pax_global_header00006660000000000000000000000064146711540260014520gustar00rootroot0000000000000052 comment=a2e59f0e7065404b44dfe92a28aca47ba1378dc4 pybind11-2.13.6/000077500000000000000000000000001467115402600132405ustar00rootroot00000000000000pybind11-2.13.6/.appveyor.yml000066400000000000000000000023671467115402600157160ustar00rootroot00000000000000version: 1.0.{build} image: - Visual Studio 2017 test: off skip_branch_with_pr: true build: parallel: true platform: - x86 environment: matrix: - PYTHON: 38 CONFIG: Debug install: - ps: | $env:CMAKE_GENERATOR = "Visual Studio 15 2017" if ($env:PLATFORM -eq "x64") { $env:PYTHON = "$env:PYTHON-x64" } $env:PATH = "C:\Python$env:PYTHON\;C:\Python$env:PYTHON\Scripts\;$env:PATH" python -W ignore -m pip install --upgrade pip wheel python -W ignore -m pip install pytest numpy --no-warn-script-location pytest-timeout - ps: | Start-FileDownload 'https://gitlab.com/libeigen/eigen/-/archive/3.3.7/eigen-3.3.7.zip' 7z x eigen-3.3.7.zip -y > $null $env:CMAKE_INCLUDE_PATH = "eigen-3.3.7;$env:CMAKE_INCLUDE_PATH" build_script: - cmake -G "%CMAKE_GENERATOR%" -A "%CMAKE_ARCH%" -DCMAKE_CXX_STANDARD=14 -DPYBIND11_WERROR=ON -DDOWNLOAD_CATCH=ON -DCMAKE_SUPPRESS_REGENERATION=1 . - set MSBuildLogger="C:\Program Files\AppVeyor\BuildAgent\Appveyor.MSBuildLogger.dll" - cmake --build . --config %CONFIG% --target pytest -- /m /v:m /logger:%MSBuildLogger% - cmake --build . --config %CONFIG% --target cpptest -- /m /v:m /logger:%MSBuildLogger% on_failure: if exist "tests\test_cmake_build" type tests\test_cmake_build\*.log* pybind11-2.13.6/.clang-format000066400000000000000000000017441467115402600156210ustar00rootroot00000000000000--- # See all possible options and defaults with: # clang-format --style=llvm --dump-config BasedOnStyle: LLVM AccessModifierOffset: -4 AllowShortLambdasOnASingleLine: true AlwaysBreakTemplateDeclarations: Yes BinPackArguments: false BinPackParameters: false BreakBeforeBinaryOperators: All BreakConstructorInitializers: BeforeColon ColumnLimit: 99 CommentPragmas: 'NOLINT:.*|^ IWYU pragma:' IncludeBlocks: Regroup IndentCaseLabels: true IndentPPDirectives: AfterHash IndentWidth: 4 Language: Cpp SpaceAfterCStyleCast: true Standard: Cpp11 StatementMacros: ['PyObject_HEAD'] TabWidth: 4 IncludeCategories: - 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can be solved later, possibly. markup: enable_markup: false pybind11-2.13.6/.codespell-ignore-lines000066400000000000000000000024341467115402600176070ustar00rootroot00000000000000template template auto &this_ = static_cast(*this); if (load_impl(temp, false)) { ssize_t nd = 0; auto trivial = broadcast(buffers, nd, shape); auto ndim = (size_t) nd; int nd; ssize_t ndim() const { return detail::array_proxy(m_ptr)->nd; } using op = op_impl; template template class_ &def(const detail::op_ &op, const Extra &...extra) { class_ &def_cast(const detail::op_ &op, const Extra &...extra) { @pytest.mark.parametrize("access", ["ro", "rw", "static_ro", "static_rw"]) struct IntStruct { explicit IntStruct(int v) : value(v){}; ~IntStruct() { value = -value; } IntStruct(const IntStruct &) = default; IntStruct &operator=(const IntStruct &) = default; py::class_(m, "IntStruct").def(py::init([](const int i) { return IntStruct(i); })); py::implicitly_convertible(); m.def("test", [](int expected, const IntStruct &in) { [](int expected, const IntStruct &in) { pybind11-2.13.6/.gitattributes000066400000000000000000000000221467115402600161250ustar00rootroot00000000000000docs/*.svg binary pybind11-2.13.6/.github/000077500000000000000000000000001467115402600146005ustar00rootroot00000000000000pybind11-2.13.6/.github/CODEOWNERS000066400000000000000000000002661467115402600161770ustar00rootroot00000000000000*.cmake @henryiii CMakeLists.txt @henryiii *.yml @henryiii *.yaml @henryiii /tools/ @henryiii /pybind11/ @henryiii noxfile.py @henryiii .clang-format @henryiii .clang-tidy @henryiii pybind11-2.13.6/.github/CONTRIBUTING.md000066400000000000000000000356651467115402600170500ustar00rootroot00000000000000Thank you for your interest in this project! Please refer to the following sections on how to contribute code and bug reports. ### Reporting bugs Before submitting a question or bug report, please take a moment of your time and ensure that your issue isn't already discussed in the project documentation provided at [pybind11.readthedocs.org][] or in the [issue tracker][]. You can also check [gitter][] to see if it came up before. Assuming that you have identified a previously unknown problem or an important question, it's essential that you submit a self-contained and minimal piece of code that reproduces the problem. In other words: no external dependencies, isolate the function(s) that cause breakage, submit matched and complete C++ and Python snippets that can be easily compiled and run in isolation; or ideally make a small PR with a failing test case that can be used as a starting point. ## Pull requests Contributions are submitted, reviewed, and accepted using GitHub pull requests. Please refer to [this article][using pull requests] for details and adhere to the following rules to make the process as smooth as possible: * Make a new branch for every feature you're working on. * Make small and clean pull requests that are easy to review but make sure they do add value by themselves. * Add tests for any new functionality and run the test suite (`cmake --build build --target pytest`) to ensure that no existing features break. * Please run [`pre-commit`][pre-commit] to check your code matches the project style. (Note that `gawk` is required.) Use `pre-commit run --all-files` before committing (or use installed-mode, check pre-commit docs) to verify your code passes before pushing to save time. * This project has a strong focus on providing general solutions using a minimal amount of code, thus small pull requests are greatly preferred. ### Licensing of contributions pybind11 is provided under a BSD-style license that can be found in the ``LICENSE`` file. By using, distributing, or contributing to this project, you agree to the terms and conditions of this license. You are under no obligation whatsoever to provide any bug fixes, patches, or upgrades to the features, functionality or performance of the source code ("Enhancements") to anyone; however, if you choose to make your Enhancements available either publicly, or directly to the author of this software, without imposing a separate written license agreement for such Enhancements, then you hereby grant the following license: a non-exclusive, royalty-free perpetual license to install, use, modify, prepare derivative works, incorporate into other computer software, distribute, and sublicense such enhancements or derivative works thereof, in binary and source code form. ## Development of pybind11 ### Quick setup To setup a quick development environment, use [`nox`](https://nox.thea.codes). This will allow you to do some common tasks with minimal setup effort, but will take more time to run and be less flexible than a full development environment. If you use [`pipx run nox`](https://pipx.pypa.io), you don't even need to install `nox`. Examples: ```bash # List all available sessions nox -l # Run linters nox -s lint # Run tests on Python 3.9 nox -s tests-3.9 # Build and preview docs nox -s docs -- serve # Build SDists and wheels nox -s build ``` ### Full setup To setup an ideal development environment, run the following commands on a system with CMake 3.14+: ```bash python3 -m venv venv source venv/bin/activate pip install -r tests/requirements.txt cmake -S . -B build -DDOWNLOAD_CATCH=ON -DDOWNLOAD_EIGEN=ON cmake --build build -j4 ``` Tips: * You can use `virtualenv` (faster, from PyPI) instead of `venv`. * You can select any name for your environment folder; if it contains "env" it will be ignored by git. * If you don't have CMake 3.14+, just add "cmake" to the pip install command. * You can use `-DPYBIND11_FINDPYTHON=ON` to use FindPython on CMake 3.12+ * In classic mode, you may need to set `-DPYTHON_EXECUTABLE=/path/to/python`. FindPython uses `-DPython_ROOT_DIR=/path/to` or `-DPython_EXECUTABLE=/path/to/python`. ### Configuration options In CMake, configuration options are given with "-D". Options are stored in the build directory, in the `CMakeCache.txt` file, so they are remembered for each build directory. Two selections are special - the generator, given with `-G`, and the compiler, which is selected based on environment variables `CXX` and similar, or `-DCMAKE_CXX_COMPILER=`. Unlike the others, these cannot be changed after the initial run. The valid options are: * `-DCMAKE_BUILD_TYPE`: Release, Debug, MinSizeRel, RelWithDebInfo * `-DPYBIND11_FINDPYTHON=ON`: Use CMake 3.12+'s FindPython instead of the classic, deprecated, custom FindPythonLibs * `-DPYBIND11_NOPYTHON=ON`: Disable all Python searching (disables tests) * `-DBUILD_TESTING=ON`: Enable the tests * `-DDOWNLOAD_CATCH=ON`: Download catch to build the C++ tests * `-DDOWNLOAD_EIGEN=ON`: Download Eigen for the NumPy tests * `-DPYBIND11_INSTALL=ON/OFF`: Enable the install target (on by default for the master project) * `-DUSE_PYTHON_INSTALL_DIR=ON`: Try to install into the python dir
A few standard CMake tricks: (click to expand)

* Use `cmake --build build -v` to see the commands used to build the files. * Use `cmake build -LH` to list the CMake options with help. * Use `ccmake` if available to see a curses (terminal) gui, or `cmake-gui` for a completely graphical interface (not present in the PyPI package). * Use `cmake --build build -j12` to build with 12 cores (for example). * Use `-G` and the name of a generator to use something different. `cmake --help` lists the generators available. - On Unix, setting `CMAKE_GENERATER=Ninja` in your environment will give you automatic multithreading on all your CMake projects! * Open the `CMakeLists.txt` with QtCreator to generate for that IDE. * You can use `-DCMAKE_EXPORT_COMPILE_COMMANDS=ON` to generate the `.json` file that some tools expect.

To run the tests, you can "build" the check target: ```bash cmake --build build --target check ``` `--target` can be spelled `-t` in CMake 3.15+. You can also run individual tests with these targets: * `pytest`: Python tests only, using the [pytest](https://docs.pytest.org/en/stable/) framework * `cpptest`: C++ tests only * `test_cmake_build`: Install / subdirectory tests If you want to build just a subset of tests, use `-DPYBIND11_TEST_OVERRIDE="test_callbacks;test_pickling"`. If this is empty, all tests will be built. Tests are specified without an extension if they need both a .py and .cpp file. You may also pass flags to the `pytest` target by editing `tests/pytest.ini` or by using the `PYTEST_ADDOPTS` environment variable (see [`pytest` docs](https://docs.pytest.org/en/2.7.3/customize.html#adding-default-options)). As an example: ```bash env PYTEST_ADDOPTS="--capture=no --exitfirst" \ cmake --build build --target pytest # Or using abbreviated flags env PYTEST_ADDOPTS="-s -x" cmake --build build --target pytest ``` ### Formatting All formatting is handled by pre-commit. Install with brew (macOS) or pip (any OS): ```bash # Any OS python3 -m pip install pre-commit # OR macOS with homebrew: brew install pre-commit ``` Then, you can run it on the items you've added to your staging area, or all files: ```bash pre-commit run # OR pre-commit run --all-files ``` And, if you want to always use it, you can install it as a git hook (hence the name, pre-commit): ```bash pre-commit install ``` ### Clang-Format As of v2.6.2, pybind11 ships with a [`clang-format`][clang-format] configuration file at the top level of the repo (the filename is `.clang-format`). Currently, formatting is NOT applied automatically, but manually using `clang-format` for newly developed files is highly encouraged. To check if a file needs formatting: ```bash clang-format -style=file --dry-run some.cpp ``` The output will show things to be fixed, if any. To actually format the file: ```bash clang-format -style=file -i some.cpp ``` Note that the `-style-file` option searches the parent directories for the `.clang-format` file, i.e. the commands above can be run in any subdirectory of the pybind11 repo. ### Clang-Tidy [`clang-tidy`][clang-tidy] performs deeper static code analyses and is more complex to run, compared to `clang-format`, but support for `clang-tidy` is built into the pybind11 CMake configuration. To run `clang-tidy`, the following recipe should work. Run the `docker` command from the top-level directory inside your pybind11 git clone. Files will be modified in place, so you can use git to monitor the changes. ```bash docker run --rm -v $PWD:/mounted_pybind11 -it silkeh/clang:15-bullseye apt-get update && apt-get install -y git python3-dev python3-pytest cmake -S /mounted_pybind11/ -B build -DCMAKE_CXX_CLANG_TIDY="$(which clang-tidy);--use-color" -DDOWNLOAD_EIGEN=ON -DDOWNLOAD_CATCH=ON -DCMAKE_CXX_STANDARD=17 cmake --build build -j 2 ``` You can add `--fix` to the options list if you want. ### Include what you use To run include what you use, install (`brew install include-what-you-use` on macOS), then run: ```bash cmake -S . -B build-iwyu -DCMAKE_CXX_INCLUDE_WHAT_YOU_USE=$(which include-what-you-use) cmake --build build ``` The report is sent to stderr; you can pipe it into a file if you wish. ### Build recipes This builds with the Intel compiler (assuming it is in your path, along with a recent CMake and Python): ```bash python3 -m venv venv . venv/bin/activate pip install pytest cmake -S . -B build-intel -DCMAKE_CXX_COMPILER=$(which icpc) -DDOWNLOAD_CATCH=ON -DDOWNLOAD_EIGEN=ON -DPYBIND11_WERROR=ON ``` This will test the PGI compilers: ```bash docker run --rm -it -v $PWD:/pybind11 nvcr.io/hpc/pgi-compilers:ce apt-get update && apt-get install -y python3-dev python3-pip python3-pytest wget -qO- "https://cmake.org/files/v3.18/cmake-3.18.2-Linux-x86_64.tar.gz" | tar --strip-components=1 -xz -C /usr/local cmake -S pybind11/ -B build cmake --build build ``` ### Explanation of the SDist/wheel building design > These details below are _only_ for packaging the Python sources from git. The > SDists and wheels created do not have any extra requirements at all and are > completely normal. The main objective of the packaging system is to create SDists (Python's source distribution packages) and wheels (Python's binary distribution packages) that include everything that is needed to work with pybind11, and which can be installed without any additional dependencies. This is more complex than it appears: in order to support CMake as a first class language even when using the PyPI package, they must include the _generated_ CMake files (so as not to require CMake when installing the `pybind11` package itself). They should also provide the option to install to the "standard" location (`/include/pybind11` and `/share/cmake/pybind11`) so they are easy to find with CMake, but this can cause problems if you are not an environment or using ``pyproject.toml`` requirements. This was solved by having two packages; the "nice" pybind11 package that stores the includes and CMake files inside the package, that you get access to via functions in the package, and a `pybind11-global` package that can be included via `pybind11[global]` if you want the more invasive but discoverable file locations. If you want to install or package the GitHub source, it is best to have Pip 10 or newer on Windows, macOS, or Linux (manylinux1 compatible, includes most distributions). You can then build the SDists, or run any procedure that makes SDists internally, like making wheels or installing. ```bash # Editable development install example python3 -m pip install -e . ``` Since Pip itself does not have an `sdist` command (it does have `wheel` and `install`), you may want to use the upcoming `build` package: ```bash python3 -m pip install build # Normal package python3 -m build -s . # Global extra PYBIND11_GLOBAL_SDIST=1 python3 -m build -s . ``` If you want to use the classic "direct" usage of `python setup.py`, you will need CMake 3.15+ and either `make` or `ninja` preinstalled (possibly via `pip install cmake ninja`), since directly running Python on `setup.py` cannot pick up and install `pyproject.toml` requirements. As long as you have those two things, though, everything works the way you would expect: ```bash # Normal package python3 setup.py sdist # Global extra PYBIND11_GLOBAL_SDIST=1 python3 setup.py sdist ``` A detailed explanation of the build procedure design for developers wanting to work on or maintain the packaging system is as follows: #### 1. Building from the source directory When you invoke any `setup.py` command from the source directory, including `pip wheel .` and `pip install .`, you will activate a full source build. This is made of the following steps: 1. If the tool is PEP 518 compliant, like Pip 10+, it will create a temporary virtual environment and install the build requirements (mostly CMake) into it. (if you are not on Windows, macOS, or a manylinux compliant system, you can disable this with `--no-build-isolation` as long as you have CMake 3.15+ installed) 2. The environment variable `PYBIND11_GLOBAL_SDIST` is checked - if it is set and truthy, this will be make the accessory `pybind11-global` package, instead of the normal `pybind11` package. This package is used for installing the files directly to your environment root directory, using `pybind11[global]`. 2. `setup.py` reads the version from `pybind11/_version.py` and verifies it matches `includes/pybind11/detail/common.h`. 