shell("echo {time_diff1} {time_diff2} | tee time_diff.txt 2>&1") rule make_output: output: "output_link" input: "input_link" run: #shell("rm -f {output}") - no longer necessary shell("ln -s {input} {output}") #This next command should be undone by Snakemake which now touches all outpout shell("touch -h -t 201604011600 {output}") snakemake-5.10.0/tests/test_symlink_time_handling/expected-results/000077500000000000000000000000001361131222100255755ustar00rootroot00000000000000snakemake-5.10.0/tests/test_symlink_time_handling/expected-results/time_diff.txt000066400000000000000000000000041361131222100302560ustar00rootroot000000000000004 1 snakemake-5.10.0/tests/test_temp/000077500000000000000000000000001361131222100166725ustar00rootroot00000000000000snakemake-5.10.0/tests/test_temp/Snakefile000066400000000000000000000011141361131222100205130ustar00rootroot00000000000000rule indelrealigner: input: bam="{base}.bam",intervals="{base}.intervals",bai='{base}.bam.bai' output: bam=temp("{base}.realigned.bam") params: batch="-q ccr -l nodes=1:gpfs" threads: 1 shell: "touch {output}" rule realignertargetcreator: input: "{base}.bam", "{base}.bam.bai" output: temp("{base}.intervals") params: batch="-q ccr -l nodes=1:gpfs" threads: 32 shell: "touch {output}" rule indexbam: threads: 1 input: '{base}.bam' output: temp('{base}.bam.bai') params: batch="-q ccr -l nodes=1:gpfs" shell: 'touch {output}' snakemake-5.10.0/tests/test_temp/expected-results/000077500000000000000000000000001361131222100221725ustar00rootroot00000000000000snakemake-5.10.0/tests/test_temp/expected-results/test.realigned.bam000066400000000000000000000000001361131222100255510ustar00rootroot00000000000000snakemake-5.10.0/tests/test_temp/qsub000077500000000000000000000001751361131222100175750ustar00rootroot00000000000000#!/bin/bash echo `date` >> qsub.log tail -n1 $1 >> qsub.log # simulate printing of job id by a random number echo $RANDOM $1 snakemake-5.10.0/tests/test_temp/test.bam000066400000000000000000000000001361131222100203200ustar00rootroot00000000000000snakemake-5.10.0/tests/test_temp_expand/000077500000000000000000000000001361131222100202315ustar00rootroot00000000000000snakemake-5.10.0/tests/test_temp_expand/Snakefile000066400000000000000000000003231361131222100220530ustar00rootroot00000000000000 rule: input: "a.txt" output: "test.txt" shell: "touch {output}" rule: output: temp(expand("{ds}.txt", ds="a b c".split())) shell: "touch {output}" snakemake-5.10.0/tests/test_temp_expand/expected-results/000077500000000000000000000000001361131222100235315ustar00rootroot00000000000000snakemake-5.10.0/tests/test_temp_expand/expected-results/test.txt000066400000000000000000000000001361131222100252370ustar00rootroot00000000000000snakemake-5.10.0/tests/test_threads/000077500000000000000000000000001361131222100173575ustar00rootroot00000000000000snakemake-5.10.0/tests/test_threads/Snakefile000066400000000000000000000002021361131222100211750ustar00rootroot00000000000000rule a: output: "test.out" threads: 20 run: print(threads) shell("echo {threads} > {output}") snakemake-5.10.0/tests/test_threads/expected-results/000077500000000000000000000000001361131222100226575ustar00rootroot00000000000000snakemake-5.10.0/tests/test_threads/expected-results/test.out000066400000000000000000000000031361131222100243600ustar00rootroot0000000000000020 snakemake-5.10.0/tests/test_threads0/000077500000000000000000000000001361131222100174375ustar00rootroot00000000000000snakemake-5.10.0/tests/test_threads0/Snakefile000066400000000000000000000001451361131222100212630ustar00rootroot00000000000000rule a: output: "test.out" threads: 0 shell: "echo {threads} > {output}" snakemake-5.10.0/tests/test_threads0/expected-results/000077500000000000000000000000001361131222100227375ustar00rootroot00000000000000snakemake-5.10.0/tests/test_threads0/expected-results/test.out000066400000000000000000000000021361131222100244370ustar00rootroot000000000000000 snakemake-5.10.0/tests/test_tibanna/000077500000000000000000000000001361131222100173415ustar00rootroot00000000000000snakemake-5.10.0/tests/test_tibanna/README.md000066400000000000000000000007351361131222100206250ustar00rootroot00000000000000``` # the following has been performed by aws admin already tibanna deploy_unicorn --usergroup=johannes --buckets=snakemake-tibanna-test,snakemake-tibanna-test2 ``` ``` # run the following to do a test run pip install -U tibanna python cleanup.py # first delete output files that are already on s3 export TIBANNA_DEFAULT_STEP_FUNCTION_NAME=tibanna_unicorn_johannes snakemake --tibanna --use-conda --configfile=config.json --default-remote-prefix=snakemake-tibanna-test/1 ``` snakemake-5.10.0/tests/test_tibanna/Snakefile000066400000000000000000000035561361131222100211760ustar00rootroot00000000000000# vim: syntax=python # # step1 and step1a are grouped. step1b must run concurrently with step1+step1a. # step2 waits for step1, step1a and step1b to finish. # all is the final rule. # step1, step1a and step1b use a conda environment. # Input of step1, step1b and all are set remote. # Output of step2 is set remote. from snakemake.remote.S3 import RemoteProvider as S3RemoteProvider S3 = S3RemoteProvider() rule all: input: final = S3.remote("snakemake-tibanna-test/1/final_message"), # final = "snakemake-tibanna-test/1/final_message" final2 = S3.remote("snakemake-tibanna-test2/1/final_message") rule step1: conda: "env.yml" group: "mygroup" input: S3.remote("snakemake-tibanna-test/1/somefile") output: message = "message1" shell: """ echo {config[message]} > message1 cat snakemake-tibanna-test/1/somefile >> message1 """ rule step1a: conda: "env.yml" group: "mygroup" input: message = "message1" output: next_message = "next_message" shell: """ cat message1 message1 > next_message """ rule step1b: conda: "env.yml" input: S3.remote("snakemake-tibanna-test/1/somefile2") output: message = "message2" log: "log.txt" benchmark: "benchmark.txt" threads: 1 resources: mem_mb=1024 shell: """ echo "abcdefg" > message2 cat snakemake-tibanna-test/1/somefile2 >> message2 """ rule step2: input: message1 = "next_message", message2 = "message2" output: final = S3.remote("snakemake-tibanna-test/1/final_message"), # final = "snakemake-tibanna-test/1/final_message" final2 = S3.remote("snakemake-tibanna-test2/1/final_message") script: "scripts/step2.py" snakemake-5.10.0/tests/test_tibanna/cleanup.py000066400000000000000000000011501361131222100213370ustar00rootroot00000000000000import subprocess import boto3 # clean up local subprocess.call(['rm', '-rf', '.snakemake']) subprocess.call(['rm', '-rf', 'snakemake-tibanna-test']) # clean up s3 s3 = boto3.client('s3') s3.delete_objects(Bucket='snakemake-tibanna-test', Delete={'Objects': [{'Key': '1/message1'}, {'Key': '1/message2'}, {'Key': '1/next_message'}, {'Key': '1/final_message'}]}) s3.delete_objects(Bucket='snakemake-tibanna-test2', Delete={'Objects': [{'Key': '1/final_message'}]}) snakemake-5.10.0/tests/test_tibanna/config.json000066400000000000000000000000271361131222100215000ustar00rootroot00000000000000{"message": "hahaha"} snakemake-5.10.0/tests/test_tibanna/env.yml000066400000000000000000000000751361131222100206560ustar00rootroot00000000000000name: pairix channels: - bioconda dependencies: - pairix snakemake-5.10.0/tests/test_tibanna/expected-results/000077500000000000000000000000001361131222100226415ustar00rootroot00000000000000snakemake-5.10.0/tests/test_tibanna/expected-results/.gitkeep000066400000000000000000000000011361131222100242610ustar00rootroot00000000000000 snakemake-5.10.0/tests/test_tibanna/scripts/000077500000000000000000000000001361131222100210305ustar00rootroot00000000000000snakemake-5.10.0/tests/test_tibanna/scripts/step2.py000066400000000000000000000002331361131222100224350ustar00rootroot00000000000000from shutil import copyfile copyfile("message2", "snakemake-tibanna-test/1/final_message") copyfile("message2", "snakemake-tibanna-test2/1/final_message") snakemake-5.10.0/tests/test_touch/000077500000000000000000000000001361131222100170475ustar00rootroot00000000000000snakemake-5.10.0/tests/test_touch/Snakefile000066400000000000000000000001101361131222100206630ustar00rootroot00000000000000rule: output: touch("test.out") shell: "exit 0" snakemake-5.10.0/tests/test_touch/expected-results/000077500000000000000000000000001361131222100223475ustar00rootroot00000000000000snakemake-5.10.0/tests/test_touch/expected-results/test.out000066400000000000000000000000001361131222100240450ustar00rootroot00000000000000snakemake-5.10.0/tests/test_unpack_dict/000077500000000000000000000000001361131222100202115ustar00rootroot00000000000000snakemake-5.10.0/tests/test_unpack_dict/Snakefile000066400000000000000000000010511361131222100220320ustar00rootroot00000000000000rule all: input: 'prefix.out1.txt', 'prefix.out2.txt', def get_in(wildcards): result = {'one': '{wildcards.prefix}.in1.txt', 'two': '{wildcards.prefix}.in2.txt'} return {key: value.format(wildcards=wildcards) for key, value in result.items()} def get_out(): return {'one': '{prefix}.out1.txt', 'two': '{prefix}.out2.txt'} rule copy_files: input: unpack(get_in) output: **get_out() shell: r""" cp {input.one} {output.one} cp {input.two} {output.two} """ snakemake-5.10.0/tests/test_unpack_dict/expected-results/000077500000000000000000000000001361131222100235115ustar00rootroot00000000000000snakemake-5.10.0/tests/test_unpack_dict/expected-results/prefix.out1.txt000066400000000000000000000000021361131222100264260ustar00rootroot000000000000001 snakemake-5.10.0/tests/test_unpack_dict/expected-results/prefix.out2.txt000066400000000000000000000000021361131222100264270ustar00rootroot000000000000002 snakemake-5.10.0/tests/test_unpack_dict/prefix.in1.txt000066400000000000000000000000021361131222100227250ustar00rootroot000000000000001 snakemake-5.10.0/tests/test_unpack_dict/prefix.in2.txt000066400000000000000000000000021361131222100227260ustar00rootroot000000000000002 snakemake-5.10.0/tests/test_unpack_list/000077500000000000000000000000001361131222100202415ustar00rootroot00000000000000snakemake-5.10.0/tests/test_unpack_list/Snakefile000066400000000000000000000007561361131222100220750ustar00rootroot00000000000000rule all: input: 'prefix.out1.txt', 'prefix.out2.txt', def get_in(wildcards): result = ['{wildcards.prefix}.in1.txt', '{wildcards.prefix}.in2.txt'] return [x.format(wildcards=wildcards) for x in result] def get_out(): return ['{prefix}.out1.txt', '{prefix}.out2.txt'] rule copy_files: input: unpack(get_in) output: *get_out() shell: r""" cp {input[0]} {output[0]} cp {input[1]} {output[1]} """ snakemake-5.10.0/tests/test_unpack_list/expected-results/000077500000000000000000000000001361131222100235415ustar00rootroot00000000000000snakemake-5.10.0/tests/test_unpack_list/expected-results/prefix.out1.txt000066400000000000000000000000021361131222100264560ustar00rootroot000000000000001 snakemake-5.10.0/tests/test_unpack_list/expected-results/prefix.out2.txt000066400000000000000000000000021361131222100264570ustar00rootroot000000000000002 snakemake-5.10.0/tests/test_unpack_list/prefix.in1.txt000066400000000000000000000000021361131222100227550ustar00rootroot000000000000001 snakemake-5.10.0/tests/test_unpack_list/prefix.in2.txt000066400000000000000000000000021361131222100227560ustar00rootroot000000000000002 snakemake-5.10.0/tests/test_until/000077500000000000000000000000001361131222100170605ustar00rootroot00000000000000snakemake-5.10.0/tests/test_until/Snakefile000066400000000000000000000023201361131222100207010ustar00rootroot00000000000000 rule all: input: "levelthree.txt", "independent.txt", expand("test{num}.final", num=[1, 2]) rule levelone: output: "levelone.txt" shell: "touch {output}" rule leveltwo_first: input: rules.levelone.output output: "leveltwo_first.txt" shell: "cp -f {input} {output}" rule leveltwo_second: input: rules.levelone.output output: "leveltwo_second.txt" shell: "cp -f {input} {output}" rule levelthree: # should not be created input: rules.leveltwo_first.output, rules.leveltwo_second.output output: "levelthree.txt" shell: "cat {input} > {output}" rule independent: # should be created in --omit-from but not --until output: "independent.txt" shell: "touch {output}" ###### Wildcard Rules ####### rule zeroth_wildcard: output: "test{num}.txt" shell: "touch {output}" rule first_wildcard: input: 'test{num}.txt' output: 'test{num}.first' shell: 'cp -f {input} {output}' rule second_wildcard: input: 'test{num}.first' output: 'test{num}.second' shell: 'cp -f {input} {output}' rule final_wildcard: input: 'test{num}.second' output: 'test{num}.final' shell: 'cp -f {input} {output}' snakemake-5.10.0/tests/test_until/expected-results/000077500000000000000000000000001361131222100223605ustar00rootroot00000000000000snakemake-5.10.0/tests/test_until/expected-results/levelone.txt000066400000000000000000000000001361131222100247200ustar00rootroot00000000000000snakemake-5.10.0/tests/test_until/expected-results/leveltwo_first.txt000066400000000000000000000000001361131222100261570ustar00rootroot00000000000000snakemake-5.10.0/tests/test_until/expected-results/leveltwo_second.txt000066400000000000000000000000001361131222100263030ustar00rootroot00000000000000snakemake-5.10.0/tests/test_until/expected-results/test1.second000066400000000000000000000000001361131222100246030ustar00rootroot00000000000000snakemake-5.10.0/tests/test_until/expected-results/test2.second000066400000000000000000000000001361131222100246040ustar00rootroot00000000000000snakemake-5.10.0/tests/test_update_config/000077500000000000000000000000001361131222100205345ustar00rootroot00000000000000snakemake-5.10.0/tests/test_update_config/Snakefile000066400000000000000000000004211361131222100223550ustar00rootroot00000000000000import