3. CMake is run with `-DCMAKE_INSTALL_PREIFX=pybind11`. Since the CMake install procedure uses only relative paths and is identical on all platforms, these files are valid as long as they stay in the correct relative position to the includes. `pybind11/share/cmake/pybind11` has the CMake files, and `pybind11/include` has the includes. The build directory is discarded. 4. Simpler files are placed in the SDist: `tools/setup_*.py.in`, `tools/pyproject.toml` (`main` or `global`) 5. The package is created by running the setup function in the `tools/setup_*.py`. `setup_main.py` fills in Python packages, and `setup_global.py` fills in only the data/header slots. 6. A context manager cleans up the temporary CMake install directory (even if an error is thrown). ### 2. Building from SDist Since the SDist has the rendered template files in `tools` along with the includes and CMake files in the correct locations, the builds are completely trivial and simple. No extra requirements are required. You can even use Pip 9 if you really want to. [pre-commit]: https://pre-commit.com [clang-format]: https://clang.llvm.org/docs/ClangFormat.html [clang-tidy]: https://clang.llvm.org/extra/clang-tidy/ [pybind11.readthedocs.org]: http://pybind11.readthedocs.org/en/latest [issue tracker]: https://github.com/pybind/pybind11/issues [gitter]: https://gitter.im/pybind/Lobby [using pull requests]: https://help.github.com/articles/using-pull-requests pybind11-2.13.6/.github/ISSUE_TEMPLATE/000077500000000000000000000000001467115402600167635ustar00rootroot00000000000000pybind11-2.13.6/.github/ISSUE_TEMPLATE/bug-report.yml000066400000000000000000000050011467115402600215700ustar00rootroot00000000000000name: Bug Report description: File an issue about a bug title: "[BUG]: " labels: [triage] body: - type: markdown attributes: value: | Please do your best to make the issue as easy to act on as possible, and only submit here if there is clearly a problem with pybind11 (ask first if unsure). **Note that a reproducer in a PR is much more likely to get immediate attention.** - type: checkboxes id: steps attributes: label: Required prerequisites description: Make sure you've completed the following steps before submitting your issue -- thank you! options: - label: Make sure you've read the [documentation](https://pybind11.readthedocs.io). Your issue may be addressed there. required: true - label: Search the [issue tracker](https://github.com/pybind/pybind11/issues) and [Discussions](https:/pybind/pybind11/discussions) to verify that this hasn't already been reported. +1 or comment there if it has. required: true - label: Consider asking first in the [Gitter chat room](https://gitter.im/pybind/Lobby) or in a [Discussion](https:/pybind/pybind11/discussions/new). required: false - type: input id: version attributes: label: What version (or hash if on master) of pybind11 are you using? validations: required: true - type: textarea id: description attributes: label: Problem description placeholder: >- Provide a short description, state the expected behavior and what actually happens. Include relevant information like what version of pybind11 you are using, what system you are on, and any useful commands / output. validations: required: true - type: textarea id: code attributes: label: Reproducible example code placeholder: >- The code should be minimal, have no external dependencies, isolate the function(s) that cause breakage. Submit matched and complete C++ and Python snippets that can be easily compiled and run to diagnose the issue. — Note that a reproducer in a PR is much more likely to get immediate attention: failing tests in the pybind11 CI are the best starting point for working out fixes. render: text - type: input id: regression attributes: label: Is this a regression? Put the last known working version here if it is. description: Put the last known working version here if this is a regression. value: Not a regression pybind11-2.13.6/.github/ISSUE_TEMPLATE/config.yml000066400000000000000000000005101467115402600207470ustar00rootroot00000000000000blank_issues_enabled: false contact_links: - name: Ask a question url: https://github.com/pybind/pybind11/discussions/new about: Please ask and answer questions here, or propose new ideas. - name: Gitter room url: https://gitter.im/pybind/Lobby about: A room for discussing pybind11 with an active community pybind11-2.13.6/.github/dependabot.yml000066400000000000000000000004711467115402600174320ustar00rootroot00000000000000version: 2 updates: # Maintain dependencies for GitHub Actions - package-ecosystem: "github-actions" directory: "/" schedule: interval: "weekly" groups: actions: patterns: - "*" ignore: - dependency-name: actions/checkout versions: - "<5" pybind11-2.13.6/.github/labeler.yml000066400000000000000000000004471467115402600167360ustar00rootroot00000000000000docs: all: - changed-files: - all-globs-to-all-files: - '!docs/changelog.rst' - '!docs/upgrade.rst' - base-branch: "^(?!dependabot).*" - base-branch: "^(?!pre-commit-ci).*" ci: - changed-files: - any-glob-to-any-file: - '.github/workflows/*.yml' pybind11-2.13.6/.github/labeler_merged.yml000066400000000000000000000005141467115402600202540ustar00rootroot00000000000000# Add 'needs changelog` label to any change to code files as long as the `CHANGELOG` hasn't changed # Skip dependabot and pre-commit-ci PRs needs changelog: - all: - changed-files: - all-globs-to-all-files: "!docs/changelog.rst" - base-branch: "^(?!dependabot).*" - base-branch: "^(?!pre-commit-ci).*" pybind11-2.13.6/.github/matchers/000077500000000000000000000000001467115402600164065ustar00rootroot00000000000000pybind11-2.13.6/.github/matchers/pylint.json000066400000000000000000000012341467115402600206200ustar00rootroot00000000000000{ "problemMatcher": [ { "severity": "warning", "pattern": [ { "regexp": "^([^:]+):(\\d+):(\\d+): ([A-DF-Z]\\d+): \\033\\[[\\d;]+m([^\\033]+).*$", "file": 1, "line": 2, "column": 3, "code": 4, "message": 5 } ], "owner": "pylint-warning" }, { "severity": "error", "pattern": [ { "regexp": "^([^:]+):(\\d+):(\\d+): (E\\d+): \\033\\[[\\d;]+m([^\\033]+).*$", "file": 1, "line": 2, "column": 3, "code": 4, "message": 5 } ], "owner": "pylint-error" } ] } pybind11-2.13.6/.github/pull_request_template.md000066400000000000000000000012051467115402600215370ustar00rootroot00000000000000 ## Description ## Suggested changelog entry: ```rst ``` pybind11-2.13.6/.github/workflows/000077500000000000000000000000001467115402600166355ustar00rootroot00000000000000pybind11-2.13.6/.github/workflows/ci.yml000066400000000000000000001063301467115402600177560ustar00rootroot00000000000000name: CI on: workflow_dispatch: pull_request: push: branches: - master - stable - v* permissions: read-all concurrency: group: test-${{ github.ref }} cancel-in-progress: true env: PIP_BREAK_SYSTEM_PACKAGES: 1 PIP_ONLY_BINARY: numpy FORCE_COLOR: 3 PYTEST_TIMEOUT: 300 # For cmake: VERBOSE: 1 jobs: # This is the "main" test suite, which tests a large number of different # versions of default compilers and Python versions in GitHub Actions. standard: strategy: fail-fast: false matrix: runs-on: [ubuntu-20.04, windows-2022, macos-13] python: - '3.8' - '3.9' - '3.12' - '3.13' - 'pypy-3.8' - 'pypy-3.9' - 'pypy-3.10' # Items in here will either be added to the build matrix (if not # present), or add new keys to an existing matrix element if all the # existing keys match. # # We support an optional key: args, for cmake args include: # Just add a key - runs-on: ubuntu-20.04 python: '3.8' args: > -DPYBIND11_FINDPYTHON=ON -DCMAKE_CXX_FLAGS="-D_=1" exercise_D_: 1 - runs-on: ubuntu-20.04 python: 'pypy-3.8' args: > -DPYBIND11_FINDPYTHON=ON - runs-on: windows-2019 python: '3.8' args: > -DPYBIND11_FINDPYTHON=ON # Inject a couple Windows 2019 runs - runs-on: windows-2019 python: '3.9' # Extra ubuntu latest job - runs-on: ubuntu-latest python: '3.11' name: "🐍 ${{ matrix.python }} • ${{ matrix.runs-on }} • x64 ${{ matrix.args }}" runs-on: ${{ matrix.runs-on }} steps: - uses: actions/checkout@v4 - name: Setup Python ${{ matrix.python }} uses: actions/setup-python@v5 with: python-version: ${{ matrix.python }} allow-prereleases: true - name: Setup Boost (Linux) # Can't use boost + define _ if: runner.os == 'Linux' && matrix.exercise_D_ != 1 run: sudo apt-get install libboost-dev - name: Setup Boost (macOS) if: runner.os == 'macOS' run: brew install boost - name: Update CMake uses: jwlawson/actions-setup-cmake@v2.0 - name: Cache wheels if: runner.os == 'macOS' uses: actions/cache@v4 with: # This path is specific to macOS - we really only need it for PyPy NumPy wheels # See https://github.com/actions/cache/blob/master/examples.md#python---pip # for ways to do this more generally path: ~/Library/Caches/pip # Look to see if there is a cache hit for the corresponding requirements file key: ${{ runner.os }}-pip-${{ matrix.python }}-x64-${{ hashFiles('tests/requirements.txt') }} - name: Prepare env run: | python -m pip install -r tests/requirements.txt - name: Setup annotations on Linux if: runner.os == 'Linux' run: python -m pip install pytest-github-actions-annotate-failures # First build - C++11 mode and inplace # More-or-less randomly adding -DPYBIND11_SIMPLE_GIL_MANAGEMENT=ON here # (same for PYBIND11_NUMPY_1_ONLY, but requires a NumPy 1.x at runtime). - name: Configure C++11 ${{ matrix.args }} run: > cmake -S . -B . -DPYBIND11_WERROR=ON -DPYBIND11_DISABLE_HANDLE_TYPE_NAME_DEFAULT_IMPLEMENTATION=ON -DPYBIND11_SIMPLE_GIL_MANAGEMENT=ON -DPYBIND11_NUMPY_1_ONLY=ON -DDOWNLOAD_CATCH=ON -DDOWNLOAD_EIGEN=ON -DCMAKE_CXX_STANDARD=11 ${{ matrix.args }} - name: Build C++11 run: cmake --build . -j 2 - name: Python tests C++11 run: cmake --build . --target pytest -j 2 - name: C++11 tests run: cmake --build . --target cpptest -j 2 - name: Interface test C++11 run: cmake --build . --target test_cmake_build - name: Clean directory run: git clean -fdx # Second build - C++17 mode and in a build directory # More-or-less randomly adding -DPYBIND11_SIMPLE_GIL_MANAGEMENT=OFF here. # (same for PYBIND11_NUMPY_1_ONLY, but requires a NumPy 1.x at runtime). - name: Configure C++17 run: > cmake -S . -B build2 -DPYBIND11_WERROR=ON -DPYBIND11_SIMPLE_GIL_MANAGEMENT=OFF -DPYBIND11_NUMPY_1_ONLY=ON -DDOWNLOAD_CATCH=ON -DDOWNLOAD_EIGEN=ON -DCMAKE_CXX_STANDARD=17 ${{ matrix.args }} - name: Build run: cmake --build build2 -j 2 - name: Python tests run: cmake --build build2 --target pytest - name: C++ tests run: cmake --build build2 --target cpptest # Third build - C++17 mode with unstable ABI - name: Configure (unstable ABI) run: > cmake -S . -B build3 -DPYBIND11_WERROR=ON -DDOWNLOAD_CATCH=ON -DDOWNLOAD_EIGEN=ON -DCMAKE_CXX_STANDARD=17 -DPYBIND11_INTERNALS_VERSION=10000000 ${{ matrix.args }} - name: Build (unstable ABI) run: cmake --build build3 -j 2 - name: Python tests (unstable ABI) run: cmake --build build3 --target pytest - name: Interface test run: cmake --build build2 --target test_cmake_build # This makes sure the setup_helpers module can build packages using # setuptools - name: Setuptools helpers test run: | pip install setuptools pytest tests/extra_setuptools if: "!(matrix.runs-on == 'windows-2022')" manylinux: name: Manylinux on 🐍 3.13t • GIL runs-on: ubuntu-latest timeout-minutes: 40 container: quay.io/pypa/musllinux_1_2_x86_64:latest steps: - uses: actions/checkout@v4 with: fetch-depth: 0 - name: Prepare venv run: python3.13t -m venv .venv - name: Install Python deps run: .venv/bin/pip install -r tests/requirements.txt - name: Configure C++11 run: > cmake -S. -Bbuild -DPYBIND11_WERROR=ON -DDOWNLOAD_CATCH=ON -DDOWNLOAD_EIGEN=ON -DPython_ROOT_DIR=.venv - name: Build C++11 run: cmake --build build -j2 - name: Python tests C++11 run: cmake --build build --target pytest -j2 deadsnakes: strategy: fail-fast: false matrix: include: # TODO: Fails on 3.10, investigate # JOB DISABLED (NEEDS WORK): https://github.com/pybind/pybind11/issues/4889 # - python-version: "3.9" # python-debug: true # valgrind: true - python-version: "3.11" python-debug: false name: "🐍 ${{ matrix.python-version }}${{ matrix.python-debug && '-dbg' || '' }} (deadsnakes)${{ matrix.valgrind && ' • Valgrind' || '' }} • x64" runs-on: ubuntu-20.04 steps: - uses: actions/checkout@v4 - name: Setup Python ${{ matrix.python-version }} (deadsnakes) uses: deadsnakes/action@v3.2.0 with: python-version: ${{ matrix.python-version }} debug: ${{ matrix.python-debug }} - name: Update CMake uses: jwlawson/actions-setup-cmake@v2.0 - name: Valgrind cache if: matrix.valgrind uses: actions/cache@v4 id: cache-valgrind with: path: valgrind key: 3.16.1 # Valgrind version - name: Compile Valgrind if: matrix.valgrind && steps.cache-valgrind.outputs.cache-hit != 'true' run: | VALGRIND_VERSION=3.16.1 curl https://sourceware.org/pub/valgrind/valgrind-$VALGRIND_VERSION.tar.bz2 -o - | tar xj mv valgrind-$VALGRIND_VERSION valgrind cd valgrind ./configure make -j 2 > /dev/null - name: Install Valgrind if: matrix.valgrind working-directory: valgrind run: | sudo make install sudo apt-get update sudo apt-get install libc6-dbg # Needed by Valgrind - name: Prepare env run: | python -m pip install -r tests/requirements.txt - name: Configure run: > cmake -S . -B build -DCMAKE_BUILD_TYPE=Debug -DPYBIND11_WERROR=ON -DDOWNLOAD_CATCH=ON -DDOWNLOAD_EIGEN=ON -DCMAKE_CXX_STANDARD=17 - name: Build run: cmake --build build -j 2 - name: Python tests run: cmake --build build --target pytest - name: C++ tests run: cmake --build build --target cpptest - name: Run Valgrind on Python tests if: matrix.valgrind run: cmake --build build --target memcheck # Testing on clang using the excellent silkeh clang docker images clang: runs-on: ubuntu-latest strategy: fail-fast: false matrix: clang: - 3.6 - 3.7 - 3.9 - 7 - 9 - dev std: - 11 container_suffix: - "" include: - clang: 5 std: 14 - clang: 10 std: 17 - clang: 11 std: 20 - clang: 12 std: 20 - clang: 13 std: 20 - clang: 14 std: 20 - clang: 15 std: 20 container_suffix: "-bullseye" - clang: 16 std: 20 container_suffix: "-bullseye" - clang: 17 std: 20 container_suffix: "-bookworm" - clang: 18 std: 20 container_suffix: "-bookworm" name: "🐍 3 • Clang ${{ matrix.clang }} • C++${{ matrix.std }} • x64" container: "silkeh/clang:${{ matrix.clang }}${{ matrix.container_suffix }}" steps: - uses: actions/checkout@v4 - name: Add wget and python3 run: apt-get update && apt-get install -y python3-dev python3-numpy python3-pytest libeigen3-dev - name: Configure shell: bash run: > cmake -S . -B build -DPYBIND11_WERROR=ON -DDOWNLOAD_CATCH=ON -DCMAKE_CXX_STANDARD=${{ matrix.std }} -DPYTHON_EXECUTABLE=$(python3 -c "import sys; print(sys.executable)") - name: Build run: cmake --build build -j 2 - name: Python tests run: cmake --build build --target pytest - name: C++ tests run: cmake --build build --target cpptest - name: Interface test run: cmake --build build --target test_cmake_build # Testing NVCC; forces sources to behave like .cu files cuda: runs-on: ubuntu-latest name: "🐍 3.10 • CUDA 12.2 • Ubuntu 22.04" container: nvidia/cuda:12.2.0-devel-ubuntu22.04 steps: - uses: actions/checkout@v4 # tzdata will try to ask for the timezone, so set the DEBIAN_FRONTEND - name: Install 🐍 3 run: apt-get update && DEBIAN_FRONTEND="noninteractive" apt-get install -y cmake git python3-dev python3-pytest python3-numpy - name: Configure run: cmake -S . -B build -DPYBIND11_CUDA_TESTS=ON -DPYBIND11_WERROR=ON -DDOWNLOAD_CATCH=ON - name: Build run: cmake --build build -j2 --verbose - name: Python tests run: cmake --build build --target pytest # TODO: Internal compiler error - report to NVidia # # Testing CentOS 8 + PGI compilers # centos-nvhpc8: # runs-on: ubuntu-latest # name: "🐍 3 • CentOS8 / PGI 20.11 • x64" # container: centos:8 # # steps: # - uses: actions/checkout@v4 # # - name: Add Python 3 and a few requirements # run: yum update -y && yum install -y git python3-devel python3-numpy python3-pytest make environment-modules # # - name: Install CMake with pip # run: | # python3 -m pip install --upgrade pip # python3 -m pip install cmake --prefer-binary # # - name: Install NVidia HPC SDK # run: > # yum -y install # https://developer.download.nvidia.com/hpc-sdk/20.11/nvhpc-20-11-20.11-1.x86_64.rpm # https://developer.download.nvidia.com/hpc-sdk/20.11/nvhpc-2020-20.11-1.x86_64.rpm # # - name: Configure # shell: bash # run: | # source /etc/profile.d/modules.sh # module load /opt/nvidia/hpc_sdk/modulefiles/nvhpc/20.11 # cmake -S . -B build -DDOWNLOAD_CATCH=ON -DCMAKE_CXX_STANDARD=14 -DPYTHON_EXECUTABLE=$(python3 -c "import sys; print(sys.executable)") # # - name: Build # run: cmake --build build -j 2 --verbose # # - name: Python tests # run: cmake --build build --target pytest # # - name: C++ tests # run: cmake --build build --target cpptest # # - name: Interface test # run: cmake --build build --target test_cmake_build # Testing on Ubuntu + NVHPC (previous PGI) compilers, which seems to require more workarounds ubuntu-nvhpc7: runs-on: ubuntu-20.04 name: "🐍 3 • NVHPC 23.5 • C++17 • x64" env: # tzdata will try to ask for the timezone, so set the DEBIAN_FRONTEND DEBIAN_FRONTEND: 'noninteractive' steps: - uses: actions/checkout@v4 - name: Add NVHPC Repo run: | echo 'deb [trusted=yes] https://developer.download.nvidia.com/hpc-sdk/ubuntu/amd64 /' | \ sudo tee /etc/apt/sources.list.d/nvhpc.list - name: Install 🐍 3 & NVHPC run: | sudo apt-get update -y && \ sudo apt-get install -y cmake environment-modules git python3-dev python3-pip python3-numpy && \ sudo apt-get install -y --no-install-recommends nvhpc-23-5 && \ sudo rm -rf /var/lib/apt/lists/* python3 -m pip install --upgrade pip python3 -m pip install --upgrade pytest # On some systems, you many need further workarounds: # https://github.com/pybind/pybind11/pull/2475 - name: Configure shell: bash run: | source /etc/profile.d/modules.sh module load /opt/nvidia/hpc_sdk/modulefiles/nvhpc/23.5 cmake -S . -B build -DDOWNLOAD_CATCH=ON \ -DCMAKE_CXX_STANDARD=17 \ -DPYTHON_EXECUTABLE=$(python3 -c "import