yaml include: "echo.rule" include: "cp.rule" configfile: "test.yaml" rule all: input: "test.out.copy" output: yaml = "config.yaml" run: with open(str(output.yaml), "w") as fh: fh.write(yaml.dump(config, default_flow_style=False)) snakemake-5.10.0/tests/test_update_config/cp.rule000066400000000000000000000005041361131222100220260ustar00rootroot00000000000000# -*- snakemake -*- from snakemake.utils import update_config c = { 'cp': { 'options': '-f', }, } update_config(config, c) rule cp: params: options = config['cp']['options'] input: '{prefix}.out' output: temporary('{prefix}.out.copy') shell: 'cp {params.options} {input} {output}' snakemake-5.10.0/tests/test_update_config/echo.rule000066400000000000000000000002761361131222100223500ustar00rootroot00000000000000# -*- snakemake -*- configfile: 'echo.yaml' rule echo: params: options = config['echo']['options'] output: temporary('{prefix}.out') shell: 'echo "{params.options}" > {output}' snakemake-5.10.0/tests/test_update_config/echo.yaml000066400000000000000000000000241361131222100223320ustar00rootroot00000000000000echo: options: '' snakemake-5.10.0/tests/test_update_config/expected-results/000077500000000000000000000000001361131222100240345ustar00rootroot00000000000000snakemake-5.10.0/tests/test_update_config/expected-results/config.yaml000066400000000000000000000000501361131222100261600ustar00rootroot00000000000000cp: options: -u echo: options: echo snakemake-5.10.0/tests/test_update_config/test.yaml000066400000000000000000000000501361131222100223720ustar00rootroot00000000000000cp: options: -u echo: options: echo snakemake-5.10.0/tests/test_url_include/000077500000000000000000000000001361131222100202325ustar00rootroot00000000000000snakemake-5.10.0/tests/test_url_include/Snakefile000066400000000000000000000001701361131222100220540ustar00rootroot00000000000000 include: "https://github.com/snakemake/snakemake/raw/master/tests/test05/Snakefile" rule: input: "test.predictions" snakemake-5.10.0/tests/test_url_include/expected-results/000077500000000000000000000000001361131222100235325ustar00rootroot00000000000000snakemake-5.10.0/tests/test_url_include/expected-results/test.1.inter000066400000000000000000000000321361131222100257060ustar00rootroot00000000000000testz0r Part test.1.inter snakemake-5.10.0/tests/test_url_include/expected-results/test.1.inter2000066400000000000000000000000321361131222100257700ustar00rootroot00000000000000testz0r Part test.1.inter snakemake-5.10.0/tests/test_url_include/expected-results/test.2.inter000066400000000000000000000000321361131222100257070ustar00rootroot00000000000000testz0r Part test.2.inter snakemake-5.10.0/tests/test_url_include/expected-results/test.2.inter2000066400000000000000000000000321361131222100257710ustar00rootroot00000000000000testz0r Part test.2.inter snakemake-5.10.0/tests/test_url_include/expected-results/test.3.inter000066400000000000000000000000321361131222100257100ustar00rootroot00000000000000testz0r Part test.3.inter snakemake-5.10.0/tests/test_url_include/expected-results/test.3.inter2000066400000000000000000000000321361131222100257720ustar00rootroot00000000000000testz0r Part test.3.inter snakemake-5.10.0/tests/test_url_include/expected-results/test.predictions000066400000000000000000000001161361131222100267540ustar00rootroot00000000000000testz0r Part test.1.inter testz0r Part test.2.inter testz0r Part test.3.inter snakemake-5.10.0/tests/test_url_include/test.in000066400000000000000000000000101361131222100215300ustar00rootroot00000000000000testz0r snakemake-5.10.0/tests/test_validate/000077500000000000000000000000001361131222100175165ustar00rootroot00000000000000snakemake-5.10.0/tests/test_validate/Snakefile000066400000000000000000000006301361131222100213410ustar00rootroot00000000000000import pandas as pd from snakemake.utils import validate configfile: "config.yaml" validate(config, "config.schema.yaml") samples = pd.read_table(config["samples"]).set_index("sample", drop=False) validate(samples, "samples.schema.yaml") rule all: input: expand("test.{sample}.txt", sample=samples.index) rule a: output: "test.{sample}.txt" shell: "touch {output}" snakemake-5.10.0/tests/test_validate/config.fail.yaml000066400000000000000000000000441361131222100225570ustar00rootroot00000000000000samples: samples.tsv adapter: ACGTX snakemake-5.10.0/tests/test_validate/config.schema.yaml000066400000000000000000000003411361131222100231040ustar00rootroot00000000000000$schema: "http://json-schema.org/draft-06/schema#" description: snakemake configuration file type: object properties: samples: type: string adapter: type: string pattern: "^[ACGT]+$" required: - samples snakemake-5.10.0/tests/test_validate/config.yaml000066400000000000000000000000431361131222100216440ustar00rootroot00000000000000samples: samples.tsv adapter: ACGT snakemake-5.10.0/tests/test_validate/expected-results/000077500000000000000000000000001361131222100230165ustar00rootroot00000000000000snakemake-5.10.0/tests/test_validate/expected-results/test.A.txt000066400000000000000000000000001361131222100247030ustar00rootroot00000000000000snakemake-5.10.0/tests/test_validate/expected-results/test.B.txt000066400000000000000000000000001361131222100247040ustar00rootroot00000000000000snakemake-5.10.0/tests/test_validate/samples.schema.yaml000066400000000000000000000005741361131222100233130ustar00rootroot00000000000000$schema: "https://json-schema.org/draft-06/schema#" description: an entry in the sample sheet properties: sample: type: string description: sample name/identifier condition: type: string description: sample condition that will be compared during differential expression analysis (e.g. a treatment, a tissue time, a disease) required: - sample - condition snakemake-5.10.0/tests/test_validate/samples.tsv000066400000000000000000000000411361131222100217130ustar00rootroot00000000000000sample condition A tumor B blood snakemake-5.10.0/tests/test_wildcard_count_ambiguity/000077500000000000000000000000001361131222100230005ustar00rootroot00000000000000snakemake-5.10.0/tests/test_wildcard_count_ambiguity/Snakefile000066400000000000000000000002401361131222100246200ustar00rootroot00000000000000 rule all: input: "test.out" rule a: output: "{prefix}.out" shell: "touch {output}" rule b: output: "test.out" shell: "touch {output}" snakemake-5.10.0/tests/test_wildcard_count_ambiguity/expected-results/000077500000000000000000000000001361131222100263005ustar00rootroot00000000000000snakemake-5.10.0/tests/test_wildcard_count_ambiguity/expected-results/test.out000066400000000000000000000000001361131222100277760ustar00rootroot00000000000000snakemake-5.10.0/tests/test_wildcard_keyword/000077500000000000000000000000001361131222100212625ustar00rootroot00000000000000snakemake-5.10.0/tests/test_wildcard_keyword/Snakefile000066400000000000000000000021301361131222100231020ustar00rootroot00000000000000 rule all: input: "stringbar.txt", "localbar.txt", "globalbar.txt", "ambig.u.ous.log" ##: NB: setting output: "{foo}.in" only works for globalwildcard rule ## since constraints will be set to "globalbar" rule infile: output: temp("{foo,(globalbar|localbar|stringbar)}.in") shell: "touch {output}" rule stringwildcard: input: "{foo}.in" output: "{foo,stringbar}.txt" log: "{foo}.log" shell: "echo {input} {output} {log} > {output}; touch {log}" rule localwildcard: input: "{foo}.in" output: "{foo}.txt" wildcard_constraints: foo="localbar" log: "{foo}.log" shell: "echo {input} {output} {log} > {output}; touch {log}" rule globalwildcard: input: "{foo}.in" output: "{foo}.txt" log: "{foo}.log" shell: "echo {input} {output} {log} > {output}; touch {log}" rule ambigouslog: output: "{foo}.{bar}.txt" log: "{foo}.{bar}.log" wildcard_constraints: foo="ambig", bar=".+" shell: "echo a={wildcards.foo} b={wildcards.bar} > {output}; touch {log}" wildcard_constraints: foo='globalbar', bar='out/{SM,[a-z]+}_{PU,[0-9]+}' snakemake-5.10.0/tests/test_wildcard_keyword/expected-results/000077500000000000000000000000001361131222100245625ustar00rootroot00000000000000snakemake-5.10.0/tests/test_wildcard_keyword/expected-results/ambig.u.ous.txt000066400000000000000000000000201361131222100274420ustar00rootroot00000000000000a=ambig b=u.ous snakemake-5.10.0/tests/test_wildcard_keyword/expected-results/globalbar.log000066400000000000000000000000001361131222100272000ustar00rootroot00000000000000snakemake-5.10.0/tests/test_wildcard_keyword/expected-results/globalbar.txt000066400000000000000000000000511361131222100272440ustar00rootroot00000000000000globalbar.in globalbar.txt globalbar.log snakemake-5.10.0/tests/test_wildcard_keyword/expected-results/localbar.log000066400000000000000000000000001361131222100270320ustar00rootroot00000000000000snakemake-5.10.0/tests/test_wildcard_keyword/expected-results/localbar.txt000066400000000000000000000000461361131222100271020ustar00rootroot00000000000000localbar.in localbar.txt localbar.log snakemake-5.10.0/tests/test_wildcard_keyword/expected-results/stringbar.log000066400000000000000000000000001361131222100272460ustar00rootroot00000000000000snakemake-5.10.0/tests/test_wildcard_keyword/expected-results/stringbar.txt000066400000000000000000000000511361131222100273120ustar00rootroot00000000000000stringbar.in stringbar.txt stringbar.log snakemake-5.10.0/tests/test_wrapper/000077500000000000000000000000001361131222100174055ustar00rootroot00000000000000snakemake-5.10.0/tests/test_wrapper/Snakefile000066400000000000000000000002021361131222100212230ustar00rootroot00000000000000rule compress_vcf: input: "test.vcf" output: "test.vcf.gz" wrapper: "0.42.0/bio/vcf/compress" snakemake-5.10.0/tests/test_wrapper/expected-results/000077500000000000000000000000001361131222100227055ustar00rootroot00000000000000snakemake-5.10.0/tests/test_wrapper/expected-results/test.vcf.gz000066400000000000000000000006671361131222100250140ustar00rootroot00000000000000BCMO@W4bB.˂ޫ" .\0%ayfaIzˌ5{áޝ[WZ8N4ќeoix$D/Y<Ⱥq^V&C }~9vAne8aqf{^G9'"KWeRQr*uE0TG3{mVxa`/}xz@ݥ؁H)Hbg 8Q'fHT lP`k{xh7tN)(cp|gAAsA+Y&l:9MMM6~6m"ۓN[*liԢ*5!jBZbZe+|)BօsPLvfq 3 nn `6)+~WBCsnakemake-5.10.0/tests/test_wrapper/test.vcf000066400000000000000000000021271361131222100210660ustar00rootroot00000000000000##fileformat=VCFv4.1 ##INFO= ##INFO= ##INFO= ##FORMAT= ##FORMAT= ##FORMAT= ##FORMAT= #CHROM POS ID REF ALT QUAL FILTER INFO FORMAT one two 19 3111939 rs1234 A AG . PASS S1=string1;N1=1;F1=1.0 GT:FS1:FN1 ./1:LongString1:1 1/1:ss1:2 19 3113255 rs2345 G GC . PASS S1=string2;N1=2;F1=2.0 GT:FS1:FN1 1|1:LongString2:1 1/1:ss2:2 19 3113259 rs2345 G GC . PASS S1=string3;N1=3;F1=3.0 GT:FS1:FN1 0/1:.:1 1/1:ss3:2 19 3113262 rs2345 G GC . PASS S1=string4;N1=4;F1=4.0 GT:FS1:FN1 0|1:LongString4:1 1/1:.:2 19 3113268 rs2345 G GC . PASS S1=string5;N1=5;F1=5.0 GT:FS1:FN1 1|.:evenlength:1 1/1:veenlength:2 19 3113272 rs2345 G GC . PASS S1=string6;N1=6;F1=6.0 GT:FS1:FN1 1/1:ss6:1 1/1:longstring6:2 snakemake-5.10.0/tests/test_xrootd/000077500000000000000000000000001361131222100172445ustar00rootroot00000000000000snakemake-5.10.0/tests/test_xrootd/Snakefile000066400000000000000000000016511361131222100210730ustar00rootroot00000000000000from snakemake.remote.XRootD import RemoteProvider as XRootDRemoteProvider XRootD = XRootDRemoteProvider(stay_on_remote=True) remote_path = 'root://eospublic.cern.ch//eos/opendata/lhcb/MasterclassDatasets/' my_files, = XRootD.glob_wildcards(remote_path+'D0lifetime/2014/mclasseventv2_D0_{n}.root') rule all: input: expand('access_remotely/mclasseventv2_D0_{n}.root', n=my_files), expand('access_locally/mclasseventv2_D0_{n}.root', n=my_files) rule access_remotely: input: XRootD.remote(remote_path+'D0lifetime/2014/mclasseventv2_D0_{n}.root') output: 'access_remotely/mclasseventv2_D0_{n}.root' shell: 'xrdcp {input[0]} {output[0]}' rule access_locally: input: XRootD.remote(remote_path+'D0lifetime/2014/mclasseventv2_D0_{n}.root', stay_on_remote=False) output: 'access_locally/mclasseventv2_D0_{n}.root' shell: 'cp {input[0]} {output[0]}' snakemake-5.10.0/tests/test_yaml_config/000077500000000000000000000000001361131222100202145ustar00rootroot00000000000000snakemake-5.10.0/tests/test_yaml_config/Snakefile000066400000000000000000000001531361131222100220370ustar00rootroot00000000000000 configfile: "test.yaml" rule: output: config["outfile"] shell: "touch {output}" snakemake-5.10.0/tests/test_yaml_config/expected-results/000077500000000000000000000000001361131222100235145ustar00rootroot00000000000000snakemake-5.10.0/tests/test_yaml_config/expected-results/test.out000066400000000000000000000000001361131222100252120ustar00rootroot00000000000000snakemake-5.10.0/tests/test_yaml_config/test.yaml000066400000000000000000000000251361131222100220540ustar00rootroot00000000000000--- outfile: test.outsnakemake-5.10.0/tests/testapi.py000066400000000000000000000017231361131222100167140ustar00rootroot00000000000000""" Tests for Snakemake’s API """ from snakemake import snakemake import tempfile import os.path from textwrap import dedent def test_keep_logger(): with tempfile.TemporaryDirectory() as tmpdir: path = os.path.join(tmpdir, "Snakefile") with open(path, "w") as f: print("rule:\n output: 'result.txt'\n shell: 'touch {output}'", file=f) snakemake(path, workdir=tmpdir, keep_logger=True) def test_run_script_directive(): with tempfile.TemporaryDirectory() as tmpdir: path = os.path.join(tmpdir, "Snakefile") with open(path, "w") as f: print( dedent( """ rule: output: 'result.txt' run: with open(output[0], 'w') as f: print("hello", file=f) """ ), file=f, ) snakemake(path, workdir=tmpdir) snakemake-5.10.0/tests/tests.py000066400000000000000000000645651361131222100164220ustar00rootroot00000000000000__authors__ = ["Tobias Marschall", "Marcel Martin", "Johannes Köster"] __copyright__ = "Copyright 2015-2019, Johannes Köster" __email__ = "koester@jimmy.harvard.edu" __license__ = "MIT" import sys import os import shutil from os.path import join from subprocess import call import tempfile import hashlib import urllib from shutil import rmtree, which from shlex import quote import pytest import subprocess from snakemake import snakemake from snakemake.shell import shell def dpath(path): """get path to a data file (relative to the directory this test lives in)""" return os.path.realpath(join(os.path.dirname(__file__), path)) def md5sum(filename): data = open(filename, "rb").read() return hashlib.md5(data).hexdigest() # test skipping def is_connected(): try: urllib.request.urlopen("http://www.google.com", timeout=1) return True except urllib.request.URLError: return False def is_ci(): return "CI" in os.environ def has_gcloud_service_key(): return "GCLOUD_SERVICE_KEY" in os.environ def has_gcloud_cluster(): return "GCLOUD_CLUSTER" in os.environ gcloud = pytest.mark.skipif( not is_connected() or not has_gcloud_service_key() or not has_gcloud_cluster(), reason="Skipping GCLOUD tests because not on " "CI, no inet connection or not logged " "in to gcloud.", ) connected = pytest.mark.skipif(not is_connected(), reason="no internet connection") ci = pytest.mark.skipif(not is_ci(), reason="not in CI") not_ci = pytest.mark.skipif(is_ci(), reason="skipped in CI") def copy(src, dst): if os.path.isdir(src): shutil.copytree(src, os.path.join(dst, os.path.basename(src))) else: shutil.copy(src, dst) def run( path, shouldfail=False, snakefile="Snakefile", subpath=None, no_tmpdir=False, check_md5=True, cores=3, set_pythonpath=True, cleanup=True, **params ): """ Test the Snakefile in path. There must be a Snakefile in the path and a subdirectory named expected-results. If cleanup is False, we return the temporary directory to the calling test for inspection, and the test should clean it up. """ if set_pythonpath: # Enforce current workdir (the snakemake source dir) to also be in PYTHONPATH # when subprocesses are invoked in the tempdir defined below. os.environ["PYTHONPATH"] = os.getcwd() elif "PYTHONPATH" in os.environ: del os.environ["PYTHONPATH"] results_dir = join(path, "expected-results") snakefile = join(path, snakefile) assert os.path.exists(snakefile) assert os.path.exists(results_dir) and os.path.isdir( results_dir ), "{} does not exist".format(results_dir) # If we need to further check results, we won't cleanup tmpdir tmpdir = next(tempfile._get_candidate_names()) tmpdir = os.path.join(tempfile.gettempdir(), "snakemake-%s" % tmpdir) os.mkdir(tmpdir) config = {} # handle subworkflow if subpath is not None: # set up a working directory for the subworkflow and pass it in `config` # for now, only one subworkflow is supported assert os.path.exists(subpath) and os.path.isdir( subpath ), "{} does not exist".format(subpath) subworkdir = os.path.join(tmpdir, "subworkdir") os.mkdir(subworkdir) # copy files for f in os.listdir(subpath): copy(os.path.join(subpath, f), subworkdir) config["subworkdir"] = subworkdir # copy files for f in os.listdir(path): print(f) copy(os.path.join(path, f), tmpdir) # run snakemake success = snakemake( snakefile, cores=cores, workdir=path if no_tmpdir else tmpdir, stats="stats.txt", config=config, verbose=True, **params ) if shouldfail: assert not success, "expected error on execution" else: assert success, "expected successful execution" for resultfile in os.listdir(results_dir): if resultfile in [".gitignore", ".gitkeep"] or not os.path.isfile( os.path.join(results_dir, resultfile) ): # this means tests cannot use directories as output files continue targetfile = join(tmpdir, resultfile) expectedfile = join(results_dir, resultfile) assert os.path.exists(targetfile), 'expected file "{}" not produced'.format( resultfile ) if check_md5: # if md5sum(targetfile) != md5sum(expectedfile): # import pdb; pdb.set_trace() if md5sum(targetfile) != md5sum(expectedfile): with open(targetfile) as target: content = target.read() assert False, 'wrong result produced for file "{}":\n{}'.format( resultfile, content ) if not cleanup: return tmpdir shutil.rmtree(tmpdir) def test_list_untracked(): run(dpath("test_list_untracked")) def test_delete_all_output(): run(dpath("test_delete_all_output")) def test_github_issue_14(): """Add cleanup_scripts argument to allow the user to keep scripts""" # Return temporary directory for inspection - we should keep scripts here tmpdir = run(dpath("test_github_issue_14"), cleanup=False, cleanup_scripts=False) assert os.listdir(os.path.join(tmpdir, ".snakemake", "scripts")) shutil.rmtree(tmpdir) # And not here tmpdir = run(dpath("test_github_issue_14"), cleanup=False) assert not os.listdir(os.path.join(tmpdir, ".snakemake", "scripts")) shutil.rmtree(tmpdir) def test_issue956(): run(dpath("test_issue956")) def test01(): run(dpath("test01")) def test02(): run(dpath("test02")) def test03(): run(dpath("test03"), targets=["test.out"]) def test04(): run(dpath("test04"), targets=["test.out"]) def test05(): run(dpath("test05")) def test06(): run(dpath("test06"), targets=["test.bla.out"]) def test07(): run(dpath("test07"), targets=["test.out", "test2.out"]) def test08(): run(dpath("test08"), targets=["test.out", "test2.out"]) def test09(): run(dpath("test09"), shouldfail=True) def test10(): run(dpath("test10")) def test11(): run(dpath("test11")) def test12(): run(dpath("test12")) def test13(): run(dpath("test13")) def test14(): run(dpath("test14"), snakefile="Snakefile.nonstandard", cluster="./qsub") def test15(): run(dpath("test15")) def test_directory(): run( dpath("test_directory"), targets=[ "downstream", "symlinked_input", "child_to_input", "some/dir-child", "some/shadow", ], ) run(dpath("test_directory"), targets=["file_expecting_dir"], shouldfail=True) run(dpath("test_directory"), targets=["dir_expecting_file"], shouldfail=True) run(dpath("test_directory"), targets=["child_to_other"], shouldfail=True) def test_ancient(): run(dpath("test_ancient"), targets=["D", "old_file"]) def test_report(): run(dpath("test_report"), report="report.html", check_md5=False) def test_dynamic(): run(dpath("test_dynamic")) def test_params(): run(dpath("test_params")) def test_same_wildcard(): run(dpath("test_same_wildcard")) def test_conditional(): run( dpath("test_conditional"), targets="test.out test.0.out test.1.out test.2.out".split(), ) def test_unpack_dict(): run(dpath("test_unpack_dict")) def test_unpack_list(): run(dpath("test_unpack_list")) def test_shell(): run(dpath("test_shell")) def test_temp(): run(dpath("test_temp"), cluster="./qsub", targets="test.realigned.bam".split()) def test_keyword_list(): run(dpath("test_keyword_list")) def test_subworkflows(): run(dpath("test_subworkflows"), subpath=dpath("test02")) def test_globwildcards(): run(dpath("test_globwildcards")) def test_local_import(): run(dpath("test_local_import")) def test_ruledeps(): run(dpath("test_ruledeps")) def test_persistent_dict(): try: import pytools run(dpath("test_persistent_dict")) except ImportError: pass @connected def test_url_include(): run(dpath("test_url_include")) def test_touch(): run(dpath("test_touch")) def test_config(): run(dpath("test_config")) def test_update_config(): run(dpath("test_update_config")) def test_wildcard_keyword(): run(dpath("test_wildcard_keyword")) def test_benchmark(): run(dpath("test_benchmark"), check_md5=False) def test_temp_expand(): run(dpath("test_temp_expand")) def test_wildcard_count_ambiguity(): run(dpath("test_wildcard_count_ambiguity")) def test_srcdir(): run(dpath("test_srcdir")) def test_multiple_includes(): run(dpath("test_multiple_includes")) def test_yaml_config(): run(dpath("test_yaml_config")) def test_remote(): run(dpath("test_remote"), cores=1) def test_cluster_sync(): run(dpath("test14"), snakefile="Snakefile.nonstandard", cluster_sync="./qsub") @pytest.mark.skip(reason="This does not work reliably in CircleCI.") def test_symlink_temp(): run(dpath("test_symlink_temp"), shouldfail=True) def test_empty_include(): run(dpath("test_empty_include")) def test_script(): run(dpath("test_script"), use_conda=True) def test_shadow(): run(dpath("test_shadow")) def test_shadow_prefix(): run(dpath("test_shadow_prefix"), shadow_prefix="shadowdir") run(dpath("test_shadow_prefix"), shadow_prefix="shadowdir", cluster="./qsub") def test_until(): run( dpath("test_until"), until=[ "leveltwo_first", # rule name "leveltwo_second.txt", # file name "second_wildcard", ], ) # wildcard rule def test_omitfrom(): run( dpath("test_omitfrom"), omit_from=[ "leveltwo_first", # rule name "leveltwo_second.txt", # file name "second_wildcard", ], ) # wildcard rule def test_nonstr_params(): run(dpath("test_nonstr_params")) def test_delete_output(): run(dpath("test_delete_output"), cores=1) def test_input_generator(): run(dpath("test_input_generator")) def test_symlink_time_handling(): # See Snakefile for notes on why this fails on some systems if os.utime in os.supports_follow_symlinks: run(dpath("test_symlink_time_handling")) def test_protected_symlink_output(): run(dpath("test_protected_symlink_output")) def test_issue328(): try: import pytools run(dpath("test_issue328"), forcerun=["split"]) except ImportError: # skip test if import fails pass def test_conda(): if conda_available(): run(dpath("test_conda"), use_conda=True) def test_conda_custom_prefix(): if conda_available(): run( dpath("test_conda_custom_prefix"), use_conda=True, conda_prefix="custom", set_pythonpath=False, ) def test_wrapper(): if conda_available(): run(dpath("test_wrapper"), use_conda=True) def conda_available(): return which("conda") def test_get_log_none(): run(dpath("test_get_log_none")) def test_get_log_both(): run(dpath("test_get_log_both")) def test_get_log_stderr(): run(dpath("test_get_log_stderr")) def test_get_log_stdout(): run(dpath("test_get_log_stdout")) def test_get_log_complex(): run(dpath("test_get_log_complex")) def test_spaces_in_fnames(): run( dpath("test_spaces_in_fnames"), # cluster="./qsub", targets=["test bam file realigned.bam"], printshellcmds=True, ) # TODO deactivate because of problems with moto and boto3. # def test_static_remote(): # import importlib # try: # importlib.reload(boto3) # importlib.reload(moto) # # only run the remote file test if the dependencies # # are installed, otherwise do nothing # run(dpath("test_static_remote"), cores=1) # except ImportError: # pass @connected def test_remote_ncbi_simple(): try: import Bio # only run the remote file test if the dependencies # are installed, otherwise do nothing run(dpath("test_remote_ncbi_simple")) except ImportError: pass @connected def test_remote_ncbi(): try: import Bio # only run the remote file test if the dependencies # are installed, otherwise do nothing run(dpath("test_remote_ncbi")) except ImportError: pass @ci def test_remote_irods(): run(dpath("test_remote_irods")) def test_deferred_func_eval(): run(dpath("test_deferred_func_eval")) def test_format_params(): run(dpath("test_format_params"), check_md5=True) def test_rule_defined_in_for_loop(): # issue 257 run(dpath("test_rule_defined_in_for_loop")) def test_issue381(): run(dpath("test_issue381")) def test_format_wildcards(): run(dpath("test_format_wildcards")) def test_with_parentheses(): run(dpath("test (with parenthese's)")) def test_dup_out_patterns(): """Duplicate output patterns should emit an error Duplicate output patterns can be detected on the rule level """ run(dpath("test_dup_out_patterns"), shouldfail=True) def test_restartable_job_cmd_exit_1_no_restart(): """Test the restartable job feature on ``exit 1`` The shell snippet in the Snakemake file will fail the first time and succeed the second time. """ run( dpath("test_restartable_job_cmd_exit_1"), cluster="./qsub", restart_times=0, shouldfail=True, ) def test_restartable_job_cmd_exit_1_one_restart(): # Restarting once is enough run( dpath("test_restartable_job_cmd_exit_1"), cluster="./qsub", restart_times=1, printshellcmds=True, ) def test_restartable_job_qsub_exit_1(): """Test the restartable job feature when qsub fails The qsub in the sub directory will fail the first time and succeed the second time. """ # Even two consecutive times should fail as files are cleared run( dpath("test_restartable_job_qsub_exit_1"), cluster="./qsub", restart_times=0, shouldfail=True, ) run( dpath("test_restartable_job_qsub_exit_1"), cluster="./qsub", restart_times=0, shouldfail=True, ) # Restarting once is enough run( dpath("test_restartable_job_qsub_exit_1"), cluster="./qsub", restart_times=1, shouldfail=False, ) def test_threads(): run(dpath("test_threads"), cores=20) def test_threads0(): run(dpath("test_threads0")) def test_dynamic_temp(): run(dpath("test_dynamic_temp")) # TODO this currently hangs. Has to be investigated (issue #660). # def test_ftp_immediate_close(): # try: # import ftputil # # # only run the remote file test if the dependencies # # are installed, otherwise do nothing # run(dpath("test_ftp_immediate_close")) # except ImportError: # pass def test_issue260(): run(dpath("test_issue260")) @not_ci def test_default_remote(): run( dpath("test_default_remote"), cores=1, default_remote_provider="S3Mocked", default_remote_prefix="test-remote-bucket", ) def test_run_namedlist(): run(dpath("test_run_namedlist")) @connected @not_ci def test_remote_gs(): run(dpath("test_remote_gs")) @pytest.mark.skip(reason="Need