sys; print(sys.executable)") \ -DCMAKE_CXX_FLAGS="-Wc,--pending_instantiations=0" \ -DPYBIND11_TEST_FILTER="test_smart_ptr.cpp" - name: Build run: cmake --build build -j 2 --verbose - name: Python tests run: cmake --build build --target pytest - name: C++ tests run: cmake --build build --target cpptest - name: Interface test run: cmake --build build --target test_cmake_build # Testing on GCC using the GCC docker images (only recent images supported) gcc: runs-on: ubuntu-latest strategy: fail-fast: false matrix: include: - { gcc: 7, std: 11 } - { gcc: 7, std: 17 } - { gcc: 8, std: 14 } - { gcc: 8, std: 17 } - { gcc: 9, std: 20 } - { gcc: 10, std: 17 } - { gcc: 10, std: 20 } - { gcc: 11, std: 20 } - { gcc: 12, std: 20 } - { gcc: 13, std: 20 } name: "🐍 3 • GCC ${{ matrix.gcc }} • C++${{ matrix.std }}• x64" container: "gcc:${{ matrix.gcc }}" steps: - uses: actions/checkout@v4 - name: Add Python 3 run: apt-get update; apt-get install -y python3-dev python3-numpy python3-pytest python3-pip libeigen3-dev - name: Update pip run: python3 -m pip install --upgrade pip - name: Update CMake uses: jwlawson/actions-setup-cmake@v2.0 - name: Configure shell: bash run: > cmake -S . -B build -DPYBIND11_WERROR=ON -DDOWNLOAD_CATCH=ON -DCMAKE_CXX_STANDARD=${{ matrix.std }} -DPYTHON_EXECUTABLE=$(python3 -c "import sys; print(sys.executable)") - name: Build run: cmake --build build -j 2 - name: Python tests run: cmake --build build --target pytest - name: C++ tests run: cmake --build build --target cpptest - name: Interface test run: cmake --build build --target test_cmake_build - name: Configure - Exercise cmake -DPYBIND11_TEST_OVERRIDE if: matrix.gcc == '12' shell: bash run: > cmake -S . -B build_partial -DPYBIND11_WERROR=ON -DDOWNLOAD_CATCH=ON -DCMAKE_CXX_STANDARD=${{ matrix.std }} -DPYTHON_EXECUTABLE=$(python3 -c "import sys; print(sys.executable)") "-DPYBIND11_TEST_OVERRIDE=test_call_policies.cpp;test_gil_scoped.cpp;test_thread.cpp" - name: Build - Exercise cmake -DPYBIND11_TEST_OVERRIDE if: matrix.gcc == '12' run: cmake --build build_partial -j 2 - name: Python tests - Exercise cmake -DPYBIND11_TEST_OVERRIDE if: matrix.gcc == '12' run: cmake --build build_partial --target pytest # Testing on ICC using the oneAPI apt repo icc: runs-on: ubuntu-20.04 name: "🐍 3 • ICC latest • x64" steps: - uses: actions/checkout@v4 - name: Add apt repo run: | sudo apt-get update sudo apt-get install -y wget build-essential pkg-config cmake ca-certificates gnupg wget https://apt.repos.intel.com/intel-gpg-keys/GPG-PUB-KEY-INTEL-SW-PRODUCTS-2023.PUB sudo apt-key add GPG-PUB-KEY-INTEL-SW-PRODUCTS-2023.PUB echo "deb https://apt.repos.intel.com/oneapi all main" | sudo tee /etc/apt/sources.list.d/oneAPI.list - name: Add ICC & Python 3 run: sudo apt-get update; sudo apt-get install -y intel-oneapi-compiler-dpcpp-cpp-and-cpp-classic cmake python3-dev python3-numpy python3-pytest python3-pip - name: Update pip run: | set +e; source /opt/intel/oneapi/setvars.sh; set -e python3 -m pip install --upgrade pip - name: Install dependencies run: | set +e; source /opt/intel/oneapi/setvars.sh; set -e python3 -m pip install -r tests/requirements.txt - name: Configure C++11 run: | set +e; source /opt/intel/oneapi/setvars.sh; set -e cmake -S . -B build-11 \ -DPYBIND11_WERROR=ON \ -DDOWNLOAD_CATCH=ON \ -DDOWNLOAD_EIGEN=OFF \ -DCMAKE_CXX_STANDARD=11 \ -DCMAKE_CXX_COMPILER=$(which icpc) \ -DPYTHON_EXECUTABLE=$(python3 -c "import sys; print(sys.executable)") - name: Build C++11 run: | set +e; source /opt/intel/oneapi/setvars.sh; set -e cmake --build build-11 -j 2 -v - name: Python tests C++11 run: | set +e; source /opt/intel/oneapi/setvars.sh; set -e sudo service apport stop cmake --build build-11 --target check - name: C++ tests C++11 run: | set +e; source /opt/intel/oneapi/setvars.sh; set -e cmake --build build-11 --target cpptest - name: Interface test C++11 run: | set +e; source /opt/intel/oneapi/setvars.sh; set -e cmake --build build-11 --target test_cmake_build - name: Configure C++17 run: | set +e; source /opt/intel/oneapi/setvars.sh; set -e cmake -S . -B build-17 \ -DPYBIND11_WERROR=ON \ -DDOWNLOAD_CATCH=ON \ -DDOWNLOAD_EIGEN=OFF \ -DCMAKE_CXX_STANDARD=17 \ -DCMAKE_CXX_COMPILER=$(which icpc) \ -DPYTHON_EXECUTABLE=$(python3 -c "import sys; print(sys.executable)") - name: Build C++17 run: | set +e; source /opt/intel/oneapi/setvars.sh; set -e cmake --build build-17 -j 2 -v - name: Python tests C++17 run: | set +e; source /opt/intel/oneapi/setvars.sh; set -e sudo service apport stop cmake --build build-17 --target check - name: C++ tests C++17 run: | set +e; source /opt/intel/oneapi/setvars.sh; set -e cmake --build build-17 --target cpptest - name: Interface test C++17 run: | set +e; source /opt/intel/oneapi/setvars.sh; set -e cmake --build build-17 --target test_cmake_build # Testing on CentOS (manylinux uses a centos base). centos: runs-on: ubuntu-latest strategy: fail-fast: false matrix: container: - "almalinux:8" - "almalinux:9" name: "🐍 3 • ${{ matrix.container }} • x64" container: "${{ matrix.container }}" steps: - name: Latest actions/checkout uses: actions/checkout@v4 - name: Add Python 3.8 if: matrix.container == 'almalinux:8' run: dnf update -y && dnf install -y python38-devel gcc-c++ make git - name: Add Python 3 (default) if: matrix.container != 'almalinux:8' run: dnf update -y && dnf install -y python3-devel gcc-c++ make git - name: Update pip run: python3 -m pip install --upgrade pip - name: Install dependencies run: | python3 -m pip install cmake -r tests/requirements.txt - name: Ensure NumPy 2 is used (required Python >= 3.9) if: matrix.container == 'almalinux:9' run: | python3 -m pip install 'numpy>=2.0.0b1' 'scipy>=1.13.0rc1' - name: Configure shell: bash run: > cmake -S . -B build -DCMAKE_BUILD_TYPE=MinSizeRel -DPYBIND11_WERROR=ON -DDOWNLOAD_CATCH=ON -DDOWNLOAD_EIGEN=ON -DCMAKE_CXX_STANDARD=11 -DPYTHON_EXECUTABLE=$(python3 -c "import sys; print(sys.executable)") - name: Build run: cmake --build build -j 2 - name: Python tests run: cmake --build build --target pytest - name: C++ tests run: cmake --build build --target cpptest - name: Interface test run: cmake --build build --target test_cmake_build # This tests an "install" with the CMake tools install-classic: name: "🐍 3.7 • Debian • x86 • Install" runs-on: ubuntu-latest container: i386/debian:buster steps: - uses: actions/checkout@v1 # v1 is required to run inside docker - name: Install requirements run: | apt-get update apt-get install -y git make cmake g++ libeigen3-dev python3-dev python3-pip pip3 install "pytest==6.*" - name: Configure for install run: > cmake . -DPYBIND11_INSTALL=1 -DPYBIND11_TEST=0 -DPYTHON_EXECUTABLE=$(python3 -c "import sys; print(sys.executable)") - name: Make and install run: make install - name: Copy tests to new directory run: cp -a tests /pybind11-tests - name: Make a new test directory run: mkdir /build-tests - name: Configure tests run: > cmake ../pybind11-tests -DDOWNLOAD_CATCH=ON -DPYBIND11_WERROR=ON -DPYTHON_EXECUTABLE=$(python3 -c "import sys; print(sys.executable)") working-directory: /build-tests - name: Python tests run: make pytest -j 2 working-directory: /build-tests # This verifies that the documentation is not horribly broken, and does a # basic validation check on the SDist. doxygen: name: "Documentation build test" runs-on: ubuntu-latest steps: - uses: actions/checkout@v4 - uses: actions/setup-python@v5 with: python-version: "3.x" - name: Install Doxygen run: sudo apt-get install -y doxygen librsvg2-bin # Changed to rsvg-convert in 20.04 - name: Build docs run: pipx run nox -s docs - name: Make SDist run: pipx run nox -s build -- --sdist - run: git status --ignored - name: Check local include dir run: > ls pybind11; python3 -c "import pybind11, pathlib; assert (a := pybind11.get_include()) == (b := str(pathlib.Path('include').resolve())), f'{a} != {b}'" - name: Compare Dists (headers only) working-directory: include run: | python3 -m pip install --user -U ../dist/*.tar.gz installed=$(python3 -c "import pybind11; print(pybind11.get_include() + '/pybind11')") diff -rq $installed ./pybind11 win32: strategy: fail-fast: false matrix: python: - '3.7' - '3.8' - '3.9' - '3.10' - '3.11' - '3.12' include: - python: '3.12' args: -DCMAKE_CXX_STANDARD=20 - python: '3.11' args: -DCMAKE_CXX_STANDARD=20 - python: '3.10' args: -DCMAKE_CXX_STANDARD=20 - python: '3.9' args: -DCMAKE_CXX_STANDARD=20 - python: '3.8' args: -DCMAKE_CXX_STANDARD=17 - python: '3.7' args: -DCMAKE_CXX_STANDARD=14 name: "🐍 ${{ matrix.python }} • MSVC 2019 • x86 ${{ matrix.args }}" runs-on: windows-2019 steps: - uses: actions/checkout@v4 - name: Setup Python ${{ matrix.python }} uses: actions/setup-python@v5 with: python-version: ${{ matrix.python }} architecture: x86 - name: Update CMake uses: jwlawson/actions-setup-cmake@v2.0 - name: Prepare MSVC uses: ilammy/msvc-dev-cmd@v1.13.0 with: arch: x86 - name: Prepare env run: | python -m pip install -r tests/requirements.txt # First build - C++11 mode and inplace - name: Configure ${{ matrix.args }} run: > cmake -S . -B build -G "Visual Studio 16 2019" -A Win32 -DPYBIND11_WERROR=ON -DDOWNLOAD_CATCH=ON -DDOWNLOAD_EIGEN=ON ${{ matrix.args }} - name: Build C++11 run: cmake --build build -j 2 - name: Python tests run: cmake --build build -t pytest win32-debug: strategy: fail-fast: false matrix: python: - 3.8 - 3.9 include: - python: 3.9 args: -DCMAKE_CXX_STANDARD=20 - python: 3.8 args: -DCMAKE_CXX_STANDARD=17 name: "🐍 ${{ matrix.python }} • MSVC 2019 (Debug) • x86 ${{ matrix.args }}" runs-on: windows-2019 steps: - uses: actions/checkout@v4 - name: Setup Python ${{ matrix.python }} uses: actions/setup-python@v5 with: python-version: ${{ matrix.python }} architecture: x86 - name: Update CMake uses: jwlawson/actions-setup-cmake@v2.0 - name: Prepare MSVC uses: ilammy/msvc-dev-cmd@v1.13.0 with: arch: x86 - name: Prepare env run: | python -m pip install -r tests/requirements.txt # First build - C++11 mode and inplace - name: Configure ${{ matrix.args }} run: > cmake -S . -B build -G "Visual Studio 16 2019" -A Win32 -DCMAKE_BUILD_TYPE=Debug -DPYBIND11_WERROR=ON -DDOWNLOAD_CATCH=ON -DDOWNLOAD_EIGEN=ON ${{ matrix.args }} - name: Build C++11 run: cmake --build build --config Debug -j 2 - name: Python tests run: cmake --build build --config Debug -t pytest windows-2022: strategy: fail-fast: false matrix: python: - 3.9 name: "🐍 ${{ matrix.python }} • MSVC 2022 C++20 • x64" runs-on: windows-2022 steps: - uses: actions/checkout@v4 - name: Setup Python ${{ matrix.python }} uses: actions/setup-python@v5 with: python-version: ${{ matrix.python }} - name: Prepare env # Ensure use of NumPy 2 (via NumPy nightlies but can be changed soon) run: | python3 -m pip install -r tests/requirements.txt python3 -m pip install 'numpy>=2.0.0b1' 'scipy>=1.13.0rc1' - name: Update CMake uses: jwlawson/actions-setup-cmake@v2.0 - name: Configure C++20 run: > cmake -S . -B build -DPYBIND11_WERROR=ON -DDOWNLOAD_CATCH=ON -DDOWNLOAD_EIGEN=ON -DCMAKE_CXX_STANDARD=20 - name: Build C++20 run: cmake --build build -j 2 - name: Python tests run: cmake --build build --target pytest - name: C++20 tests run: cmake --build build --target cpptest -j 2 - name: Interface test C++20 run: cmake --build build --target test_cmake_build - name: Configure C++20 - Exercise cmake -DPYBIND11_TEST_OVERRIDE run: > cmake -S . -B build_partial -DPYBIND11_WERROR=ON -DDOWNLOAD_CATCH=ON -DDOWNLOAD_EIGEN=ON -DCMAKE_CXX_STANDARD=20 "-DPYBIND11_TEST_OVERRIDE=test_call_policies.cpp;test_gil_scoped.cpp;test_thread.cpp" - name: Build C++20 - Exercise cmake -DPYBIND11_TEST_OVERRIDE run: cmake --build build_partial -j 2 - name: Python tests - Exercise cmake -DPYBIND11_TEST_OVERRIDE run: cmake --build build_partial --target pytest mingw: name: "🐍 3 • windows-latest • ${{ matrix.sys }}" runs-on: windows-latest defaults: run: shell: msys2 {0} strategy: fail-fast: false matrix: include: - { sys: mingw64, env: x86_64 } - { sys: mingw32, env: i686 } steps: - uses: msys2/setup-msys2@v2 with: msystem: ${{matrix.sys}} install: >- git mingw-w64-${{matrix.env}}-gcc mingw-w64-${{matrix.env}}-python-pip mingw-w64-${{matrix.env}}-python-numpy mingw-w64-${{matrix.env}}-cmake mingw-w64-${{matrix.env}}-make mingw-w64-${{matrix.env}}-python-pytest mingw-w64-${{matrix.env}}-boost mingw-w64-${{matrix.env}}-catch - uses: msys2/setup-msys2@v2 if: matrix.sys == 'mingw64' with: msystem: ${{matrix.sys}} install: >- git mingw-w64-${{matrix.env}}-python-scipy mingw-w64-${{matrix.env}}-eigen3 - uses: actions/checkout@v4 - name: Configure C++11 # LTO leads to many undefined reference like # `pybind11::detail::function_call::function_call(pybind11::detail::function_call&&) run: >- cmake -G "MinGW Makefiles" -DCMAKE_CXX_STANDARD=11 -DPYBIND11_WERROR=ON -DDOWNLOAD_CATCH=ON -DPYTHON_EXECUTABLE=$(python -c "import sys; print(sys.executable)") -S . -B build - name: Build C++11 run: cmake --build build -j 2 - name: Python tests C++11 run: cmake --build build --target pytest -j 2 - name: C++11 tests run: PYTHONHOME=/${{matrix.sys}} PYTHONPATH=/${{matrix.sys}} cmake --build build --target cpptest -j 2 - name: Interface test C++11 run: PYTHONHOME=/${{matrix.sys}} PYTHONPATH=/${{matrix.sys}} cmake --build build --target test_cmake_build - name: Clean directory run: git clean -fdx - name: Configure C++14 run: >- cmake -G "MinGW Makefiles" -DCMAKE_CXX_STANDARD=14 -DPYBIND11_WERROR=ON -DDOWNLOAD_CATCH=ON -DPYTHON_EXECUTABLE=$(python -c "import sys; print(sys.executable)") -S . -B build2 - name: Build C++14 run: cmake --build build2 -j 2 - name: Python tests C++14 run: cmake --build build2 --target pytest -j 2 - name: C++14 tests run: PYTHONHOME=/${{matrix.sys}} PYTHONPATH=/${{matrix.sys}} cmake --build build2 --target cpptest -j 2 - name: Interface test C++14 run: PYTHONHOME=/${{matrix.sys}} PYTHONPATH=/${{matrix.sys}} cmake --build build2 --target test_cmake_build - name: Clean directory run: git clean -fdx - name: Configure C++17 run: >- cmake -G "MinGW Makefiles" -DCMAKE_CXX_STANDARD=17 -DPYBIND11_WERROR=ON -DDOWNLOAD_CATCH=ON -DPYTHON_EXECUTABLE=$(python -c "import sys; print(sys.executable)") -S . -B build3 - name: Build C++17 run: cmake --build build3 -j 2 - name: Python tests C++17 run: cmake --build build3 --target pytest -j 2 - name: C++17 tests run: PYTHONHOME=/${{matrix.sys}} PYTHONPATH=/${{matrix.sys}} cmake --build build3 --target cpptest -j 2 - name: Interface test C++17 run: PYTHONHOME=/${{matrix.sys}} PYTHONPATH=/${{matrix.sys}} cmake --build build3 --target test_cmake_build windows_clang: strategy: matrix: os: [windows-latest] python: ['3.10'] runs-on: "${{ matrix.os }}" name: "🐍 ${{ matrix.python }} • ${{ matrix.os }} • clang-latest" steps: - name: Show env run: env - name: Checkout uses: actions/checkout@v4 - name: Set up Clang uses: egor-tensin/setup-clang@v1 - name: Setup Python ${{ matrix.python }} uses: actions/setup-python@v5 with: python-version: ${{ matrix.python }} - name: Update CMake uses: jwlawson/actions-setup-cmake@v2.0 - name: Install ninja-build tool uses: seanmiddleditch/gha-setup-ninja@v5 - name: Run pip installs run: | python -m pip install --upgrade pip python -m pip install -r tests/requirements.txt - name: Show Clang++ version run: clang++ --version - name: Show CMake version run: cmake --version # TODO: WERROR=ON - name: Configure Clang run: > cmake -G Ninja -S . -B . -DPYBIND11_WERROR=OFF -DPYBIND11_SIMPLE_GIL_MANAGEMENT=OFF -DDOWNLOAD_CATCH=ON -DDOWNLOAD_EIGEN=ON -DCMAKE_CXX_COMPILER=clang++ -DCMAKE_CXX_STANDARD=17 - name: Build run: cmake --build . -j 2 - name: Python tests run: cmake --build . --target pytest -j 2 - name: C++ tests run: cmake --build . --target cpptest -j 2 - name: Interface test run: cmake --build . --target test_cmake_build -j 2 - name: Clean directory run: git clean -fdx macos_brew_install_llvm: name: "macos-13 • brew install llvm" runs-on: macos-13 env: # https://apple.stackexchange.com/questions/227026/how-to-install-recent-clang-with-homebrew LDFLAGS: '-L/usr/local/opt/llvm/lib -Wl,-rpath,/usr/local/opt/llvm/lib' steps: - name: Update PATH run: echo "/usr/local/opt/llvm/bin" >> $GITHUB_PATH - name: Show env run: env - name: Checkout uses: actions/checkout@v4 - name: Show Clang++ version before brew install llvm run: clang++ --version - name: brew install llvm run: brew install llvm - name: Show Clang++ version after brew install llvm run: clang++ --version - name: Update CMake uses: jwlawson/actions-setup-cmake@v2.0 - name: Run pip installs run: | python3 -m pip install --upgrade pip python3 -m pip install -r tests/requirements.txt python3 -m pip install numpy python3 -m pip install scipy - name: Show CMake version run: cmake --version - name: CMake Configure run: > cmake -S . -B . -DPYBIND11_WERROR=ON -DPYBIND11_SIMPLE_GIL_MANAGEMENT=OFF -DDOWNLOAD_CATCH=ON -DDOWNLOAD_EIGEN=ON -DCMAKE_CXX_COMPILER=clang++ -DCMAKE_CXX_STANDARD=17 -DPYTHON_EXECUTABLE=$(python3 -c "import sys; print(sys.executable)") - name: Build run: cmake --build . -j 2 - name: Python tests run: cmake --build . --target pytest -j 2 - name: C++ tests run: cmake --build . --target cpptest -j 2 - name: Interface test run: cmake --build . --target test_cmake_build -j 2 - name: CMake Configure - Exercise cmake -DPYBIND11_TEST_OVERRIDE run: > cmake -S . -B build_partial -DPYBIND11_WERROR=ON -DPYBIND11_SIMPLE_GIL_MANAGEMENT=OFF -DDOWNLOAD_CATCH=ON -DDOWNLOAD_EIGEN=ON -DCMAKE_CXX_COMPILER=clang++ -DCMAKE_CXX_STANDARD=17 -DPYTHON_EXECUTABLE=$(python3 -c "import sys; print(sys.executable)") "-DPYBIND11_TEST_OVERRIDE=test_call_policies.cpp;test_gil_scoped.cpp;test_thread.cpp" - name: Build - Exercise cmake -DPYBIND11_TEST_OVERRIDE run: cmake --build build_partial -j 2 - name: Python tests - Exercise cmake -DPYBIND11_TEST_OVERRIDE run: cmake --build build_partial --target pytest -j 2 - name: Clean directory run: git clean -fdx pybind11-2.13.6/.github/workflows/configure.yml000066400000000000000000000043271467115402600213470ustar00rootroot00000000000000name: Config on: workflow_dispatch: pull_request: push: branches: - master - stable - v* permissions: contents: read env: PIP_BREAK_SYSTEM_PACKAGES: 1 # For cmake: VERBOSE: 1 jobs: # This tests various versions of CMake in various combinations, to make sure # the configure step passes. cmake: strategy: fail-fast: false matrix: runs-on: [ubuntu-20.04, macos-13, windows-latest] arch: [x64] cmake: ["3.26"] include: - runs-on: ubuntu-20.04 arch: x64 cmake: "3.5" - runs-on: ubuntu-20.04 arch: x64 cmake: "3.29" - runs-on: macos-13 arch: x64 cmake: "3.7" - runs-on: windows-2019 arch: x64 # x86 compilers seem to be missing on 2019 image cmake: "3.18" name: 🐍 3.7 • CMake ${{ matrix.cmake }} • ${{ matrix.runs-on }} runs-on: ${{ matrix.runs-on }} steps: - uses: actions/checkout@v4 - name: Setup Python 3.7 uses: actions/setup-python@v5 with: python-version: 3.7 architecture: ${{ matrix.arch }} - name: Prepare env run: python -m pip install -r tests/requirements.txt # An action for adding a specific version of CMake: # https://github.com/jwlawson/actions-setup-cmake - name: Setup CMake ${{ matrix.cmake }} uses: jwlawson/actions-setup-cmake@v2.0 with: cmake-version: ${{ matrix.cmake }} # These steps use a directory with a space in it intentionally - name: Make build directories run: mkdir "build dir" - name: Configure working-directory: build dir shell: bash run: > cmake .. -DPYBIND11_WERROR=ON -DDOWNLOAD_CATCH=ON -DPYTHON_EXECUTABLE=$(python -c "import sys; print(sys.executable)") # Only build and test if this was manually triggered in the GitHub UI - name: Build working-directory: build dir if: github.event_name == 'workflow_dispatch' run: cmake --build . --config Release - name: Test working-directory: build dir if: github.event_name == 'workflow_dispatch' run: cmake --build . --config Release --target check pybind11-2.13.6/.github/workflows/emscripten.yaml000066400000000000000000000010411467115402600216660ustar00rootroot00000000000000name: WASM on: workflow_dispatch: pull_request: branches: - master - stable - v* concurrency: group: ${{ github.workflow }}-${{ github.ref }} cancel-in-progress: true jobs: build-wasm-emscripten: name: Pyodide wheel runs-on: ubuntu-22.04 steps: - uses: actions/checkout@v4 with: submodules: true fetch-depth: 0 - uses: pypa/cibuildwheel@v2.20 env: PYODIDE_BUILD_EXPORTS: whole_archive with: package-dir: tests only: cp312-pyodide_wasm32 pybind11-2.13.6/.github/workflows/format.yml000066400000000000000000000027231467115402600206540ustar00rootroot00000000000000# This is a format job. Pre-commit has a first-party GitHub action, so we use # that: https://github.com/pre-commit/action name: Format on: workflow_dispatch: pull_request: push: branches: - master - stable - "v*" permissions: contents: read env: FORCE_COLOR: 3 # For cmake: VERBOSE: 1 jobs: pre-commit: name: Format runs-on: ubuntu-latest steps: - uses: actions/checkout@v4 - uses: actions/setup-python@v5 with: python-version: "3.x" - name: Add matchers run: echo "::add-matcher::$GITHUB_WORKSPACE/.github/matchers/pylint.json" - uses: pre-commit/action@v3.0.1 with: # Slow hooks are marked with manual - slow is okay here, run them too extra_args: --hook-stage manual --all-files clang-tidy: # When making changes here, please also review the "Clang-Tidy" section # in .github/CONTRIBUTING.md and update as needed. name: Clang-Tidy runs-on: ubuntu-latest container: silkeh/clang:18-bookworm steps: - uses: actions/checkout@v4 - name: Install requirements run: apt-get update && apt-get install -y git python3-dev python3-pytest - name: Configure run: > cmake -S . -B build -DCMAKE_CXX_CLANG_TIDY="$(which clang-tidy);--use-color;--warnings-as-errors=*" -DDOWNLOAD_EIGEN=ON -DDOWNLOAD_CATCH=ON -DCMAKE_CXX_STANDARD=17 - name: Build run: cmake --build build -j 2 -- --keep-going pybind11-2.13.6/.github/workflows/labeler.yml000066400000000000000000000011771467115402600207740ustar00rootroot00000000000000name: Labeler on: pull_request_target: types: [closed] permissions: {} jobs: label: name: Labeler runs-on: ubuntu-latest permissions: contents: read pull-requests: write steps: - uses: actions/labeler@v5 if: > github.event.pull_request.merged == true && !startsWith(github.event.pull_request.title, 'chore(deps):') && !startsWith(github.event.pull_request.title, 'ci(fix):') && !startsWith(github.event.pull_request.title, 'docs(changelog):') with: repo-token: ${{ secrets.GITHUB_TOKEN }} configuration-path: .github/labeler_merged.yml pybind11-2.13.6/.github/workflows/pip.yml000066400000000000000000000053021467115402600201500ustar00rootroot00000000000000name: Pip on: workflow_dispatch: pull_request: push: branches: - master - stable - v* release: types: - published permissions: contents: read env: PIP_BREAK_SYSTEM_PACKAGES: 1 PIP_ONLY_BINARY: numpy jobs: # This builds the sdists and wheels and makes sure the files are exactly as # expected. test-packaging: name: 🐍 3.8 • 📦 tests • windows-latest runs-on: windows-latest steps: - uses: actions/checkout@v4 - name: Setup 🐍 3.8 uses: actions/setup-python@v5 with: python-version: 3.8 - name: Prepare env run: | python -m pip install -r tests/requirements.txt - name: Python Packaging tests run: pytest tests/extra_python_package/ # This runs the packaging tests and also builds and saves the packages as # artifacts. packaging: name: 🐍 3.8 • 📦 & 📦 tests • ubuntu-latest runs-on: ubuntu-latest steps: - uses: actions/checkout@v4 - name: Setup 🐍 3.8 uses: actions/setup-python@v5 with: python-version: 3.8 - name: Prepare env run: | python -m pip install -r tests/requirements.txt build twine - name: Python Packaging tests run: pytest tests/extra_python_package/ - name: Build SDist and wheels run: | python -m build PYBIND11_GLOBAL_SDIST=1 python -m build - name: Check metadata run: twine check dist/* - name: Save standard package uses: actions/upload-artifact@v4 with: name: standard path: dist/pybind11-* - name: Save global package uses: actions/upload-artifact@v4 with: name: global path: dist/pybind11_global-* # When a GitHub release is made, upload the artifacts to PyPI upload: name: Upload to PyPI runs-on: ubuntu-latest if: github.event_name == 'release' && github.event.action == 'published' needs: [packaging] environment: name: pypi url: https://pypi.org/p/pybind11 permissions: id-token: write attestations: write steps: # Downloads all to directories matching the artifact names - uses: actions/download-artifact@v4 - name: Generate artifact attestation for sdist and wheel uses: actions/attest-build-provenance@1c608d11d69870c2092266b3f9a6f3abbf17002c # v1.4.3 with: subject-path: "*/pybind11*" - name: Publish standard package uses: pypa/gh-action-pypi-publish@release/v1 with: packages-dir: standard/ attestations: true - name: Publish global package uses: pypa/gh-action-pypi-publish@release/v1 with: packages-dir: global/ attestations: true pybind11-2.13.6/.github/workflows/upstream.yml000066400000000000000000000054741467115402600212320ustar00rootroot00000000000000name: Upstream on: workflow_dispatch: pull_request: permissions: contents: read concurrency: group: upstream-${{ github.ref }} cancel-in-progress: true env: PIP_BREAK_SYSTEM_PACKAGES: 1 # For cmake: VERBOSE: 1 jobs: standard: name: "🐍 3.13 latest • ubuntu-latest • x64" runs-on: ubuntu-latest # Only runs when the 'python dev' label is selected if: "contains(github.event.pull_request.labels.*.name, 'python dev')" steps: - uses: actions/checkout@v4 - name: Setup Python 3.13 uses: actions/setup-python@v5 with: python-version: "3.13" allow-prereleases: true - name: Setup Boost run: sudo apt-get install libboost-dev - name: Update CMake uses: jwlawson/actions-setup-cmake@v2.0 - name: Run pip installs run: | python -m pip install --upgrade pip python -m pip install -r tests/requirements.txt - name: Show platform info run: | python -m platform cmake --version pip list # First build - C++11 mode and inplace - name: Configure C++11 run: > cmake -S . -B build11 -DPYBIND11_WERROR=ON -DDOWNLOAD_CATCH=ON -DDOWNLOAD_EIGEN=ON -DCMAKE_CXX_STANDARD=11 -DCMAKE_BUILD_TYPE=Debug - name: Build C++11 run: cmake --build build11 -j 2 - name: Python tests C++11 run: cmake --build build11 --target pytest -j 2 - name: C++11 tests run: cmake --build build11 --target cpptest -j 2 - name: Interface test C++11 run: cmake --build build11 --target test_cmake_build # Second build - C++17 mode and in a build directory - name: Configure C++17 run: > cmake -S . -B build17 -DPYBIND11_WERROR=ON -DDOWNLOAD_CATCH=ON -DDOWNLOAD_EIGEN=ON -DCMAKE_CXX_STANDARD=17 - name: Build C++17 run: cmake --build build17 -j 2 - name: Python tests C++17 run: cmake --build build17 --target pytest - name: C++17 tests run: cmake --build build17 --target cpptest # Third build - C++17 mode with unstable ABI - name: Configure (unstable ABI) run: > cmake -S . -B build17max -DPYBIND11_WERROR=ON -DDOWNLOAD_CATCH=ON -DDOWNLOAD_EIGEN=ON -DCMAKE_CXX_STANDARD=17 -DPYBIND11_INTERNALS_VERSION=10000000 - name: Build (unstable ABI) run: cmake --build build17max -j 2 - name: Python tests (unstable ABI) run: cmake --build build17max --target pytest - name: Interface test (unstable ABI) run: cmake --build build17max --target test_cmake_build # This makes sure the setup_helpers module can build packages using # setuptools - name: Setuptools helpers test run: | pip install setuptools pytest tests/extra_setuptools pybind11-2.13.6/.gitignore000066400000000000000000000007661467115402600152410ustar00rootroot00000000000000CMakeCache.txt CMakeFiles Makefile cmake_install.cmake cmake_uninstall.cmake .DS_Store *.so *.pyd *.dll *.sln *.sdf *.opensdf *.vcxproj *.vcxproj.user *.filters example.dir Win32 x64 Release Debug .vs CTestTestfile.cmake Testing autogen MANIFEST /.ninja_* /*.ninja /docs/.build *.py[co] *.egg-info *~ .*.swp .DS_Store /dist /*build* .cache/ sosize-*.txt pybind11Config*.cmake pybind11Targets.cmake /*env* /.vscode /pybind11/include/* /pybind11/share/* /docs/_build/* .ipynb_checkpoints/ tests/main.cpp pybind11-2.13.6/.pre-commit-config.yaml000066400000000000000000000071661467115402600175330ustar00rootroot00000000000000# To use: # # pre-commit run -a # # Or: # # pre-commit install # (runs every time you commit in git) # # To update this file: # # pre-commit autoupdate # # See https://github.com/pre-commit/pre-commit ci: autoupdate_commit_msg: "chore(deps): update pre-commit hooks" autofix_commit_msg: "style: pre-commit fixes" autoupdate_schedule: monthly # third-party content exclude: ^tools/JoinPaths.cmake$ repos: # Clang format the codebase automatically - repo: https://github.com/pre-commit/mirrors-clang-format rev: "v18.1.8" hooks: - id: clang-format types_or: [c++, c, cuda] # Ruff, the Python auto-correcting linter/formatter written in Rust - repo: https://github.com/astral-sh/ruff-pre-commit rev: v0.6.3 hooks: - id: ruff args: ["--fix", "--show-fixes"] - id: ruff-format # Check static types with mypy - repo: https://github.com/pre-commit/mirrors-mypy rev: "v1.11.2" hooks: - id: mypy args: [] exclude: ^(tests|docs)/ additional_dependencies: - markdown-it-py - nox - rich - types-setuptools # CMake formatting - repo: https://github.com/cheshirekow/cmake-format-precommit rev: "v0.6.13" hooks: - id: cmake-format additional_dependencies: [pyyaml] types: [file] files: (\.cmake|CMakeLists.txt)(.in)?$ # Standard hooks - repo: https://github.com/pre-commit/pre-commit-hooks rev: "v4.6.0" hooks: - id: check-added-large-files - id: check-case-conflict - id: check-docstring-first - id: check-merge-conflict - id: check-symlinks - id: check-toml - id: check-yaml - id: debug-statements - id: end-of-file-fixer - id: mixed-line-ending - id: requirements-txt-fixer - id: trailing-whitespace # Also code format the docs - repo: https://github.com/adamchainz/blacken-docs rev: "1.18.0" hooks: - id: blacken-docs additional_dependencies: - black==23.* # Changes tabs to spaces - repo: https://github.com/Lucas-C/pre-commit-hooks rev: "v1.5.5" hooks: - id: remove-tabs # Avoid directional quotes - repo: https://github.com/sirosen/texthooks rev: "0.6.7" hooks: - id: fix-ligatures - id: fix-smartquotes # Checking for common mistakes - repo: https://github.com/pre-commit/pygrep-hooks rev: "v1.10.0" hooks: - id: rst-backticks - id: rst-directive-colons - id: rst-inline-touching-normal # Checks the manifest for missing files (native support) - repo: https://github.com/mgedmin/check-manifest rev: "0.49" hooks: - id: check-manifest # This is a slow hook, so only run this if --hook-stage manual is passed stages: [manual] additional_dependencies: [cmake, ninja] # Check for spelling # Use tools/codespell_ignore_lines_from_errors.py # to rebuild .codespell-ignore-lines - repo: https://github.com/codespell-project/codespell rev: "v2.3.0" hooks: - id: codespell exclude: ".supp$" args: ["-x.codespell-ignore-lines", "-Lccompiler,intstruct"] # Check for common shell mistakes - repo: https://github.com/shellcheck-py/shellcheck-py rev: "v0.10.0.1" hooks: - id: shellcheck # Disallow some common capitalization mistakes - repo: local hooks: - id: disallow-caps name: Disallow improper capitalization language: pygrep entry: PyBind|\bNumpy\b|Cmake|CCache|PyTest exclude: ^\.pre-commit-config.yaml$ # PyLint has native support - not always usable, but works for us - repo: https://github.com/PyCQA/pylint rev: "v3.2.7" hooks: - id: pylint files: ^pybind11 # Check schemas on some of our YAML files - repo: https://github.com/python-jsonschema/check-jsonschema rev: 0.29.2 hooks: - id: check-readthedocs - id: check-github-workflows - id: check-dependabot pybind11-2.13.6/.readthedocs.yml000066400000000000000000000004241467115402600163260ustar00rootroot00000000000000# https://blog.readthedocs.com/migrate-configuration-v2/ version: 2 build: os: ubuntu-22.04 apt_packages: - librsvg2-bin tools: python: "3.11" sphinx: configuration: docs/conf.py python: install: - requirements: docs/requirements.txt formats: - pdf pybind11-2.13.6/CMakeLists.txt000066400000000000000000000337111467115402600160050ustar00rootroot00000000000000# CMakeLists.txt -- Build system for the pybind11 modules # # Copyright (c) 2015 Wenzel Jakob # # All rights reserved. Use of this source code is governed by a # BSD-style license that can be found in the LICENSE file. # Propagate this policy (FindPythonInterp removal) so it can be detected later if(NOT CMAKE_VERSION VERSION_LESS "3.27") cmake_policy(GET CMP0148 _pybind11_cmp0148) endif() cmake_minimum_required(VERSION 3.5) # The `cmake_minimum_required(VERSION 3.5...3.29)` syntax does not work with # some versions of VS that have a patched CMake 3.11. This forces us to emulate # the behavior using the following workaround: if(${CMAKE_VERSION} VERSION_LESS 3.29) cmake_policy(VERSION ${CMAKE_MAJOR_VERSION}.${CMAKE_MINOR_VERSION}) else() cmake_policy(VERSION 3.29) endif() if(_pybind11_cmp0148) cmake_policy(SET CMP0148 ${_pybind11_cmp0148}) unset(_pybind11_cmp0148) endif() # Avoid infinite recursion if tests include this as a subdirectory if(DEFINED PYBIND11_MASTER_PROJECT) return() endif() # Extract project version from source file(STRINGS "${CMAKE_CURRENT_SOURCE_DIR}/include/pybind11/detail/common.h" pybind11_version_defines REGEX "#define PYBIND11_VERSION_(MAJOR|MINOR|PATCH) ") foreach(ver ${pybind11_version_defines}) if(ver MATCHES [[#define PYBIND11_VERSION_(MAJOR|MINOR|PATCH) +([^ ]+)$]]) set(PYBIND11_VERSION_${CMAKE_MATCH_1} "${CMAKE_MATCH_2}") endif() endforeach() if(PYBIND11_VERSION_PATCH MATCHES [[\.([a-zA-Z0-9]+)$]]) set(pybind11_VERSION_TYPE "${CMAKE_MATCH_1}") endif() string(REGEX MATCH "^[0-9]+" PYBIND11_VERSION_PATCH "${PYBIND11_VERSION_PATCH}") project( pybind11 LANGUAGES CXX VERSION "${PYBIND11_VERSION_MAJOR}.${PYBIND11_VERSION_MINOR}.${PYBIND11_VERSION_PATCH}") # Standard includes include(GNUInstallDirs) include(CMakePackageConfigHelpers) include(CMakeDependentOption) if(NOT pybind11_FIND_QUIETLY) message(STATUS "pybind11 v${pybind11_VERSION} ${pybind11_VERSION_TYPE}") endif() # Check if pybind11 is being used directly or via add_subdirectory if(CMAKE_SOURCE_DIR STREQUAL PROJECT_SOURCE_DIR) ### Warn if not an out-of-source builds if(CMAKE_CURRENT_SOURCE_DIR STREQUAL CMAKE_CURRENT_BINARY_DIR) set(lines "You are building in-place. If that is not what you intended to " "do, you can clean the source directory with:\n" "rm -r CMakeCache.txt CMakeFiles/ cmake_uninstall.cmake pybind11Config.cmake " "pybind11ConfigVersion.cmake tests/CMakeFiles/\n") message(AUTHOR_WARNING ${lines}) endif() set(PYBIND11_MASTER_PROJECT ON) if(OSX AND CMAKE_VERSION VERSION_LESS 3.7) # Bug in macOS CMake < 3.7 is unable to download catch message(WARNING "CMAKE 3.7+ needed on macOS to download catch, and newer HIGHLY recommended") elseif(WINDOWS AND CMAKE_VERSION VERSION_LESS 3.8) # Only tested with 3.8+ in CI. message(WARNING "CMAKE 3.8+ tested on Windows, previous versions untested") endif() message(STATUS "CMake ${CMAKE_VERSION}") if(CMAKE_CXX_STANDARD) set(CMAKE_CXX_EXTENSIONS OFF) set(CMAKE_CXX_STANDARD_REQUIRED ON) endif() set(pybind11_system "") set_property(GLOBAL PROPERTY USE_FOLDERS ON) if(CMAKE_VERSION VERSION_LESS "3.18") set(_pybind11_findpython_default OFF) else() set(_pybind11_findpython_default ON) endif() else() set(PYBIND11_MASTER_PROJECT OFF) set(pybind11_system SYSTEM) set(_pybind11_findpython_default OFF) endif() # Options option(PYBIND11_INSTALL "Install pybind11 header files?" ${PYBIND11_MASTER_PROJECT}) option(PYBIND11_TEST "Build pybind11 test suite?" ${PYBIND11_MASTER_PROJECT}) option(PYBIND11_NOPYTHON "Disable search for Python" OFF) option(PYBIND11_DISABLE_HANDLE_TYPE_NAME_DEFAULT_IMPLEMENTATION "To enforce that a handle_type_name<> specialization exists" OFF) option(PYBIND11_SIMPLE_GIL_MANAGEMENT "Use simpler GIL management logic that does not support disassociation" OFF) option(PYBIND11_NUMPY_1_ONLY "Disable NumPy 2 support to avoid changes to previous pybind11 versions." OFF) set(PYBIND11_INTERNALS_VERSION "" CACHE STRING "Override the ABI version, may be used to enable the unstable ABI.") option(PYBIND11_USE_CROSSCOMPILING "Respect CMAKE_CROSSCOMPILING" OFF) if(PYBIND11_DISABLE_HANDLE_TYPE_NAME_DEFAULT_IMPLEMENTATION) add_compile_definitions(PYBIND11_DISABLE_HANDLE_TYPE_NAME_DEFAULT_IMPLEMENTATION) endif() if(PYBIND11_SIMPLE_GIL_MANAGEMENT) add_compile_definitions(PYBIND11_SIMPLE_GIL_MANAGEMENT) endif() if(PYBIND11_NUMPY_1_ONLY) add_compile_definitions(PYBIND11_NUMPY_1_ONLY) endif() cmake_dependent_option( USE_PYTHON_INCLUDE_DIR "Install pybind11 headers in Python include directory instead of default installation prefix" OFF "PYBIND11_INSTALL" OFF) cmake_dependent_option(PYBIND11_FINDPYTHON "Force new FindPython" ${_pybind11_findpython_default} "NOT CMAKE_VERSION VERSION_LESS 3.12" OFF) # Allow PYTHON_EXECUTABLE if in FINDPYTHON mode and building pybind11's tests # (makes transition easier while we support both modes). if(PYBIND11_MASTER_PROJECT AND PYBIND11_FINDPYTHON AND DEFINED PYTHON_EXECUTABLE AND NOT DEFINED Python_EXECUTABLE) set(Python_EXECUTABLE "${PYTHON_EXECUTABLE}") endif() # NB: when adding a header don't forget to also add it to setup.py set(PYBIND11_HEADERS include/pybind11/detail/class.h include/pybind11/detail/common.h include/pybind11/detail/cpp_conduit.h include/pybind11/detail/descr.h include/pybind11/detail/init.h include/pybind11/detail/internals.h include/pybind11/detail/type_caster_base.h include/pybind11/detail/typeid.h include/pybind11/detail/value_and_holder.h include/pybind11/detail/exception_translation.h include/pybind11/attr.h include/pybind11/buffer_info.h include/pybind11/cast.h include/pybind11/chrono.h include/pybind11/common.h include/pybind11/complex.h include/pybind11/options.h include/pybind11/eigen.h include/pybind11/eigen/common.h include/pybind11/eigen/matrix.h include/pybind11/eigen/tensor.h include/pybind11/embed.h include/pybind11/eval.h include/pybind11/gil.h include/pybind11/gil_safe_call_once.h include/pybind11/iostream.h include/pybind11/functional.h include/pybind11/numpy.h include/pybind11/operators.h include/pybind11/pybind11.h include/pybind11/pytypes.h include/pybind11/stl.h include/pybind11/stl_bind.h include/pybind11/stl/filesystem.h include/pybind11/type_caster_pyobject_ptr.h include/pybind11/typing.h) # Compare with grep and warn if mismatched if(PYBIND11_MASTER_PROJECT AND NOT CMAKE_VERSION VERSION_LESS 3.12) file( GLOB_RECURSE _pybind11_header_check LIST_DIRECTORIES false RELATIVE "${CMAKE_CURRENT_SOURCE_DIR}" CONFIGURE_DEPENDS "include/pybind11/*.h") set(_pybind11_here_only ${PYBIND11_HEADERS}) set(_pybind11_disk_only ${_pybind11_header_check}) list(REMOVE_ITEM _pybind11_here_only ${_pybind11_header_check}) list(REMOVE_ITEM _pybind11_disk_only ${PYBIND11_HEADERS}) if(_pybind11_here_only) message(AUTHOR_WARNING "PYBIND11_HEADERS has extra files:" ${_pybind11_here_only}) endif() if(_pybind11_disk_only) message(AUTHOR_WARNING "PYBIND11_HEADERS is missing files:" ${_pybind11_disk_only}) endif() endif() # CMake 3.12 added list(TRANSFORM PREPEND # But we can't use it yet string(REPLACE "include/" "${CMAKE_CURRENT_SOURCE_DIR}/include/" PYBIND11_HEADERS "${PYBIND11_HEADERS}") # Cache variable so this can be used in parent projects set(pybind11_INCLUDE_DIR "${CMAKE_CURRENT_LIST_DIR}/include" CACHE INTERNAL "Directory where pybind11 headers are located") # Backward compatible variable for add_subdirectory mode if(NOT PYBIND11_MASTER_PROJECT) set(PYBIND11_INCLUDE_DIR "${pybind11_INCLUDE_DIR}" CACHE INTERNAL "") endif() # Note: when creating targets, you cannot use if statements at configure time - # you need generator expressions, because those will be placed in the target file. # You can also place ifs *in* the Config.in, but not here. # This section builds targets, but does *not* touch Python # Non-IMPORT targets cannot be defined twice if(NOT TARGET pybind11_headers) # Build the headers-only target (no Python included): # (long name used here to keep this from clashing in subdirectory mode) add_library(pybind11_headers INTERFACE) add_library(pybind11::pybind11_headers ALIAS pybind11_headers) # to match exported target add_library(pybind11::headers ALIAS pybind11_headers) # easier to use/remember target_include_directories( pybind11_headers ${pybind11_system} INTERFACE $ $) target_compile_features(pybind11_headers INTERFACE cxx_inheriting_constructors cxx_user_literals cxx_right_angle_brackets) if(NOT "${PYBIND11_INTERNALS_VERSION}" STREQUAL "") target_compile_definitions( pybind11_headers INTERFACE "PYBIND11_INTERNALS_VERSION=${PYBIND11_INTERNALS_VERSION}") endif() else() # It is invalid to install a target twice, too. set(PYBIND11_INSTALL OFF) endif() include("${CMAKE_CURRENT_SOURCE_DIR}/tools/pybind11Common.cmake") # https://github.com/jtojnar/cmake-snips/#concatenating-paths-when-building-pkg-config-files # TODO: cmake 3.20 adds the cmake_path() function, which obsoletes this snippet include("${CMAKE_CURRENT_SOURCE_DIR}/tools/JoinPaths.cmake") # Relative directory setting if(USE_PYTHON_INCLUDE_DIR AND DEFINED Python_INCLUDE_DIRS) file(RELATIVE_PATH CMAKE_INSTALL_INCLUDEDIR ${CMAKE_INSTALL_PREFIX} ${Python_INCLUDE_DIRS}) elseif(USE_PYTHON_INCLUDE_DIR AND DEFINED PYTHON_INCLUDE_DIR) file(RELATIVE_PATH CMAKE_INSTALL_INCLUDEDIR ${CMAKE_INSTALL_PREFIX} ${PYTHON_INCLUDE_DIRS}) endif() if(PYBIND11_INSTALL) install(DIRECTORY ${pybind11_INCLUDE_DIR}/pybind11 DESTINATION ${CMAKE_INSTALL_INCLUDEDIR}) set(PYBIND11_CMAKECONFIG_INSTALL_DIR "${CMAKE_INSTALL_DATAROOTDIR}/cmake/${PROJECT_NAME}" CACHE STRING "install path for pybind11Config.cmake") if(IS_ABSOLUTE "${CMAKE_INSTALL_INCLUDEDIR}") set(pybind11_INCLUDEDIR "${CMAKE_INSTALL_FULL_INCLUDEDIR}") else() set(pybind11_INCLUDEDIR "\$\{PACKAGE_PREFIX_DIR\}/${CMAKE_INSTALL_INCLUDEDIR}") endif() configure_package_config_file( tools/${PROJECT_NAME}Config.cmake.in "${CMAKE_CURRENT_BINARY_DIR}/${PROJECT_NAME}Config.cmake" INSTALL_DESTINATION ${PYBIND11_CMAKECONFIG_INSTALL_DIR}) if(CMAKE_VERSION VERSION_LESS 3.14) # Remove CMAKE_SIZEOF_VOID_P from ConfigVersion.cmake since the library does # not depend on architecture specific settings or libraries. set(_PYBIND11_CMAKE_SIZEOF_VOID_P ${CMAKE_SIZEOF_VOID_P}) unset(CMAKE_SIZEOF_VOID_P) write_basic_package_version_file( ${CMAKE_CURRENT_BINARY_DIR}/${PROJECT_NAME}ConfigVersion.cmake VERSION ${PROJECT_VERSION} COMPATIBILITY AnyNewerVersion) set(CMAKE_SIZEOF_VOID_P ${_PYBIND11_CMAKE_SIZEOF_VOID_P}) else() # CMake 3.14+ natively supports header-only libraries write_basic_package_version_file( ${CMAKE_CURRENT_BINARY_DIR}/${PROJECT_NAME}ConfigVersion.cmake VERSION ${PROJECT_VERSION} COMPATIBILITY AnyNewerVersion ARCH_INDEPENDENT) endif() install( FILES ${CMAKE_CURRENT_BINARY_DIR}/${PROJECT_NAME}Config.cmake ${CMAKE_CURRENT_BINARY_DIR}/${PROJECT_NAME}ConfigVersion.cmake tools/FindPythonLibsNew.cmake tools/pybind11Common.cmake tools/pybind11Tools.cmake tools/pybind11NewTools.cmake tools/pybind11GuessPythonExtSuffix.cmake DESTINATION ${PYBIND11_CMAKECONFIG_INSTALL_DIR}) if(NOT PYBIND11_EXPORT_NAME) set(PYBIND11_EXPORT_NAME "${PROJECT_NAME}Targets") endif() install(TARGETS pybind11_headers EXPORT "${PYBIND11_EXPORT_NAME}") install( EXPORT "${PYBIND11_EXPORT_NAME}" NAMESPACE "pybind11::" DESTINATION ${PYBIND11_CMAKECONFIG_INSTALL_DIR}) # pkg-config support if(NOT prefix_for_pc_file) if(IS_ABSOLUTE "${CMAKE_INSTALL_DATAROOTDIR}") set(prefix_for_pc_file "${CMAKE_INSTALL_PREFIX}") else() set(pc_datarootdir "${CMAKE_INSTALL_DATAROOTDIR}") if(CMAKE_VERSION VERSION_LESS 3.20) set(prefix_for_pc_file "\${pcfiledir}/..") while(pc_datarootdir) get_filename_component(pc_datarootdir "${pc_datarootdir}" DIRECTORY) string(APPEND prefix_for_pc_file "/..") endwhile() else() cmake_path(RELATIVE_PATH CMAKE_INSTALL_PREFIX BASE_DIRECTORY CMAKE_INSTALL_DATAROOTDIR OUTPUT_VARIABLE prefix_for_pc_file) endif() endif() endif() join_paths(includedir_for_pc_file "\${prefix}" "${CMAKE_INSTALL_INCLUDEDIR}") configure_file("${CMAKE_CURRENT_SOURCE_DIR}/tools/pybind11.pc.in" "${CMAKE_CURRENT_BINARY_DIR}/pybind11.pc" @ONLY) install(FILES "${CMAKE_CURRENT_BINARY_DIR}/pybind11.pc" DESTINATION "${CMAKE_INSTALL_DATAROOTDIR}/pkgconfig/") # Uninstall target if(PYBIND11_MASTER_PROJECT) configure_file("${CMAKE_CURRENT_SOURCE_DIR}/tools/cmake_uninstall.cmake.in" "${CMAKE_CURRENT_BINARY_DIR}/cmake_uninstall.cmake" IMMEDIATE @ONLY) add_custom_target(uninstall COMMAND ${CMAKE_COMMAND} -P ${CMAKE_CURRENT_BINARY_DIR}/cmake_uninstall.cmake) endif() endif() # BUILD_TESTING takes priority, but only if this is the master project if(PYBIND11_MASTER_PROJECT AND DEFINED BUILD_TESTING) if(BUILD_TESTING) if(_pybind11_nopython) message(FATAL_ERROR "Cannot activate tests in NOPYTHON mode") else() add_subdirectory(tests) endif() endif() else() if(PYBIND11_TEST) if(_pybind11_nopython) message(FATAL_ERROR "Cannot activate tests in NOPYTHON mode") else() add_subdirectory(tests) endif() endif() endif() # Better symmetry with find_package(pybind11 CONFIG) mode. if(NOT PYBIND11_MASTER_PROJECT) set(pybind11_FOUND TRUE CACHE INTERNAL "True if pybind11 and all required components found on the system") endif() pybind11-2.13.6/LICENSE000066400000000000000000000032241467115402600142460ustar00rootroot00000000000000Copyright (c) 2016 Wenzel Jakob , All rights reserved. Redistribution and use in source and binary forms, with or without modification, are permitted provided that the following conditions are met: 1. Redistributions of source code must retain the above copyright notice, this list of conditions and the following disclaimer. 2. Redistributions in binary form must reproduce the above copyright notice, this list of conditions and the following disclaimer in the documentation and/or other materials provided with the distribution. 3. Neither the name of the copyright holder nor the names of its contributors may be used to endorse or promote products derived from this software without specific prior written permission. THIS SOFTWARE IS PROVIDED BY THE COPYRIGHT HOLDERS AND CONTRIBUTORS "AS IS" AND ANY EXPRESS OR IMPLIED WARRANTIES, INCLUDING, BUT NOT LIMITED TO, THE IMPLIED WARRANTIES OF MERCHANTABILITY AND FITNESS FOR A PARTICULAR PURPOSE ARE DISCLAIMED. IN NO EVENT SHALL THE COPYRIGHT HOLDER OR CONTRIBUTORS BE LIABLE FOR ANY DIRECT, INDIRECT, INCIDENTAL, SPECIAL, EXEMPLARY, OR CONSEQUENTIAL DAMAGES (INCLUDING, BUT NOT LIMITED TO, PROCUREMENT OF SUBSTITUTE GOODS OR SERVICES; LOSS OF USE, DATA, OR PROFITS; OR BUSINESS INTERRUPTION) HOWEVER CAUSED AND ON ANY THEORY OF LIABILITY, WHETHER IN CONTRACT, STRICT LIABILITY, OR TORT (INCLUDING NEGLIGENCE OR OTHERWISE) ARISING IN ANY WAY OUT OF THE USE OF THIS SOFTWARE, EVEN IF ADVISED OF THE POSSIBILITY OF SUCH DAMAGE. Please also refer to the file .github/CONTRIBUTING.md, which clarifies licensing of external contributions to this project including patches, pull requests, etc. pybind11-2.13.6/MANIFEST.in000066400000000000000000000003671467115402600150040ustar00rootroot00000000000000prune tests recursive-include pybind11/include/pybind11 *.h recursive-include pybind11 *.py recursive-include pybind11 py.typed include pybind11/share/cmake/pybind11/*.cmake include LICENSE README.rst SECURITY.md pyproject.toml setup.py setup.cfg pybind11-2.13.6/README.rst000066400000000000000000000170711467115402600147350ustar00rootroot00000000000000.. figure:: https://github.com/pybind/pybind11/raw/master/docs/pybind11-logo.png :alt: pybind11 logo **pybind11 — Seamless operability between C++11 and Python** |Latest Documentation Status| |Stable Documentation Status| |Gitter chat| |GitHub Discussions| |CI| |Build status| |Repology| |PyPI package| |Conda-forge| |Python Versions| `Setuptools example `_ • `Scikit-build example `_ • `CMake example `_ .. start **pybind11** is a lightweight header-only library that exposes C++ types in Python and vice versa, mainly to create Python bindings of existing C++ code. Its goals and syntax are similar to the excellent `Boost.Python `_ library by David Abrahams: to minimize boilerplate code in traditional extension modules by inferring type information using compile-time introspection. The main issue with Boost.Python—and the reason for creating such a similar project—is Boost. Boost is an enormously large and complex suite of utility libraries that works with almost every C++ compiler in existence. This compatibility has its cost: arcane template tricks and workarounds are necessary to support the oldest and buggiest of compiler specimens. Now that C++11-compatible compilers are widely available, this heavy machinery has become an excessively large and unnecessary dependency. Think of this library as a tiny self-contained version of Boost.Python with everything stripped away that isn't relevant for binding generation. Without comments, the core header files only require ~4K lines of code and depend on Python (3.7+, or PyPy) and the C++ standard library. This compact implementation was possible thanks to some C++11 language features (specifically: tuples, lambda functions and variadic templates). Since its creation, this library has grown beyond Boost.Python in many ways, leading to dramatically simpler binding code in many common situations. Tutorial and reference documentation is provided at `pybind11.readthedocs.io `_. A PDF version of the manual is available `here `_. And the source code is always available at `github.com/pybind/pybind11 `_. Core features ------------- pybind11 can map the following core C++ features to Python: - Functions accepting and returning custom data structures per value, reference, or pointer - Instance methods and static methods - Overloaded functions - Instance attributes and static attributes - Arbitrary exception types - Enumerations - Callbacks - Iterators and ranges - Custom operators - Single and multiple inheritance - STL data structures - Smart pointers with reference counting like ``std::shared_ptr`` - Internal references with correct reference counting - C++ classes with virtual (and pure virtual) methods can be extended in Python - Integrated NumPy support (NumPy 2 requires pybind11 2.12+) Goodies ------- In addition to the core functionality, pybind11 provides some extra goodies: - Python 3.7+, and PyPy3 7.3 are supported with an implementation-agnostic interface (pybind11 2.9 was the last version to support Python 2 and 3.5). - It is possible to bind C++11 lambda functions with captured variables. The lambda capture data is stored inside the resulting Python function object. - pybind11 uses C++11 move constructors and move assignment operators whenever possible to efficiently transfer custom data types. - It's easy to expose the internal storage of custom data types through Pythons' buffer protocols. This is handy e.g. for fast conversion between C++ matrix classes like Eigen and NumPy without expensive copy operations. - pybind11 can automatically vectorize functions so that they are transparently applied to all entries of one or more NumPy array arguments. - Python's slice-based access and assignment operations can be supported with just a few lines of code. - Everything is contained in just a few header files; there is no need to link against any additional libraries. - Binaries are generally smaller by a factor of at least 2 compared to equivalent bindings generated by Boost.Python. A recent pybind11 conversion of PyRosetta, an enormous Boost.Python binding project, `reported `_ a binary size reduction of **5.4x** and compile time reduction by **5.8x**. - Function signatures are precomputed at compile time (using ``constexpr``), leading to smaller binaries. - With little extra effort, C++ types can be pickled and unpickled similar to regular Python objects. Supported compilers ------------------- 1. Clang/LLVM 3.3 or newer (for Apple Xcode's clang, this is 5.0.0 or newer) 2. GCC 4.8 or newer 3. Microsoft Visual Studio 2017 or newer 4. Intel classic C++ compiler 18 or newer (ICC 20.2 tested in CI) 5. Cygwin/GCC (previously tested on 2.5.1) 6. NVCC (CUDA 11.0 tested in CI) 7. NVIDIA PGI (20.9 tested in CI) About ----- This project was created by `Wenzel Jakob `_. Significant features and/or improvements to the code were contributed by Jonas Adler, Lori A. Burns, Sylvain Corlay, Eric Cousineau, Aaron Gokaslan, Ralf Grosse-Kunstleve, Trent Houliston, Axel Huebl, @hulucc, Yannick Jadoul, Sergey Lyskov, Johan Mabille, Tomasz Miąsko, Dean Moldovan, Ben Pritchard, Jason Rhinelander, Boris Schäling, Pim Schellart, Henry Schreiner, Ivan Smirnov, Boris Staletic, and Patrick Stewart. We thank Google for a generous financial contribution to the continuous integration infrastructure used by this project. Contributing ~~~~~~~~~~~~ See the `contributing guide `_ for information on building and contributing to pybind11. License ~~~~~~~ pybind11 is provided under a BSD-style license that can be found in the `LICENSE `_ file. By using, distributing, or contributing to this project, you agree to the terms and conditions of this license. .. |Latest Documentation Status| image:: https://readthedocs.org/projects/pybind11/badge?version=latest :target: http://pybind11.readthedocs.org/en/latest .. |Stable Documentation Status| image:: https://img.shields.io/badge/docs-stable-blue.svg :target: http://pybind11.readthedocs.org/en/stable .. |Gitter chat| image:: https://img.shields.io/gitter/room/gitterHQ/gitter.svg :target: https://gitter.im/pybind/Lobby .. |CI| image:: https://github.com/pybind/pybind11/workflows/CI/badge.svg :target: https://github.com/pybind/pybind11/actions .. |Build status| image:: https://ci.appveyor.com/api/projects/status/riaj54pn4h08xy40?svg=true :target: https://ci.appveyor.com/project/wjakob/pybind11 .. |PyPI package| image:: https://img.shields.io/pypi/v/pybind11.svg :target: https://pypi.org/project/pybind11/ .. |Conda-forge| image:: https://img.shields.io/conda/vn/conda-forge/pybind11.svg :target: https://github.com/conda-forge/pybind11-feedstock .. |Repology| image:: https://repology.org/badge/latest-versions/python:pybind11.svg :target: https://repology.org/project/python:pybind11/versions .. |Python Versions| image:: https://img.shields.io/pypi/pyversions/pybind11.svg :target: https://pypi.org/project/pybind11/ .. |GitHub Discussions| image:: https://img.shields.io/static/v1?label=Discussions&message=Ask&color=blue&logo=github :target: https://github.com/pybind/pybind11/discussions pybind11-2.13.6/SECURITY.md000066400000000000000000000012601467115402600150300ustar00rootroot00000000000000# Security Policy ## Supported Versions Security updates are applied only to the latest release. ## Reporting a Vulnerability If you have discovered a security vulnerability in this project, please report it privately. **Do not disclose it as a public issue.