to choose how to provide billable project") @connected @not_ci def test_gs_requester_pays( requesting_project=None, requesting_url="gcp-public-data-landsat/LC08/01/001/003/LC08_L1GT_001003_20170430_20170501_01_RT/LC08_L1GT_001003_20170430_20170501_01_RT_MTL.txt", ): """ Tests pull-request 79 / issue 96 for billable user projects on GS If requesting_project None, behaves as test_remote_gs(). Parameters ---------- requesting_project: Optional[str] User project to bill for download. None will not provide project for requester-pays as is the usual default requesting_url: str URL of bucket to download. Default will match expected output, but is a bucket that doesn't require requester pays. """ # create temporary config file with tempfile.NamedTemporaryFile(suffix=".yaml") as handle: # specify project and url for download if requesting_project is None: handle.write(b"project: null\n") else: handle.write('project: "{}"\n'.format(requesting_project).encode()) handle.write('url: "{}"\n'.format(requesting_url).encode()) # make sure we can read them handle.flush() # run the pipeline run(dpath("test_gs_requester_pays"), configfiles=[handle.name], forceall=True) @pytest.mark.skip(reason="We need free azure access to test this in CircleCI.") @connected @ci def test_remote_azure(): run(dpath("test_remote_azure")) def test_remote_log(): run(dpath("test_remote_log"), shouldfail=True) @connected @pytest.mark.xfail def test_remote_http(): run(dpath("test_remote_http")) @connected @pytest.mark.xfail def test_remote_http_cluster(): run(dpath("test_remote_http"), cluster=os.path.abspath(dpath("test14/qsub"))) def test_profile(): run(dpath("test_profile")) @connected def test_singularity(): run(dpath("test_singularity"), use_singularity=True) def test_singularity_invalid(): run( dpath("test_singularity"), targets=["invalid.txt"], use_singularity=True, shouldfail=True, ) @connected def test_singularity_conda(): run(dpath("test_singularity_conda"), use_singularity=True, use_conda=True) def test_issue612(): run(dpath("test_issue612"), dryrun=True) def test_bash(): run(dpath("test_bash")) def test_inoutput_is_path(): run(dpath("test_inoutput_is_path")) def test_archive(): run(dpath("test_archive"), archive="workflow-archive.tar.gz") def test_log_input(): run(dpath("test_log_input")) @pytest.fixture(scope="module") def gcloud_cluster(): class Cluster: def __init__(self): self.cluster = os.environ["GCLOUD_CLUSTER"] self.bucket_name = "snakemake-testing-{}".format(self.cluster) shell( """ $GCLOUD container clusters create {self.cluster} --num-nodes 3 --scopes storage-rw --zone us-central1-a --machine-type f1-micro $GCLOUD container clusters get-credentials {self.cluster} --zone us-central1-a $GSUTIL mb gs://{self.bucket_name} """ ) def delete(self): shell( """ $GCLOUD container clusters delete {self.cluster} --zone us-central1-a --quiet || true $GSUTIL rm -r gs://{self.bucket_name} || true """ ) def run(self, test="test_kubernetes", **kwargs): try: run( dpath(test), kubernetes="default", default_remote_provider="GS", default_remote_prefix=self.bucket_name, no_tmpdir=True, **kwargs ) except Exception as e: shell( "for p in `kubectl get pods | grep ^snakejob- | cut -f 1 -d ' '`; do kubectl logs $p; done" ) raise e def reset(self): shell("$GSUTIL rm -r gs://{self.bucket_name}/* || true") cluster = Cluster() yield cluster cluster.delete() @gcloud @pytest.mark.skip( reason="reenable once we have figured out how to fail if available core hours per month are exceeded" ) @pytest.mark.xfail def test_gcloud_plain(gcloud_cluster): gcloud_cluster.reset() gcloud_cluster.run() @gcloud @pytest.mark.skip(reason="need a faster cloud compute instance to run this") def test_gcloud_conda(gcloud_cluster): gcloud_cluster.reset() gcloud_cluster.run(use_conda=True) @gcloud @pytest.mark.skip(reason="need a faster cloud compute instance to run this") def test_gcloud_singularity(gcloud_cluster): gcloud_cluster.reset() gcloud_cluster.run(use_singularity=True) @gcloud @pytest.mark.skip(reason="need a faster cloud compute instance to run this") def test_gcloud_conda_singularity(gcloud_cluster): gcloud_cluster.reset() gcloud_cluster.run(use_singularity=True, use_conda=True) @gcloud() @pytest.mark.skip(reason="need a faster cloud compute instance to run this") def test_issue1041(gcloud_cluster): gcloud_cluster.reset() gcloud_cluster.run(test="test_issue1041") @connected def test_cwl(): run(dpath("test_cwl")) @connected def test_cwl_singularity(): run(dpath("test_cwl"), use_singularity=True) def test_issue805(): run(dpath("test_issue805"), shouldfail=True) def test_pathlib(): run(dpath("test_pathlib")) def test_pathlib_missing_file(): run(dpath("test_pathlib_missing_file"), shouldfail=True) def test_group_jobs(): run(dpath("test_group_jobs"), cluster="./qsub") def test_group_job_fail(): run(dpath("test_group_job_fail"), cluster="./qsub", shouldfail=True) def test_pipes(): run(dpath("test_pipes")) def test_pipes_fail(): run(dpath("test_pipes_fail"), shouldfail=True) def test_validate(): run(dpath("test_validate")) def test_validate_fail(): run( dpath("test_validate"), configfiles=[dpath("test_validate/config.fail.yaml")], shouldfail=True, ) def test_issue854(): # output and benchmark have inconsistent wildcards # this should fail when parsing run(dpath("test_issue854"), shouldfail=True) def test_issue850(): run(dpath("test_issue850"), cluster="./qsub") def test_issue860(): run(dpath("test_issue860"), cluster="./qsub", targets=["done"]) def test_issue894(): run(dpath("test_issue894")) def test_issue584(): run(dpath("test_issue584")) def test_issue912(): run(dpath("test_issue912")) def test_job_properties(): run(dpath("test_job_properties"), cluster="./qsub.py") def test_issue916(): run(dpath("test_issue916")) def test_issue930(): run(dpath("test_issue930"), cluster="./qsub") def test_issue635(): run(dpath("test_issue635"), use_conda=True, check_md5=False) # TODO remove skip @pytest.mark.skip( reason="Temporarily disable until the stable container image becomes available again." ) def test_convert_to_cwl(): workdir = dpath("test_convert_to_cwl") # run(workdir, export_cwl=os.path.join(workdir, "workflow.cwl")) shell( "cd {workdir}; PYTHONPATH={src} python -m snakemake --export-cwl workflow.cwl", src=os.getcwd(), ) shell("cd {workdir}; cwltool --singularity workflow.cwl") assert os.path.exists(os.path.join(workdir, "test.out")) def test_issue1037(): run(dpath("test_issue1037"), dryrun=True, cluster="qsub", targets=["Foo_A.done"]) def test_issue1046(): run(dpath("test_issue1046")) def test_checkpoints(): run(dpath("test_checkpoints")) def test_checkpoints_dir(): run(dpath("test_checkpoints_dir")) def test_issue1092(): run(dpath("test_issue1092")) def test_issue1093(): run(dpath("test_issue1093"), use_conda=True) def test_issue958(): run(dpath("test_issue958"), cluster="dummy", dryrun=True) def test_issue471(): run(dpath("test_issue471")) def test_issue1085(): run(dpath("test_issue1085"), shouldfail=True) def test_issue1083(): run(dpath("test_issue1083"), use_singularity=True) def test_pipes2(): run(dpath("test_pipes2")) @pytest.mark.skip( reason="The AWS Access Key Id you provided does not exist in our records." ) def test_tibanna(): workdir = dpath("test_tibanna") subprocess.check_call(["python", "cleanup.py"], cwd=workdir) run( workdir, use_conda=True, configfiles=[os.path.join(workdir, "config.json")], default_remote_prefix="snakemake-tibanna-test/1", tibanna_sfn="tibanna_unicorn_johannes", ) def test_expand_flag(): run(dpath("test_expand_flag"), shouldfail=True) def test_default_resources(): from snakemake.resources import DefaultResources run( dpath("test_default_resources"), default_resources=DefaultResources( ["mem_mb=max(2*input.size, 1000)", "disk_mb=max(2*input.size, 1000)"] ), ) def test_issue1284(): run(dpath("test_issue1284")) def test_issue1281(): run(dpath("test_issue1281")) def test_filegraph(): workdir = dpath("test_filegraph") dot_path = os.path.abspath("fg.dot") pdf_path = "fg.pdf" # make sure the calls work shell("cd {workdir}; python -m snakemake --filegraph > {dot_path}") # make sure the output can be interpreted by dot with open(dot_path, "rb") as dot_file, open(pdf_path, "wb") as pdf_file: pdf_file.write( subprocess.check_output(["dot", "-Tpdf"], stdin=dot_file, cwd=workdir) ) # make sure the generated pdf file is not empty assert os.stat(pdf_path).st_size > 0 def test_batch(): from snakemake.dag import Batch run(dpath("test_batch"), batch=Batch("aggregate", 1, 2)) def test_batch_final(): from snakemake.dag import Batch run(dpath("test_batch_final"), batch=Batch("aggregate", 1, 1)) def test_batch_fail(): from snakemake.dag import Batch run(dpath("test_batch"), batch=Batch("aggregate", 2, 2), shouldfail=True) def test_github_issue52(): run(dpath("test_github_issue52"), shouldfail=True) run(dpath("test_github_issue52"), snakefile="other.smk", shouldfail=True) def test_github_issue78(): run(dpath("test_github_issue78"), use_singularity=True) def test_github_issue105(): run(dpath("test_github_issue105")) def test_output_file_cache(): test_path = dpath("test_output_file_cache") os.environ["SNAKEMAKE_OUTPUT_CACHE"] = os.path.join(test_path, "cache") run(test_path, cache=["a", "b", "c"]) run(test_path, cache=["invalid_multi"], targets="invalid1.txt", shouldfail=True) def test_output_file_cache_remote(): test_path = dpath("test_output_file_cache_remote") os.environ["SNAKEMAKE_OUTPUT_CACHE"] = "cache" run( test_path, cache=["a", "b", "c"], default_remote_provider="S3Mocked", default_remote_prefix="test-remote-bucket", ) def test_multiext(): run(dpath("test_multiext")) def test_core_dependent_threads(): run(dpath("test_core_dependent_threads")) def test_env_modules(): run(dpath("test_env_modules"), use_env_modules=True) snakemake-5.10.0/versioneer.py000066400000000000000000002060031361131222100162600ustar00rootroot00000000000000 # Version: 0.18 """The Versioneer - like a rocketeer, but for versions. The Versioneer ============== * like a rocketeer, but for versions! * https://github.com/warner/python-versioneer * Brian Warner * License: Public Domain * Compatible With: python2.6, 2.7, 3.2, 3.3, 3.4, 3.5, 3.6, and pypy * [![Latest Version] (https://pypip.in/version/versioneer/badge.svg?style=flat) ](https://pypi.python.org/pypi/versioneer/) * [![Build Status] (https://travis-ci.org/warner/python-versioneer.png?branch=master) ](https://travis-ci.org/warner/python-versioneer) This is a tool for managing a recorded version number in distutils-based python projects. The goal is to remove the tedious and error-prone "update the embedded version string" step from your release process. Making a new release should be as easy as recording a new tag in your version-control system, and maybe making new tarballs. ## Quick Install * `pip install versioneer` to somewhere to your $PATH * add a `[versioneer]` section to your setup.cfg (see below) * run `versioneer install` in your source tree, commit the results ## Version Identifiers Source trees come from a variety of places: * a version-control system checkout (mostly used by developers) * a nightly tarball, produced by build automation * a snapshot tarball, produced by a web-based VCS browser, like github's "tarball from tag" feature * a release tarball, produced by "setup.py sdist", distributed through PyPI Within each source tree, the version identifier (either a string or a number, this tool is format-agnostic) can come from a variety of places: * ask the VCS tool itself, e.g. "git describe" (for checkouts), which knows about recent "tags" and an absolute revision-id * the name of the directory into which the tarball was unpacked * an expanded VCS keyword ($Id$, etc) * a `_version.py` created by some earlier build step For released software, the version identifier is closely related to a VCS tag. Some projects use tag names that include more than just the version string (e.g. "myproject-1.2" instead of just "1.2"), in which case the tool needs to strip the tag prefix to extract the version identifier. For unreleased software (between tags), the version identifier should provide enough information to help developers recreate the same tree, while also giving them an idea of roughly how old the tree is (after version 1.2, before version 1.3). Many VCS systems can report a description that captures this, for example `git describe --tags --dirty --always` reports things like "0.7-1-g574ab98-dirty" to indicate that the checkout is one revision past the 0.7 tag, has a unique revision id of "574ab98", and is "dirty" (it has uncommitted changes. The version identifier is used for multiple purposes: * to allow the module to self-identify its version: `myproject.