** This gives us time to work with you to fix the issue before public exposure, reducing the chance that the exploit will be used before a patch is released. Please disclose it at [security advisory](https://github.com/pybind/pybind11/security/advisories/new). This project is maintained by a team of volunteers on a reasonable-effort basis. 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The pseudo-XML files are in $(BUILDDIR)/pseudoxml." pybind11-2.13.6/docs/_static/000077500000000000000000000000001467115402600156165ustar00rootroot00000000000000pybind11-2.13.6/docs/_static/css/000077500000000000000000000000001467115402600164065ustar00rootroot00000000000000pybind11-2.13.6/docs/_static/css/custom.css000066400000000000000000000000451467115402600204310ustar00rootroot00000000000000.highlight .go { color: #707070; } pybind11-2.13.6/docs/advanced/000077500000000000000000000000001467115402600157355ustar00rootroot00000000000000pybind11-2.13.6/docs/advanced/cast/000077500000000000000000000000001467115402600166675ustar00rootroot00000000000000pybind11-2.13.6/docs/advanced/cast/chrono.rst000066400000000000000000000075411467115402600207200ustar00rootroot00000000000000Chrono ====== When including the additional header file :file:`pybind11/chrono.h` conversions from C++11 chrono datatypes to python datetime objects are automatically enabled. This header also enables conversions of python floats (often from sources such as ``time.monotonic()``, ``time.perf_counter()`` and ``time.process_time()``) into durations. An overview of clocks in C++11 ------------------------------ A point of confusion when using these conversions is the differences between clocks provided in C++11. There are three clock types defined by the C++11 standard and users can define their own if needed. Each of these clocks have different properties and when converting to and from python will give different results. The first clock defined by the standard is ``std::chrono::system_clock``. This clock measures the current date and time. However, this clock changes with to updates to the operating system time. For example, if your time is synchronised with a time server this clock will change. This makes this clock a poor choice for timing purposes but good for measuring the wall time. The second clock defined in the standard is ``std::chrono::steady_clock``. This clock ticks at a steady rate and is never adjusted. This makes it excellent for timing purposes, however the value in this clock does not correspond to the current date and time. Often this clock will be the amount of time your system has been on, although it does not have to be. This clock will never be the same clock as the system clock as the system clock can change but steady clocks cannot. The third clock defined in the standard is ``std::chrono::high_resolution_clock``. This clock is the clock that has the highest resolution out of the clocks in the system. It is normally a typedef to either the system clock or the steady clock but can be its own independent clock. This is important as when using these conversions as the types you get in python for this clock might be different depending on the system. If it is a typedef of the system clock, python will get datetime objects, but if it is a different clock they will be timedelta objects. Provided conversions -------------------- .. rubric:: C++ to Python - ``std::chrono::system_clock::time_point`` → ``datetime.datetime`` System clock times are converted to python datetime instances. They are in the local timezone, but do not have any timezone information attached to them (they are naive datetime objects). - ``std::chrono::duration`` → ``datetime.timedelta`` Durations are converted to timedeltas, any precision in the duration greater than microseconds is lost by rounding towards zero. - ``std::chrono::[other_clocks]::time_point`` → ``datetime.timedelta`` Any clock time that is not the system clock is converted to a time delta. This timedelta measures the time from the clocks epoch to now. .. rubric:: Python to C++ - ``datetime.datetime`` or ``datetime.date`` or ``datetime.time`` → ``std::chrono::system_clock::time_point`` Date/time objects are converted into system clock timepoints. Any timezone information is ignored and the type is treated as a naive object. - ``datetime.timedelta`` → ``std::chrono::duration`` Time delta are converted into durations with microsecond precision. - ``datetime.timedelta`` → ``std::chrono::[other_clocks]::time_point`` Time deltas that are converted into clock timepoints are treated as the amount of time from the start of the clocks epoch. - ``float`` → ``std::chrono::duration`` Floats that are passed to C++ as durations be interpreted as a number of seconds. These will be converted to the duration using ``duration_cast`` from the float. - ``float`` → ``std::chrono::[other_clocks]::time_point`` Floats that are passed to C++ as time points will be interpreted as the number of seconds from the start of the clocks epoch. pybind11-2.13.6/docs/advanced/cast/custom.rst000066400000000000000000000065451467115402600207450ustar00rootroot00000000000000Custom type casters =================== In very rare cases, applications may require custom type casters that cannot be expressed using the abstractions provided by pybind11, thus requiring raw Python C API calls. This is fairly advanced usage and should only be pursued by experts who are familiar with the intricacies of Python reference counting. The following snippets demonstrate how this works for a very simple ``inty`` type that that should be convertible from Python types that provide a ``__int__(self)`` method. .. code-block:: cpp struct inty { long long_value; }; void print(inty s) { std::cout << s.long_value << std::endl; } The following Python snippet demonstrates the intended usage from the Python side: .. code-block:: python class A: def __int__(self): return 123 from example import print print(A()) To register the necessary conversion routines, it is necessary to add an instantiation of the ``pybind11::detail::type_caster`` template. Although this is an implementation detail, adding an instantiation of this type is explicitly allowed. .. code-block:: cpp namespace PYBIND11_NAMESPACE { namespace detail { template <> struct type_caster { public: /** * This macro establishes the name 'inty' in * function signatures and declares a local variable * 'value' of type inty */ PYBIND11_TYPE_CASTER(inty, const_name("inty")); /** * Conversion part 1 (Python->C++): convert a PyObject into a inty * instance or return false upon failure. The second argument * indicates whether implicit conversions should be applied. */ bool load(handle src, bool) { /* Extract PyObject from handle */ PyObject *source = src.ptr(); /* Try converting into a Python integer value */ PyObject *tmp = PyNumber_Long(source); if (!tmp) return false; /* Now try to convert into a C++ int */ value.long_value = PyLong_AsLong(tmp); Py_DECREF(tmp); /* Ensure return code was OK (to avoid out-of-range errors etc) */ return !(value.long_value == -1 && !PyErr_Occurred()); } /** * Conversion part 2 (C++ -> Python): convert an inty instance into * a Python object. The second and third arguments are used to * indicate the return value policy and parent object (for * ``return_value_policy::reference_internal``) and are generally * ignored by implicit casters. */ static handle cast(inty src, return_value_policy /* policy */, handle /* parent */) { return PyLong_FromLong(src.long_value); } }; }} // namespace PYBIND11_NAMESPACE::detail .. note:: A ``type_caster`` defined with ``PYBIND11_TYPE_CASTER(T, ...)`` requires that ``T`` is default-constructible (``value`` is first default constructed and then ``load()`` assigns to it). .. warning:: When using custom type casters, it's important to declare them consistently in every compilation unit of the Python extension module. Otherwise, undefined behavior can ensue. pybind11-2.13.6/docs/advanced/cast/eigen.rst000066400000000000000000000337071467115402600205220ustar00rootroot00000000000000Eigen ##### `Eigen `_ is C++ header-based library for dense and sparse linear algebra. Due to its popularity and widespread adoption, pybind11 provides transparent conversion and limited mapping support between Eigen and Scientific Python linear algebra data types. To enable the built-in Eigen support you must include the optional header file :file:`pybind11/eigen.h`. Pass-by-value ============= When binding a function with ordinary Eigen dense object arguments (for example, ``Eigen::MatrixXd``), pybind11 will accept any input value that is already (or convertible to) a ``numpy.ndarray`` with dimensions compatible with the Eigen type, copy its values into a temporary Eigen variable of the appropriate type, then call the function with this temporary variable. Sparse matrices are similarly copied to or from ``scipy.sparse.csr_matrix``/``scipy.sparse.csc_matrix`` objects. Pass-by-reference ================= One major limitation of the above is that every data conversion implicitly involves a copy, which can be both expensive (for large matrices) and disallows binding functions that change their (Matrix) arguments. Pybind11 allows you to work around this by using Eigen's ``Eigen::Ref`` class much as you would when writing a function taking a generic type in Eigen itself (subject to some limitations discussed below). When calling a bound function accepting a ``Eigen::Ref`` type, pybind11 will attempt to avoid copying by using an ``Eigen::Map`` object that maps into the source ``numpy.ndarray`` data: this requires both that the data types are the same (e.g. ``dtype='float64'`` and ``MatrixType::Scalar`` is ``double``); and that the storage is layout compatible. The latter limitation is discussed in detail in the section below, and requires careful consideration: by default, numpy matrices and Eigen matrices are *not* storage compatible. If the numpy matrix cannot be used as is (either because its types differ, e.g. passing an array of integers to an Eigen parameter requiring doubles, or because the storage is incompatible), pybind11 makes a temporary copy and passes the copy instead. When a bound function parameter is instead ``Eigen::Ref`` (note the lack of ``const``), pybind11 will only allow the function to be called if it can be mapped *and* if the numpy array is writeable (that is ``a.flags.writeable`` is true). Any access (including modification) made to the passed variable will be transparently carried out directly on the ``numpy.ndarray``. This means you can write code such as the following and have it work as expected: .. code-block:: cpp void scale_by_2(Eigen::Ref v) { v *= 2; } Note, however, that you will likely run into limitations due to numpy and Eigen's difference default storage order for data; see the below section on :ref:`storage_orders` for details on how to bind code that won't run into such limitations. .. note:: Passing by reference is not supported for sparse types. Returning values to Python ========================== When returning an ordinary dense Eigen matrix type to numpy (e.g. ``Eigen::MatrixXd`` or ``Eigen::RowVectorXf``) pybind11 keeps the matrix and returns a numpy array that directly references the Eigen matrix: no copy of the data is performed. The numpy array will have ``array.flags.owndata`` set to ``False`` to indicate that it does not own the data, and the lifetime of the stored Eigen matrix will be tied to the returned ``array``. If you bind a function with a non-reference, ``const`` return type (e.g. ``const Eigen::MatrixXd``), the same thing happens except that pybind11 also sets the numpy array's ``writeable`` flag to false. If you return an lvalue reference or pointer, the usual pybind11 rules apply, as dictated by the binding function's return value policy (see the documentation on :ref:`return_value_policies` for full details). That means, without an explicit return value policy, lvalue references will be copied and pointers will be managed by pybind11. In order to avoid copying, you should explicitly specify an appropriate return value policy, as in the following example: .. code-block:: cpp class MyClass { Eigen::MatrixXd big_mat = Eigen::MatrixXd::Zero(10000, 10000); public: Eigen::MatrixXd &getMatrix() { return big_mat; } const Eigen::MatrixXd &viewMatrix() { return big_mat; } }; // Later, in binding code: py::class_(m, "MyClass") .def(py::init<>()) .def("copy_matrix", &MyClass::getMatrix) // Makes a copy! .def("get_matrix", &MyClass::getMatrix, py::return_value_policy::reference_internal) .def("view_matrix", &MyClass::viewMatrix, py::return_value_policy::reference_internal) ; .. code-block:: python a = MyClass() m = a.get_matrix() # flags.writeable = True, flags.owndata = False v = a.view_matrix() # flags.writeable = False, flags.owndata = False c = a.copy_matrix() # flags.writeable = True, flags.owndata = True # m[5,6] and v[5,6] refer to the same element, c[5,6] does not. Note in this example that ``py::return_value_policy::reference_internal`` is used to tie the life of the MyClass object to the life of the returned arrays. You may also return an ``Eigen::Ref``, ``Eigen::Map`` or other map-like Eigen object (for example, the return value of ``matrix.block()`` and related methods) that map into a dense Eigen type. When doing so, the default behaviour of pybind11 is to simply reference the returned data: you must take care to ensure that this data remains valid! You may ask pybind11 to explicitly *copy* such a return value by using the ``py::return_value_policy::copy`` policy when binding the function. You may also use ``py::return_value_policy::reference_internal`` or a ``py::keep_alive`` to ensure the data stays valid as long as the returned numpy array does. When returning such a reference of map, pybind11 additionally respects the readonly-status of the returned value, marking the numpy array as non-writeable if the reference or map was itself read-only. .. note:: Sparse types are always copied when returned. .. _storage_orders: Storage orders ============== Passing arguments via ``Eigen::Ref`` has some limitations that you must be aware of in order to effectively pass matrices by reference. First and foremost is that the default ``Eigen::Ref`` class requires contiguous storage along columns (for column-major types, the default in Eigen) or rows if ``MatrixType`` is specifically an ``Eigen::RowMajor`` storage type. The former, Eigen's default, is incompatible with ``numpy``'s default row-major storage, and so you will not be able to pass numpy arrays to Eigen by reference without making one of two changes. (Note that this does not apply to vectors (or column or row matrices): for such types the "row-major" and "column-major" distinction is meaningless). The first approach is to change the use of ``Eigen::Ref`` to the more general ``Eigen::Ref>`` (or similar type with a fully dynamic stride type in the third template argument). Since this is a rather cumbersome type, pybind11 provides a ``py::EigenDRef`` type alias for your convenience (along with EigenDMap for the equivalent Map, and EigenDStride for just the stride type). This type allows Eigen to map into any arbitrary storage order. This is not the default in Eigen for performance reasons: contiguous storage allows vectorization that cannot be done when storage is not known to be contiguous at compile time. The default ``Eigen::Ref`` stride type allows non-contiguous storage along the outer dimension (that is, the rows of a column-major matrix or columns of a row-major matrix), but not along the inner dimension. This type, however, has the added benefit of also being able to map numpy array slices. For example, the following (contrived) example uses Eigen with a numpy slice to multiply by 2 all coefficients that are both on even rows (0, 2, 4, ...) and in columns 2, 5, or 8: .. code-block:: cpp m.def("scale", [](py::EigenDRef m, double c) { m *= c; }); .. code-block:: python # a = np.array(...) scale_by_2(myarray[0::2, 2:9:3]) The second approach to avoid copying is more intrusive: rearranging the underlying data types to not run into the non-contiguous storage problem in the first place. In particular, that means using matrices with ``Eigen::RowMajor`` storage, where appropriate, such as: .. code-block:: cpp using RowMatrixXd = Eigen::Matrix; // Use RowMatrixXd instead of MatrixXd Now bound functions accepting ``Eigen::Ref`` arguments will be callable with numpy's (default) arrays without involving a copying. You can, alternatively, change the storage order that