__version__` * to choose a name and prefix for a 'setup.py sdist' tarball ## Theory of Operation Versioneer works by adding a special `_version.py` file into your source tree, where your `__init__.py` can import it. This `_version.py` knows how to dynamically ask the VCS tool for version information at import time. `_version.py` also contains `$Revision$` markers, and the installation process marks `_version.py` to have this marker rewritten with a tag name during the `git archive` command. As a result, generated tarballs will contain enough information to get the proper version. To allow `setup.py` to compute a version too, a `versioneer.py` is added to the top level of your source tree, next to `setup.py` and the `setup.cfg` that configures it. This overrides several distutils/setuptools commands to compute the version when invoked, and changes `setup.py build` and `setup.py sdist` to replace `_version.py` with a small static file that contains just the generated version data. ## Installation See [INSTALL.md](./INSTALL.md) for detailed installation instructions. ## Version-String Flavors Code which uses Versioneer can learn about its version string at runtime by importing `_version` from your main `__init__.py` file and running the `get_versions()` function. From the "outside" (e.g. in `setup.py`), you can import the top-level `versioneer.py` and run `get_versions()`. Both functions return a dictionary with different flavors of version information: * `['version']`: A condensed version string, rendered using the selected style. This is the most commonly used value for the project's version string. The default "pep440" style yields strings like `0.11`, `0.11+2.g1076c97`, or `0.11+2.g1076c97.dirty`. See the "Styles" section below for alternative styles. * `['full-revisionid']`: detailed revision identifier. For Git, this is the full SHA1 commit id, e.g. "1076c978a8d3cfc70f408fe5974aa6c092c949ac". * `['date']`: Date and time of the latest `HEAD` commit. For Git, it is the commit date in ISO 8601 format. This will be None if the date is not available. * `['dirty']`: a boolean, True if the tree has uncommitted changes. Note that this is only accurate if run in a VCS checkout, otherwise it is likely to be False or None * `['error']`: if the version string could not be computed, this will be set to a string describing the problem, otherwise it will be None. It may be useful to throw an exception in setup.py if this is set, to avoid e.g. creating tarballs with a version string of "unknown". Some variants are more useful than others. Including `full-revisionid` in a bug report should allow developers to reconstruct the exact code being tested (or indicate the presence of local changes that should be shared with the developers). `version` is suitable for display in an "about" box or a CLI `--version` output: it can be easily compared against release notes and lists of bugs fixed in various releases. The installer adds the following text to your `__init__.py` to place a basic version in `YOURPROJECT.__version__`: from ._version import get_versions __version__ = get_versions()['version'] del get_versions ## Styles The setup.cfg `style=` configuration controls how the VCS information is rendered into a version string. The default style, "pep440", produces a PEP440-compliant string, equal to the un-prefixed tag name for actual releases, and containing an additional "local version" section with more detail for in-between builds. For Git, this is TAG[+DISTANCE.gHEX[.dirty]] , using information from `git describe --tags --dirty --always`. For example "0.11+2.g1076c97.dirty" indicates that the tree is like the "1076c97" commit but has uncommitted changes (".dirty"), and that this commit is two revisions ("+2") beyond the "0.11" tag. For released software (exactly equal to a known tag), the identifier will only contain the stripped tag, e.g. "0.11". Other styles are available. See [details.md](details.md) in the Versioneer source tree for descriptions. ## Debugging Versioneer tries to avoid fatal errors: if something goes wrong, it will tend to return a version of "0+unknown". To investigate the problem, run `setup.py version`, which will run the version-lookup code in a verbose mode, and will display the full contents of `get_versions()` (including the `error` string, which may help identify what went wrong). ## Known Limitations Some situations are known to cause problems for Versioneer. This details the most significant ones. More can be found on Github [issues page](https://github.com/warner/python-versioneer/issues). ### Subprojects Versioneer has limited support for source trees in which `setup.py` is not in the root directory (e.g. `setup.py` and `.git/` are *not* siblings). The are two common reasons why `setup.py` might not be in the root: * Source trees which contain multiple subprojects, such as [Buildbot](https://github.com/buildbot/buildbot), which contains both "master" and "slave" subprojects, each with their own `setup.py`, `setup.cfg`, and `tox.ini`. Projects like these produce multiple PyPI distributions (and upload multiple independently-installable tarballs). * Source trees whose main purpose is to contain a C library, but which also provide bindings to Python (and perhaps other langauges) in subdirectories. Versioneer will look for `.git` in parent directories, and most operations should get the right version string. However `pip` and `setuptools` have bugs and implementation details which frequently cause `pip install .` from a subproject directory to fail to find a correct version string (so it usually defaults to `0+unknown`). `pip install --editable .` should work correctly. `setup.py install` might work too. Pip-8.1.1 is known to have this problem, but hopefully it will get fixed in some later version. [Bug #38](https://github.com/warner/python-versioneer/issues/38) is tracking this issue. The discussion in [PR #61](https://github.com/warner/python-versioneer/pull/61) describes the issue from the Versioneer side in more detail. [pip PR#3176](https://github.com/pypa/pip/pull/3176) and [pip PR#3615](https://github.com/pypa/pip/pull/3615) contain work to improve pip to let Versioneer work correctly. Versioneer-0.16 and earlier only looked for a `.git` directory next to the `setup.cfg`, so subprojects were completely unsupported with those releases. ### Editable installs with setuptools <= 18.5 `setup.py develop` and `pip install --editable .` allow you to install a project into a virtualenv once, then continue editing the source code (and test) without re-installing after every change. "Entry-point scripts" (`setup(entry_points={"console_scripts": ..})`) are a convenient way to specify executable scripts that should be installed along with the python package. These both work as expected when using modern setuptools. When using setuptools-18.5 or earlier, however, certain operations will cause `pkg_resources.DistributionNotFound` errors when running the entrypoint script, which must be resolved by re-installing the package. This happens when the install happens with one version, then the egg_info data is regenerated while a different version is checked out. Many setup.py commands cause egg_info to be rebuilt (including `sdist`, `wheel`, and installing into a different virtualenv), so this can be surprising. [Bug #83](https://github.com/warner/python-versioneer/issues/83) describes this one, but upgrading to a newer version of setuptools should probably resolve it. ### Unicode version strings While Versioneer works (and is continually tested) with both Python 2 and Python 3, it is not entirely consistent with bytes-vs-unicode distinctions. Newer releases probably generate unicode version strings on py2. It's not clear that this is wrong, but it may be surprising for applications when then write these strings to a network connection or include them in bytes-oriented APIs like cryptographic checksums. [Bug #71](https://github.com/warner/python-versioneer/issues/71) investigates this question. ## Updating Versioneer To upgrade your project to a new release of Versioneer, do the following: * install the new Versioneer (`pip install -U versioneer` or equivalent) * edit `setup.cfg`, if necessary, to include any new configuration settings indicated by the release notes. See [UPGRADING](./UPGRADING.md) for details. * re-run `versioneer install` in your source tree, to replace `SRC/_version.py` * commit any changed files ## Future Directions This tool is designed to make it easily extended to other version-control systems: all VCS-specific components are in separate directories like src/git/ . The top-level `versioneer.py` script is assembled from these components by running make-versioneer.py . In the future, make-versioneer.py will take a VCS name as an argument, and will construct a version of `versioneer.py` that is specific to the given VCS. It might also take the configuration arguments that are currently provided manually during installation by editing setup.py . Alternatively, it might go the other direction and include code from all supported VCS systems, reducing the number of intermediate scripts. ## License To make Versioneer easier to embed, all its code is dedicated to the public domain. The `_version.py` that it creates is also in the public domain. Specifically, both are released under the Creative Commons "Public Domain Dedication" license (CC0-1.0), as described in https://creativecommons.org/publicdomain/zero/1.0/ . """ from __future__ import print_function try: import configparser except ImportError: import ConfigParser as configparser import errno import json import os import re import subprocess import sys class VersioneerConfig: """Container for Versioneer configuration parameters.""" def get_root(): """Get the project root directory. We require that all commands are run from the project root, i.e. the directory that contains setup.py, setup.cfg, and versioneer.py . """ root = os.path.realpath(os.path.abspath(os.getcwd())) setup_py = os.path.join(root, "setup.py") versioneer_py = os.path.join(root, "versioneer.py") if not (os.path.exists(setup_py) or os.path.exists(versioneer_py)): # allow 'python path/to/setup.py COMMAND' root = os.path.dirname(os.path.realpath(os.path.abspath(sys.argv[0]))) setup_py = os.path.join(root, "setup.py") versioneer_py = os.path.join(root, "versioneer.py") if not (os.path.exists(setup_py) or os.path.exists(versioneer_py)): err = ("Versioneer was unable to run the project root directory. " "Versioneer requires setup.py to be executed from " "its immediate directory (like 'python setup.py COMMAND'), " "or in a way that lets it use sys.argv[0] to find the root " "(like 'python path/to/setup.py COMMAND').") raise VersioneerBadRootError(err) try: # Certain runtime workflows (setup.py install/develop in a setuptools # tree) execute all dependencies in a single python process, so # "versioneer" may be imported multiple times, and python's shared # module-import table will cache the first one. So we can't use # os.path.dirname(__file__), as that will find whichever # versioneer.py was first imported, even in later projects. me = os.path.realpath(os.path.abspath(__file__)) me_dir = os.path.normcase(os.path.splitext(me)[0]) vsr_dir = os.path.normcase(os.path.splitext(versioneer_py)[0]) if me_dir != vsr_dir: print("Warning: build in %s is using versioneer.py from %s" % (os.path.dirname(me), versioneer_py)) except NameError: pass return root def get_config_from_root(root): """Read the project setup.cfg file to determine Versioneer config.""" # This might raise EnvironmentError (if setup.cfg is missing), or # configparser.NoSectionError (if it lacks a [versioneer] section), or # configparser.NoOptionError (if it lacks "VCS="). See the docstring at # the top of versioneer.py for instructions on writing your setup.cfg . setup_cfg = os.path.join(root, "setup.cfg") parser = configparser.SafeConfigParser() with open(setup_cfg, "r") as f: parser.readfp(f) VCS = parser.get("versioneer", "VCS") # mandatory def get(parser, name): if parser.has_option("versioneer", name): return parser.get("versioneer", name) return None cfg = VersioneerConfig() cfg.VCS = VCS cfg.style = get(parser, "style") or "" cfg.versionfile_source = get(parser, "versionfile_source") cfg.versionfile_build = get(parser, "versionfile_build") cfg.tag_prefix = get(parser, "tag_prefix") if cfg.tag_prefix in ("''", '""'): cfg.tag_prefix = "" cfg.parentdir_prefix = get(parser, "parentdir_prefix") cfg.verbose = get(parser, "verbose") return cfg class NotThisMethod(Exception): """Exception raised if a method is not valid for the current scenario.""" # these dictionaries contain VCS-specific tools LONG_VERSION_PY = {} HANDLERS = {} def register_vcs_handler(vcs, method): # decorator """Decorator to mark a method as the handler for a particular VCS.""" def decorate(f): """Store f in HANDLERS[vcs][method].""" if vcs not in HANDLERS: HANDLERS[vcs] = {} HANDLERS[vcs][method] = f return f return decorate def run_command(commands, args, cwd=None, verbose=False, hide_stderr=False, env=None): """Call the given command(s).""" assert isinstance(commands, list) p = None for c in commands: try: dispcmd = str([c] + args) # remember shell=False, so use git.cmd on windows, not just git p = subprocess.Popen([c] + args, cwd=cwd, env=env, stdout=subprocess.PIPE, stderr=(subprocess.PIPE if hide_stderr else None)) break except EnvironmentError: e = sys.exc_info()[1] if e.errno == errno.ENOENT: continue if verbose: print("unable to run %s" % dispcmd) print(e) return None, None else: if verbose: print("unable to find command, tried %s" % (commands,)) return None, None stdout = p.communicate()[0].strip() if sys.version_info[0] >= 3: stdout = stdout.decode() if p.returncode != 0: if verbose: print("unable to run %s (error)" % dispcmd) print("stdout was %s" % stdout) return None, p.returncode return stdout, p.returncode LONG_VERSION_PY['git'] = ''' # This file helps to compute a version number in source trees obtained from # git-archive tarball (such as those provided by githubs download-from-tag # feature). Distribution tarballs (built by setup.py sdist) and build # directories (produced by setup.py build) will contain a much shorter file # that just contains the computed version number. # This file is released into the public domain. Generated by # versioneer-0.18 (https://github.com/warner/python-versioneer) """Git implementation of _version.py.""" import errno import os import re import subprocess import sys def get_keywords(): """Get the keywords needed to look up the version information.""" # these strings will be replaced by git during git-archive. # setup.py/versioneer.py will grep for the variable names, so they must # each be defined on a line of their own. _version.py will just call # get_keywords(). git_refnames = "%(DOLLAR)sFormat:%%d%(DOLLAR)s" git_full = "%(DOLLAR)sFormat:%%H%(DOLLAR)s" git_date = "%(DOLLAR)sFormat:%%ci%(DOLLAR)s" keywords = {"refnames": git_refnames, "full": git_full, "date": git_date} return keywords class VersioneerConfig: """Container for Versioneer configuration parameters.""" def get_config(): """Create, populate and return the VersioneerConfig() object.""" # these strings are filled in when 'setup.py versioneer' creates # _version.py cfg = VersioneerConfig() cfg.VCS = "git" cfg.style = "%(STYLE)s" cfg.tag_prefix = "%(TAG_PREFIX)s" cfg.parentdir_prefix = "%(PARENTDIR_PREFIX)s" cfg.versionfile_source = "%(VERSIONFILE_SOURCE)s" cfg.verbose = False return cfg class NotThisMethod(Exception): """Exception raised if a method is not valid for the current scenario.""" LONG_VERSION_PY = {} HANDLERS = {} def register_vcs_handler(vcs, method): # decorator """Decorator to mark a method as the handler for a particular VCS.""" def decorate(f): """Store f in HANDLERS[vcs][method].""" if vcs not in HANDLERS: HANDLERS[vcs] = {} HANDLERS[vcs][method] = f return f return decorate def run_command(commands, args, cwd=None, verbose=False, hide_stderr=False, env=None): """Call the given command(s).""" assert isinstance(commands, list) p = None for c in commands: try: dispcmd = str([c] + args) # remember shell=False, so use git.cmd on windows, not just git p = subprocess.Popen([c] + args, cwd=cwd, env=env, stdout=subprocess.PIPE, stderr=(subprocess.PIPE if hide_stderr else None)) break except EnvironmentError: e = sys.exc_info()[1] if e.errno == errno.ENOENT: continue if verbose: print("unable to run %%s" %% dispcmd) print(e) return None, None else: if verbose: print("unable to find command, tried %%s" %% (commands,)) return None, None stdout = p.communicate()[0].strip() if sys.version_info[0] >= 3: stdout = stdout.decode() if p.returncode != 0: if verbose: print("unable to run %%s (error)" %% dispcmd) print("stdout was %%s" %% stdout) return None, p.returncode return stdout, p.returncode def versions_from_parentdir(parentdir_prefix, root, verbose): """Try to determine the version from the parent directory name. Source tarballs conventionally unpack into a directory that includes both the project name and a version string. We will also support searching up two directory levels for an appropriately named parent directory """ rootdirs = [] for i in range(3): dirname = os.path.basename(root) if dirname.startswith(parentdir_prefix): return {"version": dirname[len(parentdir_prefix):], "full-revisionid": None, "dirty": False, "error": None, "date": None} else: rootdirs.append(root) root = os.path.dirname(root) # up a level if verbose: print("Tried directories %%s but none started with prefix %%s" %% (str(rootdirs), parentdir_prefix)) raise NotThisMethod("rootdir doesn't start with parentdir_prefix") @register_vcs_handler("git", "get_keywords") def git_get_keywords(versionfile_abs): """Extract version information from the given file.""" # the code embedded in _version.py can just fetch the value of these # keywords. When used from setup.py, we don't want to import _version.py, # so we do it with a regexp instead. This function is not used from # _version.py. keywords = {} try: f = open(versionfile_abs, "r") for line in f.readlines(): if line.strip().startswith("git_refnames ="): mo = re.search(r'=\s*"(.*)"', line) if mo: keywords["refnames"] = mo.group(1) if line.strip().startswith("git_full ="): mo = re.search(r'=\s*"(.*)"', line) if mo: keywords["full"] = mo.group(1) if line.strip().startswith("git_date ="): mo = re.search(r'=\s*"(.*)"', line) if mo: keywords["date"] = mo.group(1) f.close() except EnvironmentError: pass return keywords @register_vcs_handler("git", "keywords") def git_versions_from_keywords(keywords, tag_prefix, verbose): """Get version information from git keywords.""" if not keywords: raise NotThisMethod("no keywords at all, weird") date = keywords.get("date") if date is not None: # git-2.2.0 added "%%cI", which expands to an ISO-8601 -compliant # datestamp. However we prefer "%%ci" (which expands to an "ISO-8601 # -like" string, which we must then edit to make compliant), because # it's been around since git-1.5.3, and it's too difficult to # discover which version we're using, or to work around using an # older one. date = date.strip().replace(" ", "T", 1).replace(" ", "", 1) refnames = keywords["refnames"].strip() if refnames.startswith("$Format"): if verbose: print("keywords are unexpanded, not using") raise NotThisMethod("unexpanded keywords, not a git-archive tarball") refs = set([r.strip() for r in refnames.strip("()").split(",")]) # starting in git-1.8.3, tags are listed as "tag: foo-1.0" instead of # just "foo-1.0". If we see a "tag: " prefix, prefer those. TAG = "tag: " tags = set([r[len(TAG):] for r in refs if r.startswith(TAG)]) if not tags: # Either we're using git < 1.8.3, or there really are no tags. We use # a heuristic: assume all version tags have a digit. The old git %%d # expansion behaves like git log --decorate=short and strips out the # refs/heads/ and refs/tags/ prefixes that would let us distinguish # between branches and tags. By ignoring refnames without digits, we # filter out many common branch names like "release" and # "stabilization", as well as "HEAD" and "master". tags = set([r for r in refs if re.search(r'\d', r)]) if verbose: print("discarding '%%s', no digits" %% ",".join(refs - tags)) if verbose: print("likely tags: %%s" %% ",".join(sorted(tags))) for ref in sorted(tags): # sorting will prefer e.g. "2.0" over "2.0rc1" if ref.startswith(tag_prefix): r = ref[len(tag_prefix):] if verbose: print("picking %%s" %% r) return {"version": r, "full-revisionid": keywords["full"].strip(), "dirty": False, "error": None, "date": date} # no suitable tags, so version is "0+unknown", but full hex is still there if verbose: print("no suitable tags, using unknown + full revision id") return {"version": "0+unknown", "full-revisionid": keywords["full"].strip(), "dirty": False, "error": "no suitable tags", "date": None} @register_vcs_handler("git", "pieces_from_vcs") def git_pieces_from_vcs(tag_prefix, root, verbose, run_command=run_command): """Get version from 'git describe' in the root of the source tree. This only gets called if the git-archive 'subst' keywords were *not* expanded, and _version.py hasn't already been rewritten with a short version string, meaning we're inside a checked out source tree. """ GITS = ["git"] if sys.platform == "win32": GITS = ["git.cmd", "git.exe"] out, rc = run_command(GITS, ["rev-parse", "--git-dir"], cwd=root, hide_stderr=True) if rc != 0: if verbose: print("Directory %%s not under git control" %% root) raise NotThisMethod("'git rev-parse --git-dir' returned error") # if there is a tag matching tag_prefix, this yields TAG-NUM-gHEX[-dirty] # if there isn't one, this yields HEX[-dirty] (no NUM) describe_out, rc = run_command(GITS, ["describe", "--tags", "--dirty", "--always", "--long", "--match", "%%s*" %% tag_prefix], cwd=root) # --long was added in git-1.5.5 if describe_out is None: raise NotThisMethod("'git describe' failed") describe_out = describe_out.strip() full_out, rc = run_command(GITS, ["rev-parse", "HEAD"], cwd=root) if full_out is None: raise NotThisMethod("'git rev-parse' failed") full_out = full_out.strip() pieces = {} pieces["long"] = full_out pieces["short"] = full_out[:7] # maybe improved later pieces["error"] = None # parse describe_out. It will be like TAG-NUM-gHEX[-dirty] or HEX[-dirty] # TAG might have hyphens. git_describe = describe_out # look for -dirty suffix dirty = git_describe.endswith("-dirty") pieces["dirty"] = dirty if dirty: git_describe = git_describe[:git_describe.rindex("-dirty")] # now we have TAG-NUM-gHEX or HEX if "-" in git_describe: # TAG-NUM-gHEX mo = re.search(r'^(.+)-(\d+)-g([0-9a-f]+)$', git_describe) if not mo: # unparseable. Maybe git-describe is misbehaving? pieces["error"] = ("unable to parse git-describe output: '%%s'" %% describe_out) return pieces # tag full_tag = mo.group(1) if not full_tag.startswith(tag_prefix): if verbose: fmt = "tag '%%s' doesn't start with prefix '%%s'" print(fmt %% (full_tag, tag_prefix)) pieces["error"] = ("tag '%%s' doesn't start with prefix '%%s'" %% (full_tag, tag_prefix)) return pieces pieces["closest-tag"] = full_tag[len(tag_prefix):] # distance: number of commits since tag pieces["distance"] = int(mo.group(2)) # commit: short hex revision ID pieces["short"] = mo.group(3) else: # HEX: no tags pieces["closest-tag"] = None count_out, rc = run_command(GITS, ["rev-list", "HEAD", "--count"], cwd=root) pieces["distance"] = int(count_out) # total number of commits # commit date: see ISO-8601 comment in git_versions_from_keywords() date = run_command(GITS, ["show", "-s", "--format=%%ci", "HEAD"], cwd=root)[0].strip() pieces["date"] = date.strip().replace(" ", "T", 1).replace(" ", "", 1) return pieces def plus_or_dot(pieces): """Return a + if we don't already have one, else return a .""" if "+" in pieces.get("closest-tag", ""): return "." return "+" def render_pep440(pieces): """Build up version string, with post-release "local version identifier". Our goal: TAG[+DISTANCE.gHEX[.dirty]] . Note that if you get a tagged build and then dirty it, you'll get TAG+0.gHEX.dirty Exceptions: 1: no tags. git_describe was just HEX. 0+untagged.DISTANCE.gHEX[.dirty] """ if pieces["closest-tag"]: rendered = pieces["closest-tag"] if pieces["distance"] or pieces["dirty"]: rendered += plus_or_dot(pieces) rendered += "%%d.g%%s" %% (pieces["distance"], pieces["short"]) if pieces["dirty"]: rendered += ".dirty" else: # exception #1 rendered = "0+untagged.%%d.g%%s" %% (pieces["distance"], pieces["short"]) if pieces["dirty"]: rendered += ".dirty" return rendered def render_pep440_pre(pieces): """TAG[.post.devDISTANCE] -- No -dirty. Exceptions: 1: no tags. 0.post.devDISTANCE """ if pieces["closest-tag"]: rendered = pieces["closest-tag"] if pieces["distance"]: rendered += ".post.dev%%d" %% pieces["distance"] else: # exception #1 rendered = "0.post.dev%%d" %% pieces["distance"] return rendered def render_pep440_post(pieces): """TAG[.postDISTANCE[.dev0]+gHEX] . The ".dev0" means dirty. Note that .dev0 sorts backwards (a dirty tree will appear "older" than the corresponding clean one), but you shouldn't be releasing software with -dirty anyways. Exceptions: 1: no tags. 0.postDISTANCE[.dev0] """ if pieces["closest-tag"]: rendered = pieces["closest-tag"] if pieces["distance"] or pieces["dirty"]: rendered += ".post%%d" %% pieces["distance"] if pieces["dirty"]: rendered += ".dev0" rendered += plus_or_dot(pieces) rendered += "g%%s" %% pieces["short"] else: # exception #1 rendered = "0.post%%d" %% pieces["distance"] if pieces["dirty"]: rendered += ".dev0" rendered += "+g%%s" %% pieces["short"] return rendered def render_pep440_old(pieces): """TAG[.postDISTANCE[.dev0]] . The ".dev0" means dirty. Eexceptions: 1: no tags. 0.postDISTANCE[.dev0] """ if pieces["closest-tag"]: rendered = pieces["closest-tag"] if pieces["distance"] or pieces["dirty"]: rendered += ".post%%d" %% pieces["distance"] if pieces["dirty"]: rendered += ".dev0" else: # exception #1 rendered = "0.post%%d" %% pieces["distance"] if pieces["dirty"]: rendered += ".dev0" return rendered def render_git_describe(pieces): """TAG[-DISTANCE-gHEX][-dirty]. Like 'git describe --tags --dirty --always'. Exceptions: 1: no tags. HEX[-dirty] (note: no 'g' prefix) """ if pieces["closest-tag"]: rendered = pieces["closest-tag"] if pieces["distance"]: rendered += "-%%d-g%%s" %% (pieces["distance"], pieces["short"]) else: # exception #1 rendered = pieces["short"] if pieces["dirty"]: rendered += "-dirty" return rendered def render_git_describe_long(pieces): """TAG-DISTANCE-gHEX[-dirty]. Like 'git describe --tags --dirty --always -long'. The distance/hash is unconditional. Exceptions: 1: no tags. HEX[-dirty] (note: no 'g' prefix) """ if pieces["closest-tag"]: rendered = pieces["closest-tag"] rendered += "-%%d-g%%s" %% (pieces["distance"], pieces["short"]) else: # exception #1 rendered = pieces["short"] if pieces["dirty"]: rendered += "-dirty" return rendered def render(pieces, style): """Render the given version pieces into the requested style.""" if pieces["error"]: return {"version": "unknown", "full-revisionid": pieces.get("long"), "dirty": None, "error": pieces["error"], "date": None} if not style or style == "default": style = "pep440" # the default if style == "pep440": rendered = render_pep440(pieces) elif style == "pep440-pre": rendered = render_pep440_pre(pieces) elif style == "pep440-post": rendered = render_pep440_post(pieces) elif style == "pep440-old": rendered = render_pep440_old(pieces) elif style == "git-describe": rendered = render_git_describe(pieces) elif style == "git-describe-long": rendered = render_git_describe_long(pieces) else: raise ValueError("unknown style '%%s'" %% style) return {"version": rendered, "full-revisionid": pieces["long"], "dirty": pieces["dirty"], "error": None, "date": pieces.get("date")} def get_versions(): """Get version information or return default if unable to do so.""" # I am in _version.py, which lives at ROOT/VERSIONFILE_SOURCE. If we have # __file__, we can work backwards from there to the root. Some # py2exe/bbfreeze/non-CPython implementations don't do __file__, in which # case we can only use expanded keywords. cfg = get_config() verbose = cfg.verbose try: return git_versions_from_keywords(get_keywords(), cfg.tag_prefix, verbose) except NotThisMethod: pass try: root = os.path.realpath(__file__) # versionfile_source is the relative path from the top of the source # tree (where the .git directory might live) to this file. Invert # this to find the root from __file__. for i in cfg.versionfile_source.split('/'): root = os.path.dirname(root) except NameError: return {"version": "0+unknown", "full-revisionid": None, "dirty": None, "error": "unable to find root of source tree", "date": None} try: pieces = git_pieces_from_vcs(cfg.tag_prefix, root, verbose) return render(pieces, cfg.style) except NotThisMethod: pass try: if cfg.parentdir_prefix: return versions_from_parentdir(cfg.parentdir_prefix, root, verbose) except NotThisMethod: pass return {"version": "0+unknown", "full-revisionid": None, "dirty": None, "error": "unable to compute version", "date": None} ''' @register_vcs_handler("git", "get_keywords") def git_get_keywords(versionfile_abs): """Extract version information from the given file.""" # the code embedded in _version.py can just fetch the value of these # keywords. When used from setup.py, we don't want to import _version.py, # so we do it with a regexp instead. This function is not used from # _version.py. keywords = {} try: f = open(versionfile_abs, "r") for line in f.readlines(): if line.strip().startswith("git_refnames ="): mo = re.search(r'=\s*"(.