numpy arrays use by adding the ``order='F'`` option when creating an array: .. code-block:: python myarray = np.array(source, order="F") Such an object will be passable to a bound function accepting an ``Eigen::Ref`` (or similar column-major Eigen type). One major caveat with this approach, however, is that it is not entirely as easy as simply flipping all Eigen or numpy usage from one to the other: some operations may alter the storage order of a numpy array. For example, ``a2 = array.transpose()`` results in ``a2`` being a view of ``array`` that references the same data, but in the opposite storage order! While this approach allows fully optimized vectorized calculations in Eigen, it cannot be used with array slices, unlike the first approach. When *returning* a matrix to Python (either a regular matrix, a reference via ``Eigen::Ref<>``, or a map/block into a matrix), no special storage consideration is required: the created numpy array will have the required stride that allows numpy to properly interpret the array, whatever its storage order. Failing rather than copying =========================== The default behaviour when binding ``Eigen::Ref`` Eigen references is to copy matrix values when passed a numpy array that does not conform to the element type of ``MatrixType`` or does not have a compatible stride layout. If you want to explicitly avoid copying in such a case, you should bind arguments using the ``py::arg().noconvert()`` annotation (as described in the :ref:`nonconverting_arguments` documentation). The following example shows an example of arguments that don't allow data copying to take place: .. code-block:: cpp // The method and function to be bound: class MyClass { // ... double some_method(const Eigen::Ref &matrix) { /* ... */ } }; float some_function(const Eigen::Ref &big, const Eigen::Ref &small) { // ... } // The associated binding code: using namespace pybind11::literals; // for "arg"_a py::class_(m, "MyClass") // ... other class definitions .def("some_method", &MyClass::some_method, py::arg().noconvert()); m.def("some_function", &some_function, "big"_a.noconvert(), // <- Don't allow copying for this arg "small"_a // <- This one can be copied if needed ); With the above binding code, attempting to call the ``some_method(m)`` method on a ``MyClass`` object, or attempting to call ``some_function(m, m2)`` will raise a ``RuntimeError`` rather than making a temporary copy of the array. It will, however, allow the ``m2`` argument to be copied into a temporary if necessary. Note that explicitly specifying ``.noconvert()`` is not required for *mutable* Eigen references (e.g. ``Eigen::Ref`` without ``const`` on the ``MatrixXd``): mutable references will never be called with a temporary copy. Vectors versus column/row matrices ================================== Eigen and numpy have fundamentally different notions of a vector. In Eigen, a vector is simply a matrix with the number of columns or rows set to 1 at compile time (for a column vector or row vector, respectively). NumPy, in contrast, has comparable 2-dimensional 1xN and Nx1 arrays, but *also* has 1-dimensional arrays of size N. When passing a 2-dimensional 1xN or Nx1 array to Eigen, the Eigen type must have matching dimensions: That is, you cannot pass a 2-dimensional Nx1 numpy array to an Eigen value expecting a row vector, or a 1xN numpy array as a column vector argument. On the other hand, pybind11 allows you to pass 1-dimensional arrays of length N as Eigen parameters. If the Eigen type can hold a column vector of length N it will be passed as such a column vector. If not, but the Eigen type constraints will accept a row vector, it will be passed as a row vector. (The column vector takes precedence when both are supported, for example, when passing a 1D numpy array to a MatrixXd argument). Note that the type need not be explicitly a vector: it is permitted to pass a 1D numpy array of size 5 to an Eigen ``Matrix``: you would end up with a 1x5 Eigen matrix. Passing the same to an ``Eigen::MatrixXd`` would result in a 5x1 Eigen matrix. When returning an Eigen vector to numpy, the conversion is ambiguous: a row vector of length 4 could be returned as either a 1D array of length 4, or as a 2D array of size 1x4. When encountering such a situation, pybind11 compromises by considering the returned Eigen type: if it is a compile-time vector--that is, the type has either the number of rows or columns set to 1 at compile time--pybind11 converts to a 1D numpy array when returning the value. For instances that are a vector only at run-time (e.g. ``MatrixXd``, ``Matrix``), pybind11 returns the vector as a 2D array to numpy. If this isn't want you want, you can use ``array.reshape(...)`` to get a view of the same data in the desired dimensions. .. seealso:: The file :file:`tests/test_eigen.cpp` contains a complete example that shows how to pass Eigen sparse and dense data types in more detail. pybind11-2.13.6/docs/advanced/cast/functional.rst000066400000000000000000000074611467115402600215730ustar00rootroot00000000000000Functional ########## The following features must be enabled by including :file:`pybind11/functional.h`. Callbacks and passing anonymous functions ========================================= The C++11 standard brought lambda functions and the generic polymorphic function wrapper ``std::function<>`` to the C++ programming language, which enable powerful new ways of working with functions. Lambda functions come in two flavors: stateless lambda function resemble classic function pointers that link to an anonymous piece of code, while stateful lambda functions additionally depend on captured variables that are stored in an anonymous *lambda closure object*. Here is a simple example of a C++ function that takes an arbitrary function (stateful or stateless) with signature ``int -> int`` as an argument and runs it with the value 10. .. code-block:: cpp int func_arg(const std::function &f) { return f(10); } The example below is more involved: it takes a function of signature ``int -> int`` and returns another function of the same kind. The return value is a stateful lambda function, which stores the value ``f`` in the capture object and adds 1 to its return value upon execution. .. code-block:: cpp std::function func_ret(const std::function &f) { return [f](int i) { return f(i) + 1; }; } This example demonstrates using python named parameters in C++ callbacks which requires using ``py::cpp_function`` as a wrapper. Usage is similar to defining methods of classes: .. code-block:: cpp py::cpp_function func_cpp() { return py::cpp_function([](int i) { return i+1; }, py::arg("number")); } After including the extra header file :file:`pybind11/functional.h`, it is almost trivial to generate binding code for all of these functions. .. code-block:: cpp #include PYBIND11_MODULE(example, m) { m.def("func_arg", &func_arg); m.def("func_ret", &func_ret); m.def("func_cpp", &func_cpp); } The following interactive session shows how to call them from Python. .. code-block:: pycon $ python >>> import example >>> def square(i): ... return i * i ... >>> example.func_arg(square) 100L >>> square_plus_1 = example.func_ret(square) >>> square_plus_1(4) 17L >>> plus_1 = func_cpp() >>> plus_1(number=43) 44L .. warning:: Keep in mind that passing a function from C++ to Python (or vice versa) will instantiate a piece of wrapper code that translates function invocations between the two languages. Naturally, this translation increases the computational cost of each function call somewhat. A problematic situation can arise when a function is copied back and forth between Python and C++ many times in a row, in which case the underlying wrappers will accumulate correspondingly. The resulting long sequence of C++ -> Python -> C++ -> ... roundtrips can significantly decrease performance. There is one exception: pybind11 detects case where a stateless function (i.e. a function pointer or a lambda function without captured variables) is passed as an argument to another C++ function exposed in Python. In this case, there is no overhead. Pybind11 will extract the underlying C++ function pointer from the wrapped function to sidestep a potential C++ -> Python -> C++ roundtrip. This is demonstrated in :file:`tests/test_callbacks.cpp`. .. note:: This functionality is very useful when generating bindings for callbacks in C++ libraries (e.g. GUI libraries, asynchronous networking libraries, etc.). The file :file:`tests/test_callbacks.cpp` contains a complete example that demonstrates how to work with callbacks and anonymous functions in more detail. pybind11-2.13.6/docs/advanced/cast/index.rst000066400000000000000000000030241467115402600205270ustar00rootroot00000000000000.. _type-conversions: Type conversions ################ Apart from enabling cross-language function calls, a fundamental problem that a binding tool like pybind11 must address is to provide access to native Python types in C++ and vice versa. There are three fundamentally different ways to do this—which approach is preferable for a particular type depends on the situation at hand. 1. Use a native C++ type everywhere. In this case, the type must be wrapped using pybind11-generated bindings so that Python can interact with it. 2. Use a native Python type everywhere. It will need to be wrapped so that C++ functions can interact with it. 3. Use a native C++ type on the C++ side and a native Python type on the Python side. pybind11 refers to this as a *type conversion*. Type conversions are the most "natural" option in the sense that native (non-wrapped) types are used everywhere. The main downside is that a copy of the data must be made on every Python ↔ C++ transition: this is needed since the C++ and Python versions of the same type generally won't have the same memory layout. pybind11 can perform many kinds of conversions automatically. An overview is provided in the table ":ref:`conversion_table`". The following subsections discuss the differences between these options in more detail. The main focus in this section is on type conversions, which represent the last case of the above list. .. toctree:: :maxdepth: 1 overview strings stl functional chrono eigen custom pybind11-2.13.6/docs/advanced/cast/overview.rst000066400000000000000000000301231467115402600212660ustar00rootroot00000000000000Overview ######## .. rubric:: 1. Native type in C++, wrapper in Python Exposing a custom C++ type using :class:`py::class_` was covered in detail in the :doc:`/classes` section. There, the underlying data structure is always the original C++ class while the :class:`py::class_` wrapper provides a Python interface. Internally, when an object like this is sent from C++ to Python, pybind11 will just add the outer wrapper layer over the native C++ object. Getting it back from Python is just a matter of peeling off the wrapper. .. rubric:: 2. Wrapper in C++, native type in Python This is the exact opposite situation. Now, we have a type which is native to Python, like a ``tuple`` or a ``list``. One way to get this data into C++ is with the :class:`py::object` family of wrappers. These are explained in more detail in the :doc:`/advanced/pycpp/object` section. We'll just give a quick example here: .. code-block:: cpp void print_list(py::list my_list) { for (auto item : my_list) std::cout << item << " "; } .. code-block:: pycon >>> print_list([1, 2, 3]) 1 2 3 The Python ``list`` is not converted in any way -- it's just wrapped in a C++ :class:`py::list` class. At its core it's still a Python object. Copying a :class:`py::list` will do the usual reference-counting like in Python. Returning the object to Python will just remove the thin wrapper. .. rubric:: 3. Converting between native C++ and Python types In the previous two cases we had a native type in one language and a wrapper in the other. Now, we have native types on both sides and we convert between them. .. code-block:: cpp void print_vector(const std::vector &v) { for (auto item : v) std::cout << item << "\n"; } .. code-block:: pycon >>> print_vector([1, 2, 3]) 1 2 3 In this case, pybind11 will construct a new ``std::vector`` and copy each element from the Python ``list``. The newly constructed object will be passed to ``print_vector``. The same thing happens in the other direction: a new ``list`` is made to match the value returned from C++. Lots of these conversions are supported out of the box, as shown in the table below. They are very convenient, but keep in mind that these conversions are fundamentally based on copying data. This is perfectly fine for small immutable types but it may become quite expensive for large data structures. This can be avoided by overriding the automatic conversion with a custom wrapper (i.e. the above-mentioned approach 1). This requires some manual effort and more details are available in the :ref:`opaque` section. .. _conversion_table: List of all builtin conversions ------------------------------- The following basic data types are supported out of the box (some may require an additional extension header to be included). To pass other data structures as arguments and return values, refer to the section on binding :ref:`classes`. +------------------------------------+---------------------------+-----------------------------------+ | Data type | Description | Header file | +====================================+===========================+===================================+ | ``int8_t``, ``uint8_t`` | 8-bit integers | :file:`pybind11/pybind11.h` | +------------------------------------+---------------------------+-----------------------------------+ | ``int16_t``, ``uint16_t`` | 16-bit integers | :file:`pybind11/pybind11.h` | +------------------------------------+---------------------------+-----------------------------------+ | ``int32_t``, ``uint32_t`` | 32-bit integers | :file:`pybind11/pybind11.h` | +------------------------------------+---------------------------+-----------------------------------+ | ``int64_t``, ``uint64_t`` | 64-bit integers | :file:`pybind11/pybind11.h` | +------------------------------------+---------------------------+-----------------------------------+ | ``ssize_t``, ``size_t`` | Platform-dependent size | :file:`pybind11/pybind11.h` | +------------------------------------+---------------------------+-----------------------------------+ | ``float``, ``double`` | Floating point types | :file:`pybind11/pybind11.h` | +------------------------------------+---------------------------+-----------------------------------+ | ``bool`` | Two-state Boolean type | :file:`pybind11/pybind11.h` | +------------------------------------+---------------------------+-----------------------------------+ | ``char`` | Character literal | :file:`pybind11/pybind11.h` | +------------------------------------+---------------------------+-----------------------------------+ | ``char16_t`` | UTF-16 character literal | :file:`pybind11/pybind11.h` | +------------------------------------+---------------------------+-----------------------------------+ | ``char32_t`` | UTF-32 character literal | :file:`pybind11/pybind11.h` | +------------------------------------+---------------------------+-----------------------------------+ | ``wchar_t`` | Wide character literal | :file:`pybind11/pybind11.h` | +------------------------------------+---------------------------+-----------------------------------+ | ``const char *`` | UTF-8 string literal | :file:`pybind11/pybind11.h` | +------------------------------------+---------------------------+-----------------------------------+ | ``const char16_t *`` | UTF-16 string literal | :file:`pybind11/pybind11.h` | +------------------------------------+---------------------------+-----------------------------------+ | ``const char32_t *`` | UTF-32 string literal | :file:`pybind11/pybind11.h` | +------------------------------------+---------------------------+-----------------------------------+ | ``const wchar_t *`` | Wide string literal | :file:`pybind11/pybind11.h` | +------------------------------------+---------------------------+-----------------------------------+ | ``std::string`` | STL dynamic UTF-8 string | :file:`pybind11/pybind11.h` | +------------------------------------+---------------------------+-----------------------------------+ | ``std::u16string`` | STL dynamic UTF-16 string | :file:`pybind11/pybind11.h` | +------------------------------------+---------------------------+-----------------------------------+ | ``std::u32string`` | STL dynamic UTF-32 string | :file:`pybind11/pybind11.h` | +------------------------------------+---------------------------+-----------------------------------+ | ``std::wstring`` | STL dynamic wide string | :file:`pybind11/pybind11.h` | +------------------------------------+---------------------------+-----------------------------------+ | ``std::string_view``, | STL C++17 string views | :file:`pybind11/pybind11.h` | | ``std::u16string_view``, etc. | | | +------------------------------------+---------------------------+-----------------------------------+ | ``std::pair`` | Pair of two custom types | :file:`pybind11/pybind11.h` | +------------------------------------+---------------------------+-----------------------------------+ | ``std::tuple<...>`` | Arbitrary tuple of types | :file:`pybind11/pybind11.h` | +------------------------------------+---------------------------+-----------------------------------+ | ``std::reference_wrapper<...