*)"', line) if mo: keywords["refnames"] = mo.group(1) if line.strip().startswith("git_full ="): mo = re.search(r'=\s*"(.*)"', line) if mo: keywords["full"] = mo.group(1) if line.strip().startswith("git_date ="): mo = re.search(r'=\s*"(.*)"', line) if mo: keywords["date"] = mo.group(1) f.close() except EnvironmentError: pass return keywords @register_vcs_handler("git", "keywords") def git_versions_from_keywords(keywords, tag_prefix, verbose): """Get version information from git keywords.""" if not keywords: raise NotThisMethod("no keywords at all, weird") date = keywords.get("date") if date is not None: # git-2.2.0 added "%cI", which expands to an ISO-8601 -compliant # datestamp. However we prefer "%ci" (which expands to an "ISO-8601 # -like" string, which we must then edit to make compliant), because # it's been around since git-1.5.3, and it's too difficult to # discover which version we're using, or to work around using an # older one. date = date.strip().replace(" ", "T", 1).replace(" ", "", 1) refnames = keywords["refnames"].strip() if refnames.startswith("$Format"): if verbose: print("keywords are unexpanded, not using") raise NotThisMethod("unexpanded keywords, not a git-archive tarball") refs = set([r.strip() for r in refnames.strip("()").split(",")]) # starting in git-1.8.3, tags are listed as "tag: foo-1.0" instead of # just "foo-1.0". If we see a "tag: " prefix, prefer those. TAG = "tag: " tags = set([r[len(TAG):] for r in refs if r.startswith(TAG)]) if not tags: # Either we're using git < 1.8.3, or there really are no tags. We use # a heuristic: assume all version tags have a digit. The old git %d # expansion behaves like git log --decorate=short and strips out the # refs/heads/ and refs/tags/ prefixes that would let us distinguish # between branches and tags. By ignoring refnames without digits, we # filter out many common branch names like "release" and # "stabilization", as well as "HEAD" and "master". tags = set([r for r in refs if re.search(r'\d', r)]) if verbose: print("discarding '%s', no digits" % ",".join(refs - tags)) if verbose: print("likely tags: %s" % ",".join(sorted(tags))) for ref in sorted(tags): # sorting will prefer e.g. "2.0" over "2.0rc1" if ref.startswith(tag_prefix): r = ref[len(tag_prefix):] if verbose: print("picking %s" % r) return {"version": r, "full-revisionid": keywords["full"].strip(), "dirty": False, "error": None, "date": date} # no suitable tags, so version is "0+unknown", but full hex is still there if verbose: print("no suitable tags, using unknown + full revision id") return {"version": "0+unknown", "full-revisionid": keywords["full"].strip(), "dirty": False, "error": "no suitable tags", "date": None} @register_vcs_handler("git", "pieces_from_vcs") def git_pieces_from_vcs(tag_prefix, root, verbose, run_command=run_command): """Get version from 'git describe' in the root of the source tree. This only gets called if the git-archive 'subst' keywords were *not* expanded, and _version.py hasn't already been rewritten with a short version string, meaning we're inside a checked out source tree. """ GITS = ["git"] if sys.platform == "win32": GITS = ["git.cmd", "git.exe"] out, rc = run_command(GITS, ["rev-parse", "--git-dir"], cwd=root, hide_stderr=True) if rc != 0: if verbose: print("Directory %s not under git control" % root) raise NotThisMethod("'git rev-parse --git-dir' returned error") # if there is a tag matching tag_prefix, this yields TAG-NUM-gHEX[-dirty] # if there isn't one, this yields HEX[-dirty] (no NUM) describe_out, rc = run_command(GITS, ["describe", "--tags", "--dirty", "--always", "--long", "--match", "%s*" % tag_prefix], cwd=root) # --long was added in git-1.5.5 if describe_out is None: raise NotThisMethod("'git describe' failed") describe_out = describe_out.strip() full_out, rc = run_command(GITS, ["rev-parse", "HEAD"], cwd=root) if full_out is None: raise NotThisMethod("'git rev-parse' failed") full_out = full_out.strip() pieces = {} pieces["long"] = full_out pieces["short"] = full_out[:7] # maybe improved later pieces["error"] = None # parse describe_out. It will be like TAG-NUM-gHEX[-dirty] or HEX[-dirty] # TAG might have hyphens. git_describe = describe_out # look for -dirty suffix dirty = git_describe.endswith("-dirty") pieces["dirty"] = dirty if dirty: git_describe = git_describe[:git_describe.rindex("-dirty")] # now we have TAG-NUM-gHEX or HEX if "-" in git_describe: # TAG-NUM-gHEX mo = re.search(r'^(.+)-(\d+)-g([0-9a-f]+)$', git_describe) if not mo: # unparseable. Maybe git-describe is misbehaving? pieces["error"] = ("unable to parse git-describe output: '%s'" % describe_out) return pieces # tag full_tag = mo.group(1) if not full_tag.startswith(tag_prefix): if verbose: fmt = "tag '%s' doesn't start with prefix '%s'" print(fmt % (full_tag, tag_prefix)) pieces["error"] = ("tag '%s' doesn't start with prefix '%s'" % (full_tag, tag_prefix)) return pieces pieces["closest-tag"] = full_tag[len(tag_prefix):] # distance: number of commits since tag pieces["distance"] = int(mo.group(2)) # commit: short hex revision ID pieces["short"] = mo.group(3) else: # HEX: no tags pieces["closest-tag"] = None count_out, rc = run_command(GITS, ["rev-list", "HEAD", "--count"], cwd=root) pieces["distance"] = int(count_out) # total number of commits # commit date: see ISO-8601 comment in git_versions_from_keywords() date = run_command(GITS, ["show", "-s", "--format=%ci", "HEAD"], cwd=root)[0].strip() pieces["date"] = date.strip().replace(" ", "T", 1).replace(" ", "", 1) return pieces def do_vcs_install(manifest_in, versionfile_source, ipy): """Git-specific installation logic for Versioneer. For Git, this means creating/changing .gitattributes to mark _version.py for export-subst keyword substitution. """ GITS = ["git"] if sys.platform == "win32": GITS = ["git.cmd", "git.exe"] files = [manifest_in, versionfile_source] if ipy: files.append(ipy) try: me = __file__ if me.endswith(".pyc") or me.endswith(".pyo"): me = os.path.splitext(me)[0] + ".py" versioneer_file = os.path.relpath(me) except NameError: versioneer_file = "versioneer.py" files.append(versioneer_file) present = False try: f = open(".gitattributes", "r") for line in f.readlines(): if line.strip().startswith(versionfile_source): if "export-subst" in line.strip().split()[1:]: present = True f.close() except EnvironmentError: pass if not present: f = open(".gitattributes", "a+") f.write("%s export-subst\n" % versionfile_source) f.close() files.append(".gitattributes") run_command(GITS, ["add", "--"] + files) def versions_from_parentdir(parentdir_prefix, root, verbose): """Try to determine the version from the parent directory name. Source tarballs conventionally unpack into a directory that includes both the project name and a version string. We will also support searching up two directory levels for an appropriately named parent directory """ rootdirs = [] for i in range(3): dirname = os.path.basename(root) if dirname.startswith(parentdir_prefix): return {"version": dirname[len(parentdir_prefix):], "full-revisionid": None, "dirty": False, "error": None, "date": None} else: rootdirs.append(root) root = os.path.dirname(root) # up a level if verbose: print("Tried directories %s but none started with prefix %s" % (str(rootdirs), parentdir_prefix)) raise NotThisMethod("rootdir doesn't start with parentdir_prefix") SHORT_VERSION_PY = """ # This file was generated by 'versioneer.py' (0.18) from # revision-control system data, or from the parent directory name of an # unpacked source archive. Distribution tarballs contain a pre-generated copy # of this file. import json version_json = ''' %s ''' # END VERSION_JSON def get_versions(): return json.loads(version_json) """ def versions_from_file(filename): """Try to determine the version from _version.py if present.""" try: with open(filename) as f: contents = f.read() except EnvironmentError: raise NotThisMethod("unable to read _version.py") mo = re.search(r"version_json = '''\n(.*)''' # END VERSION_JSON", contents, re.M | re.S) if not mo: mo = re.search(r"version_json = '''\r\n(.*)''' # END VERSION_JSON", contents, re.M | re.S) if not mo: raise NotThisMethod("no version_json in _version.py") return json.loads(mo.group(1)) def write_to_version_file(filename, versions): """Write the given version number to the given _version.py file.""" os.unlink(filename) contents = json.dumps(versions, sort_keys=True, indent=1, separators=(",", ": ")) with open(filename, "w") as f: f.write(SHORT_VERSION_PY % contents) print("set %s to '%s'" % (filename, versions["version"])) def plus_or_dot(pieces): """Return a + if we don't already have one, else return a .""" if "+" in pieces.get("closest-tag", ""): return "." return "+" def render_pep440(pieces): """Build up version string, with post-release "local version identifier". Our goal: TAG[+DISTANCE.gHEX[.dirty]] . Note that if you get a tagged build and then dirty it, you'll get TAG+0.gHEX.dirty Exceptions: 1: no tags. git_describe was just HEX. 0+untagged.DISTANCE.gHEX[.dirty] """ if pieces["closest-tag"]: rendered = pieces["closest-tag"] if pieces["distance"] or pieces["dirty"]: rendered += plus_or_dot(pieces) rendered += "%d.g%s" % (pieces["distance"], pieces["short"]) if pieces["dirty"]: rendered += ".dirty" else: # exception #1 rendered = "0+untagged.%d.g%s" % (pieces["distance"], pieces["short"]) if pieces["dirty"]: rendered += ".dirty" return rendered def render_pep440_pre(pieces): """TAG[.post.devDISTANCE] -- No -dirty. Exceptions: 1: no tags. 0.post.devDISTANCE """ if pieces["closest-tag"]: rendered = pieces["closest-tag"] if pieces["distance"]: rendered += ".post.dev%d" % pieces["distance"] else: # exception #1 rendered = "0.post.dev%d" % pieces["distance"] return rendered def render_pep440_post(pieces): """TAG[.postDISTANCE[.dev0]+gHEX] . The ".dev0" means dirty. Note that .dev0 sorts backwards (a dirty tree will appear "older" than the corresponding clean one), but you shouldn't be releasing software with -dirty anyways. Exceptions: 1: no tags. 0.postDISTANCE[.dev0] """ if pieces["closest-tag"]: rendered = pieces["closest-tag"] if pieces["distance"] or pieces["dirty"]: rendered += ".post%d" % pieces["distance"] if pieces["dirty"]: rendered += ".dev0" rendered += plus_or_dot(pieces) rendered += "g%s" % pieces["short"] else: # exception #1 rendered = "0.post%d" % pieces["distance"] if pieces["dirty"]: rendered += ".dev0" rendered += "+g%s" % pieces["short"] return rendered def render_pep440_old(pieces): """TAG[.postDISTANCE[.dev0]] . The ".dev0" means dirty. Eexceptions: 1: no tags. 0.postDISTANCE[.dev0] """ if pieces["closest-tag"]: rendered = pieces["closest-tag"] if pieces["distance"] or pieces["dirty"]: rendered += ".post%d" % pieces["distance"] if pieces["dirty"]: rendered += ".dev0" else: # exception #1 rendered = "0.post%d" % pieces["distance"] if pieces["dirty"]: rendered += ".dev0" return rendered def render_git_describe(pieces): """TAG[-DISTANCE-gHEX][-dirty]. Like 'git describe --tags --dirty --always'. Exceptions: 1: no tags. HEX[-dirty] (note: no 'g' prefix) """ if pieces["closest-tag"]: rendered = pieces["closest-tag"] if pieces["distance"]: rendered += "-%d-g%s" % (pieces["distance"], pieces["short"]) else: # exception #1 rendered = pieces["short"] if pieces["dirty"]: rendered += "-dirty" return rendered def render_git_describe_long(pieces): """TAG-DISTANCE-gHEX[-dirty]. Like 'git describe --tags --dirty --always -long'. The distance/hash is unconditional. Exceptions: 1: no tags. HEX[-dirty] (note: no 'g' prefix) """ if pieces["closest-tag"]: rendered = pieces["closest-tag"] rendered += "-%d-g%s" % (pieces["distance"], pieces["short"]) else: # exception #1 rendered = pieces["short"] if pieces["dirty"]: rendered += "-dirty" return rendered def render(pieces, style): """Render the given version pieces into the requested style.""" if pieces["error"]: return {"version": "unknown", "full-revisionid": pieces.get("long"), "dirty": None, "error": pieces["error"], "date": None} if not style or style == "default": style = "pep440" # the default if style == "pep440": rendered = render_pep440(pieces) elif style == "pep440-pre": rendered = render_pep440_pre(pieces) elif style == "pep440-post": rendered = render_pep440_post(pieces) elif style == "pep440-old": rendered = render_pep440_old(pieces) elif style == "git-describe": rendered = render_git_describe(pieces) elif style == "git-describe-long": rendered = render_git_describe_long(pieces) else: raise ValueError("unknown style '%s'" % style) return {"version": rendered, "full-revisionid": pieces["long"], "dirty": pieces["dirty"], "error": None, "date": pieces.get("date")} class VersioneerBadRootError(Exception): """The project root directory is unknown or missing key files.""" def get_versions(verbose=False): """Get the project version from whatever source is available. Returns dict with two keys: 'version' and 'full'. """ if "versioneer" in sys.modules: # see the discussion in cmdclass.py:get_cmdclass() del sys.modules["versioneer"] root = get_root() cfg = get_config_from_root(root) assert cfg.VCS is not None, "please set [versioneer]VCS= in setup.cfg" handlers = HANDLERS.get(cfg.VCS) assert handlers, "unrecognized VCS '%s'" % cfg.VCS verbose = verbose or cfg.verbose assert cfg.versionfile_source is not None, \ "please set versioneer.versionfile_source" assert cfg.tag_prefix is not None, "please set versioneer.tag_prefix" versionfile_abs = os.path.join(root, cfg.versionfile_source) # extract version from first of: _version.py, VCS command (e.g. 'git # describe'), parentdir. This is meant to work for developers using a # source checkout, for users of a tarball created by 'setup.py sdist', # and for users of a tarball/zipball created by 'git archive' or github's # download-from-tag feature or the equivalent in other VCSes. get_keywords_f = handlers.get("get_keywords") from_keywords_f = handlers.get("keywords") if get_keywords_f and from_keywords_f: try: keywords = get_keywords_f(versionfile_abs) ver = from_keywords_f(keywords, cfg.tag_prefix, verbose) if verbose: print("got version from expanded keyword %s" % ver) return ver except NotThisMethod: pass try: ver = versions_from_file(versionfile_abs) if verbose: print("got version from file %s %s" % (versionfile_abs, ver)) return ver except NotThisMethod: pass from_vcs_f = handlers.get("pieces_from_vcs") if from_vcs_f: try: pieces = from_vcs_f(cfg.tag_prefix, root, verbose) ver = render(pieces, cfg.style) if verbose: print("got version from VCS %s" % ver) return ver except NotThisMethod: pass try: if cfg.parentdir_prefix: ver = versions_from_parentdir(cfg.parentdir_prefix, root, verbose) if verbose: print("got version from parentdir %s" % ver) return ver except NotThisMethod: pass if verbose: print("unable to compute version") return {"version": "0+unknown", "full-revisionid": None, "dirty": None, "error": "unable to compute version", "date": None} def get_version(): """Get the short version string for this project.""" return get_versions()["version"] def get_cmdclass(): """Get the custom setuptools/distutils subclasses used by Versioneer.""" if "versioneer" in sys.modules: del sys.modules["versioneer"] # this fixes the "python setup.py develop" case (also 'install' and # 'easy_install .'), in which subdependencies of the main project are # built (using setup.py bdist_egg) in the same python process. Assume # a main project A and a dependency B, which use different versions # of Versioneer. A's setup.py imports A's Versioneer, leaving it in # sys.modules by the time B's setup.py is executed, causing B to run # with the wrong versioneer. Setuptools wraps the sub-dep builds in a # sandbox that restores sys.modules to it's pre-build state, so the # parent is protected against the child's "import versioneer". By # removing ourselves from sys.modules here, before the child build # happens, we protect the child from the parent's versioneer too. # Also see https://github.com/warner/python-versioneer/issues/52 cmds = {} # we add "version" to both distutils and setuptools from distutils.core import Command class cmd_version(Command): description = "report generated version string" user_options = [] boolean_options = [] def initialize_options(self): pass def finalize_options(self): pass def run(self): vers = get_versions(verbose=True) print("Version: %s" % vers["version"]) print(" full-revisionid: %s" % vers.get("full-revisionid")) print(" dirty: %s" % vers.get("dirty")) print(" date: %s" % vers.get("date")) if vers["error"]: print(" error: %s" % vers["error"]) cmds["version"] = cmd_version # we override "build_py" in both distutils and setuptools # # most invocation pathways end up running build_py: # distutils/build -> build_py # distutils/install -> distutils/build ->.. # setuptools/bdist_wheel -> distutils/install ->.. # setuptools/bdist_egg -> distutils/install_lib -> build_py # setuptools/install -> bdist_egg ->.. # setuptools/develop -> ? # pip install: # copies source tree to a tempdir before running egg_info/etc # if .git isn't copied too, 'git describe' will fail # then does setup.py bdist_wheel, or sometimes setup.py install # setup.py egg_info -> ? # we override different "build_py" commands for both environments if "setuptools" in sys.modules: from setuptools.command.build_py import build_py as _build_py else: from distutils.command.build_py import build_py as _build_py class cmd_build_py(_build_py): def run(self): root = get_root() cfg = get_config_from_root(root) versions = get_versions() _build_py.run(self) # now locate _version.py in the new build/ directory and replace # it with an updated value if cfg.versionfile_build: target_versionfile = os.path.join(self.build_lib, cfg.versionfile_build) print("UPDATING %s" % target_versionfile) write_to_version_file(target_versionfile, versions) cmds["build_py"] = cmd_build_py if "cx_Freeze" in sys.modules: # cx_freeze enabled? from cx_Freeze.dist import build_exe as _build_exe # nczeczulin reports that py2exe won't like the pep440-style string # as FILEVERSION, but it can be used for PRODUCTVERSION, e.g. # setup(console=[{ # "version": versioneer.get_version().split("+", 1)[0], # FILEVERSION # "product_version": versioneer.get_version(), # ... class cmd_build_exe(_build_exe): def run(self): root = get_root() cfg = get_config_from_root(root) versions = get_versions() target_versionfile = cfg.versionfile_source print("UPDATING %s" % target_versionfile) write_to_version_file(target_versionfile, versions) _build_exe.run(self) os.unlink(target_versionfile) with open(cfg.versionfile_source, "w") as f: LONG = LONG_VERSION_PY[cfg.VCS] f.write(LONG % {"DOLLAR": "$", "STYLE": cfg.style, "TAG_PREFIX": cfg.tag_prefix, "PARENTDIR_PREFIX": cfg.parentdir_prefix, "VERSIONFILE_SOURCE": cfg.versionfile_source, }) cmds["build_exe"] = cmd_build_exe del cmds["build_py"] if 'py2exe' in sys.modules: # py2exe enabled? try: from py2exe.distutils_buildexe import py2exe as _py2exe # py3 except ImportError: from py2exe.build_exe import py2exe as _py2exe # py2 class cmd_py2exe(_py2exe): def run(self): root = get_root() cfg = get_config_from_root(root) versions = get_versions() target_versionfile = cfg.versionfile_source print("UPDATING %s" % target_versionfile) write_to_version_file(target_versionfile, versions) _py2exe.run(self) os.unlink(target_versionfile) with open(cfg.versionfile_source, "w") as f: LONG = LONG_VERSION_PY[cfg.VCS] f.write(LONG % {"DOLLAR": "$", "STYLE": cfg.style, "TAG_PREFIX": cfg.tag_prefix, "PARENTDIR_PREFIX": cfg.parentdir_prefix, "VERSIONFILE_SOURCE": cfg.versionfile_source, }) cmds["py2exe"] = cmd_py2exe # we override different "sdist" commands for both environments if "setuptools" in sys.modules: from setuptools.command.sdist import sdist as _sdist else: from distutils.command.sdist import sdist as _sdist class cmd_sdist(_sdist): def run(self): versions = get_versions() self._versioneer_generated_versions = versions # unless we update this, the command will keep using the old # version self.distribution.metadata.version = versions["version"] return _sdist.run(self) def make_release_tree(self, base_dir, files): root = get_root() cfg = get_config_from_root(root) _sdist.make_release_tree(self, base_dir, files) # now locate _version.py in the new base_dir directory # (remembering that it may be a hardlink) and replace it with an # updated value target_versionfile = os.path.join(base_dir, cfg.versionfile_source) print("UPDATING %s" % target_versionfile) write_to_version_file(target_versionfile, self._versioneer_generated_versions) cmds["sdist"] = cmd_sdist return cmds CONFIG_ERROR = """ setup.cfg is missing the necessary Versioneer configuration. You need a section like: [versioneer] VCS = git style = pep440 versionfile_source = src/myproject/_version.py versionfile_build = myproject/_version.py tag_prefix = parentdir_prefix = myproject- You will also need to edit your setup.py to use the results: import versioneer setup(version=versioneer.get_version(), cmdclass=versioneer.get_cmdclass(), ...) Please read the docstring in ./versioneer.py for configuration instructions, edit setup.cfg, and re-run the installer or 'python versioneer.py setup'. """ SAMPLE_CONFIG = """ # See the docstring in versioneer.py for instructions. Note that you must # re-run 'versioneer.py setup' after changing this section, and commit the # resulting files. [versioneer] #VCS = git #style = pep440 #versionfile_source = #versionfile_build = #tag_prefix = #parentdir_prefix = """ INIT_PY_SNIPPET = """ from ._version import get_versions __version__ = get_versions()['version'] del get_versions """ def do_setup(): """Main VCS-independent setup function for installing Versioneer.""" root = get_root() try: cfg = get_config_from_root(root) except (EnvironmentError, configparser.NoSectionError, configparser.NoOptionError) as e: if isinstance(e, (EnvironmentError, configparser.NoSectionError)): print("Adding sample versioneer config to setup.cfg", file=sys.stderr) with open(os.path.join(root, "setup.cfg"), "a") as f: f.write(SAMPLE_CONFIG) print(CONFIG_ERROR, file=sys.stderr) return 1 print(" creating %s" % cfg.versionfile_source) with open(cfg.versionfile_source, "w") as f: LONG = LONG_VERSION_PY[cfg.VCS] f.write(LONG % {"DOLLAR": "$", "STYLE": cfg.style, "TAG_PREFIX": cfg.tag_prefix, "PARENTDIR_PREFIX": cfg.parentdir_prefix, "VERSIONFILE_SOURCE": cfg.versionfile_source, }) ipy = os.path.join(os.path.dirname(cfg.versionfile_source), "__init__.py") if os.path.exists(ipy): try: with open(ipy, "r") as f: old = f.read() except EnvironmentError: old = "" if INIT_PY_SNIPPET not in old: print(" appending to %s" % ipy) with open(ipy, "a") as f: f.write(INIT_PY_SNIPPET) else: print(" %s unmodified" % ipy) else: print(" %s doesn't exist, ok" % ipy) ipy = None # Make sure both the top-level "versioneer.py" and versionfile_source # (PKG/_version.py, used by runtime code) are in MANIFEST.in, so # they'll be copied into source distributions. Pip won't be able to # install the package without this. manifest_in = os.path.join(root, "MANIFEST.in") simple_includes = set() try: with open(manifest_in, "r") as f: for line in f: if line.startswith("include "): for include in line.split()[1:]: simple_includes.add(include) except EnvironmentError: pass # That doesn't cover everything MANIFEST.in can do # (http://docs.python.org/2/distutils/sourcedist.html#commands), so # it might give some false negatives. Appending redundant 'include' # lines is safe, though. if "versioneer.py" not in simple_includes: print(" appending 'versioneer.py' to MANIFEST.in") with open(manifest_in, "a") as f: f.write("include versioneer.py\n") else: print(" 'versioneer.py' already in MANIFEST.in") if cfg.versionfile_source not in simple_includes: print(" appending versionfile_source ('%s') to MANIFEST.in" % cfg.versionfile_source) with open(manifest_in, "a") as f: f.write("include %s\n" % cfg.versionfile_source) else: print(" versionfile_source already in MANIFEST.in") # Make VCS-specific changes. For git, this means creating/changing # .gitattributes to mark _version.py for export-subst keyword # substitution. do_vcs_install(manifest_in, cfg.versionfile_source, ipy) return 0 def scan_setup_py(): """Validate the contents of setup.py against Versioneer's expectations.""" found = set() setters = False errors = 0 with open("setup.py", "r") as f: for line in f.readlines(): if "import versioneer" in line: found.add("import") if "versioneer.get_cmdclass()" in line: found.add("cmdclass") if "versioneer.get_version()" in line: found.add("get_version") if "versioneer.VCS" in line: setters = True if "versioneer.versionfile_source" in line: setters = True if len(found) != 3: print("") print("Your setup.py appears to be missing some important items") print("(but I might be wrong). Please make sure it has something") print("roughly like the following:") print("") print(" import versioneer") print(" setup( version=versioneer.get_version(),") print(" cmdclass=versioneer.get_cmdclass(), ...)") print("") errors += 1 if setters: print("You should remove lines like 'versioneer.VCS = ' and") print("'versioneer.versionfile_source = ' . This configuration") print("now lives in setup.cfg, and should be removed from setup.py") print("") errors += 1 return errors if __name__ == "__main__": cmd = sys.argv[1] if cmd == "setup": errors = do_setup() errors += scan_setup_py() if errors: sys.exit(1)