>`` | Reference type wrapper | :file:`pybind11/pybind11.h` | +------------------------------------+---------------------------+-----------------------------------+ | ``std::complex`` | Complex numbers | :file:`pybind11/complex.h` | +------------------------------------+---------------------------+-----------------------------------+ | ``std::array`` | STL static array | :file:`pybind11/stl.h` | +------------------------------------+---------------------------+-----------------------------------+ | ``std::vector`` | STL dynamic array | :file:`pybind11/stl.h` | +------------------------------------+---------------------------+-----------------------------------+ | ``std::deque`` | STL double-ended queue | :file:`pybind11/stl.h` | +------------------------------------+---------------------------+-----------------------------------+ | ``std::valarray`` | STL value array | :file:`pybind11/stl.h` | +------------------------------------+---------------------------+-----------------------------------+ | ``std::list`` | STL linked list | :file:`pybind11/stl.h` | +------------------------------------+---------------------------+-----------------------------------+ | ``std::map`` | STL ordered map | :file:`pybind11/stl.h` | +------------------------------------+---------------------------+-----------------------------------+ | ``std::unordered_map`` | STL unordered map | :file:`pybind11/stl.h` | +------------------------------------+---------------------------+-----------------------------------+ | ``std::set`` | STL ordered set | :file:`pybind11/stl.h` | +------------------------------------+---------------------------+-----------------------------------+ | ``std::unordered_set`` | STL unordered set | :file:`pybind11/stl.h` | +------------------------------------+---------------------------+-----------------------------------+ | ``std::optional`` | STL optional type (C++17) | :file:`pybind11/stl.h` | +------------------------------------+---------------------------+-----------------------------------+ | ``std::experimental::optional`` | STL optional type (exp.) | :file:`pybind11/stl.h` | +------------------------------------+---------------------------+-----------------------------------+ | ``std::variant<...>`` | Type-safe union (C++17) | :file:`pybind11/stl.h` | +------------------------------------+---------------------------+-----------------------------------+ | ``std::filesystem::path`` | STL path (C++17) [#]_ | :file:`pybind11/stl/filesystem.h` | +------------------------------------+---------------------------+-----------------------------------+ | ``std::function<...>`` | STL polymorphic function | :file:`pybind11/functional.h` | +------------------------------------+---------------------------+-----------------------------------+ | ``std::chrono::duration<...>`` | STL time duration | :file:`pybind11/chrono.h` | +------------------------------------+---------------------------+-----------------------------------+ | ``std::chrono::time_point<...>`` | STL date/time | :file:`pybind11/chrono.h` | +------------------------------------+---------------------------+-----------------------------------+ | ``Eigen::Matrix<...>`` | Eigen: dense matrix | :file:`pybind11/eigen.h` | +------------------------------------+---------------------------+-----------------------------------+ | ``Eigen::Map<...>`` | Eigen: mapped memory | :file:`pybind11/eigen.h` | +------------------------------------+---------------------------+-----------------------------------+ | ``Eigen::SparseMatrix<...>`` | Eigen: sparse matrix | :file:`pybind11/eigen.h` | +------------------------------------+---------------------------+-----------------------------------+ .. [#] ``std::filesystem::path`` is converted to ``pathlib.Path`` and ``os.PathLike`` is converted to ``std::filesystem::path``. pybind11-2.13.6/docs/advanced/cast/stl.rst000066400000000000000000000225571467115402600202360ustar00rootroot00000000000000STL containers ############## Automatic conversion ==================== When including the additional header file :file:`pybind11/stl.h`, conversions between ``std::vector<>``/``std::deque<>``/``std::list<>``/``std::array<>``/``std::valarray<>``, ``std::set<>``/``std::unordered_set<>``, and ``std::map<>``/``std::unordered_map<>`` and the Python ``list``, ``set`` and ``dict`` data structures are automatically enabled. The types ``std::pair<>`` and ``std::tuple<>`` are already supported out of the box with just the core :file:`pybind11/pybind11.h` header. The major downside of these implicit conversions is that containers must be converted (i.e. copied) on every Python->C++ and C++->Python transition, which can have implications on the program semantics and performance. Please read the next sections for more details and alternative approaches that avoid this. .. note:: Arbitrary nesting of any of these types is possible. .. seealso:: The file :file:`tests/test_stl.cpp` contains a complete example that demonstrates how to pass STL data types in more detail. .. _cpp17_container_casters: C++17 library containers ======================== The :file:`pybind11/stl.h` header also includes support for ``std::optional<>`` and ``std::variant<>``. These require a C++17 compiler and standard library. In C++14 mode, ``std::experimental::optional<>`` is supported if available. Various versions of these containers also exist for C++11 (e.g. in Boost). pybind11 provides an easy way to specialize the ``type_caster`` for such types: .. code-block:: cpp // `boost::optional` as an example -- can be any `std::optional`-like container namespace PYBIND11_NAMESPACE { namespace detail { template struct type_caster> : optional_caster> {}; }} The above should be placed in a header file and included in all translation units where automatic conversion is needed. Similarly, a specialization can be provided for custom variant types: .. code-block:: cpp // `boost::variant` as an example -- can be any `std::variant`-like container namespace PYBIND11_NAMESPACE { namespace detail { template struct type_caster> : variant_caster> {}; // Specifies the function used to visit the variant -- `apply_visitor` instead of `visit` template <> struct visit_helper { template static auto call(Args &&...args) -> decltype(boost::apply_visitor(args...)) { return boost::apply_visitor(args...); } }; }} // namespace PYBIND11_NAMESPACE::detail The ``visit_helper`` specialization is not required if your ``name::variant`` provides a ``name::visit()`` function. For any other function name, the specialization must be included to tell pybind11 how to visit the variant. .. warning:: When converting a ``variant`` type, pybind11 follows the same rules as when determining which function overload to call (:ref:`overload_resolution`), and so the same caveats hold. In particular, the order in which the ``variant``'s alternatives are listed is important, since pybind11 will try conversions in this order. This means that, for example, when converting ``variant``, the ``bool`` variant will never be selected, as any Python ``bool`` is already an ``int`` and is convertible to a C++ ``int``. Changing the order of alternatives (and using ``variant``, in this example) provides a solution. .. note:: pybind11 only supports the modern implementation of ``boost::variant`` which makes use of variadic templates. This requires Boost 1.56 or newer. .. _opaque: Making opaque types =================== pybind11 heavily relies on a template matching mechanism to convert parameters and return values that are constructed from STL data types such as vectors, linked lists, hash tables, etc. This even works in a recursive manner, for instance to deal with lists of hash maps of pairs of elementary and custom types, etc. However, a fundamental limitation of this approach is that internal conversions between Python and C++ types involve a copy operation that prevents pass-by-reference semantics. What does this mean? Suppose we bind the following function .. code-block:: cpp void append_1(std::vector &v) { v.push_back(1); } and call it from Python, the following happens: .. code-block:: pycon >>> v = [5, 6] >>> append_1(v) >>> print(v) [5, 6] As you can see, when passing STL data structures by reference, modifications are not propagated back the Python side. A similar situation arises when exposing STL data structures using the ``def_readwrite`` or ``def_readonly`` functions: .. code-block:: cpp /* ... definition ... */ class MyClass { std::vector contents; }; /* ... binding code ... */ py::class_(m, "MyClass") .def(py::init<>()) .def_readwrite("contents", &MyClass::contents); In this case, properties can be read and written in their entirety. However, an ``append`` operation involving such a list type has no effect: .. code-block:: pycon >>> m = MyClass() >>> m.contents = [5, 6] >>> print(m.contents) [5, 6] >>> m.contents.append(7) >>> print(m.contents) [5, 6] Finally, the involved copy operations can be costly when dealing with very large lists. To deal with all of the above situations, pybind11 provides a macro named ``PYBIND11_MAKE_OPAQUE(T)`` that disables the template-based conversion machinery of types, thus rendering them *opaque*. The contents of opaque objects are never inspected or extracted, hence they *can* be passed by reference. For instance, to turn ``std::vector`` into an opaque type, add the declaration .. code-block:: cpp PYBIND11_MAKE_OPAQUE(std::vector) before any binding code (e.g. invocations to ``class_::def()``, etc.). This macro must be specified at the top level (and outside of any namespaces), since it adds a template instantiation of ``type_caster``. If your binding code consists of multiple compilation units, it must be present in every file (typically via a common header) preceding any usage of ``std::vector``. Opaque types must also have a corresponding ``class_`` declaration to associate them with a name in Python, and to define a set of available operations, e.g.: .. code-block:: cpp py::class_>(m, "IntVector") .def(py::init<>()) .def("clear", &std::vector::clear) .def("pop_back", &std::vector::pop_back) .def("__len__", [](const std::vector &v) { return v.size(); }) .def("__iter__", [](std::vector &v) { return py::make_iterator(v.begin(), v.end()); }, py::keep_alive<0, 1>()) /* Keep vector alive while iterator is used */ // .... .. seealso:: The file :file:`tests/test_opaque_types.cpp` contains a complete example that demonstrates how to create and expose opaque types using pybind11 in more detail. .. _stl_bind: Binding STL containers ====================== The ability to expose STL containers as native Python objects is a fairly common request, hence pybind11 also provides an optional header file named :file:`pybind11/stl_bind.h` that does exactly this. The mapped containers try to match the behavior of their native Python counterparts as much as possible. The following example showcases usage of :file:`pybind11/stl_bind.h`: .. code-block:: cpp // Don't forget this #include PYBIND11_MAKE_OPAQUE(std::vector) PYBIND11_MAKE_OPAQUE(std::map) // ... // later in binding code: py::bind_vector>(m, "VectorInt"); py::bind_map>(m, "MapStringDouble"); When binding STL containers pybind11 considers the types of the container's elements to decide whether the container should be confined to the local module (via the :ref:`module_local` feature). If the container element types are anything other than already-bound custom types bound without ``py::module_local()`` the container binding will have ``py::module_local()`` applied. This includes converting types such as numeric types, strings, Eigen types; and types that have not yet been bound at the time of the stl container binding. This module-local binding is designed to avoid potential conflicts between module bindings (for example, from two separate modules each attempting to bind ``std::vector`` as a python type). It is possible to override this behavior to force a definition to be either module-local or global. To do so, you can pass the attributes ``py::module_local()`` (to make the binding module-local) or ``py::module_local(false)`` (to make the binding global) into the ``py::bind_vector`` or ``py::bind_map`` arguments: .. code-block:: cpp py::bind_vector>(m, "VectorInt", py::module_local(false)); Note, however, that such a global binding would make it impossible to load this module at the same time as any other pybind module that also attempts to bind the same container type (``std::vector`` in the above example). See :ref:`module_local` for more details on module-local bindings. .. seealso:: The file :file:`tests/test_stl_binders.cpp` shows how to use the convenience STL container wrappers. pybind11-2.13.6/docs/advanced/cast/strings.rst000066400000000000000000000216371467115402600211230ustar00rootroot00000000000000Strings, bytes and Unicode conversions ###################################### Passing Python strings to C++ ============================= When a Python ``str`` is passed from Python to a C++ function that accepts ``std::string`` or ``char *`` as arguments, pybind11 will encode the Python string to UTF-8. All Python ``str`` can be encoded in UTF-8, so this operation does not fail. The C++ language is encoding agnostic. It is the responsibility of the programmer to track encodings. It's often easiest to simply `use UTF-8 everywhere `_. .. code-block:: c++ m.def("utf8_test", [](const std::string &s) { cout << "utf-8 is icing on the cake.\n"; cout << s; } ); m.def("utf8_charptr", [](const char *s) { cout << "My favorite food is\n"; cout << s; } ); .. code-block:: pycon >>> utf8_test("🎂") utf-8 is icing on the cake. 🎂 >>> utf8_charptr("🍕") My favorite food is 🍕 .. note:: Some terminal emulators do not support UTF-8 or emoji fonts and may not display the example above correctly. The results are the same whether the C++ function accepts arguments by value or reference, and whether or not ``const`` is used. Passing bytes to C++ -------------------- A Python ``bytes`` object will be passed to C++ functions that accept ``std::string`` or ``char*`` *without* conversion. In order to make a function *only* accept ``bytes`` (and not ``str``), declare it as taking a ``py::bytes`` argument. Returning C++ strings to Python =============================== When a C++ function returns a ``std::string`` or ``char*`` to a Python caller, **pybind11 will assume that the string is valid UTF-8** and will decode it to a native Python ``str``, using the same API as Python uses to perform ``bytes.decode('utf-8')``. If this implicit conversion fails, pybind11 will raise a ``UnicodeDecodeError``. .. code-block:: c++ m.def("std_string_return", []() { return std::string("This string needs to be UTF-8 encoded"); } ); .. code-block:: pycon >>> isinstance(example.std_string_return(), str) True Because UTF-8 is inclusive of pure ASCII, there is never any issue with returning a pure ASCII string to Python. If there is any possibility that the string is not pure ASCII, it is necessary to ensure the encoding is valid UTF-8. .. warning:: Implicit conversion assumes that a returned ``char *`` is null-terminated. If there is no null terminator a buffer overrun will occur. Explicit conversions -------------------- If some C++ code constructs a ``std::string`` that is not a UTF-8 string, one can perform a explicit conversion and return a ``py::str`` object. Explicit conversion has the same overhead as implicit conversion. .. code-block:: c++ // This uses the Python C API to convert Latin-1 to Unicode m.def("str_output", []() { std::string s = "Send your r\xe9sum\xe9 to Alice in HR"; // Latin-1 py::handle py_s = PyUnicode_DecodeLatin1(s.data(), s.length(), nullptr); if (!py_s) { throw py::error_already_set(); } return py::reinterpret_steal(py_s); } ); .. code-block:: pycon >>> str_output() 'Send your résumé to Alice in HR' The `Python C API `_ provides several built-in codecs. Note that these all return *new* references, so use :cpp:func:`reinterpret_steal` when converting them to a :cpp:class:`str`. One could also use a third party encoding library such as libiconv to transcode to UTF-8. Return C++ strings without conversion ------------------------------------- If the data in a C++ ``std::string`` does not represent text and should be returned to Python as ``bytes``, then one can return the data as a ``py::bytes`` object. .. code-block:: c++ m.def("return_bytes", []() { std::string s("\xba\xd0\xba\xd0"); // Not valid UTF-8 return py::bytes(s); // Return the data without transcoding } ); .. code-block:: pycon >>> example.return_bytes() b'\xba\xd0\xba\xd0' Note the asymmetry: pybind11 will convert ``bytes`` to ``std::string`` without encoding, but cannot convert ``std::string`` back to ``bytes`` implicitly. .. code-block:: c++ m.def("asymmetry", [](std::string s) { // Accepts str or bytes from Python return s; // Looks harmless, but implicitly converts to str } ); .. code-block:: pycon >>> isinstance(example.asymmetry(b"have some bytes"), str) True >>> example.asymmetry(b"\xba\xd0\xba\xd0") # invalid utf-8 as bytes UnicodeDecodeError: 'utf-8' codec can't decode byte 0xba in position 0: invalid start byte Wide character strings ====================== When a Python ``str`` is passed to a C++ function expecting ``std::wstring``, ``wchar_t*``, ``std::u16string`` or ``std::u32string``, the ``str`` will be encoded to UTF-16 or UTF-32 depending on how the C++ compiler implements each type, in the platform's native endianness. When strings of these types are returned, they are assumed to contain valid UTF-16 or UTF-32, and will be decoded to Python ``str``. .. code-block:: c++ #define UNICODE #include m.def("set_window_text", [](HWND hwnd, std::wstring s) { // Call SetWindowText with null-terminated UTF-16 string ::SetWindowText(hwnd, s.c_str()); } ); m.def("get_window_text", [](HWND hwnd) { const int buffer_size = ::GetWindowTextLength(hwnd) + 1; auto buffer = std::make_unique< wchar_t[] >(buffer_size); ::GetWindowText(hwnd, buffer.data(), buffer_size); std::wstring text(buffer.get()); // wstring will be converted to Python str return text; } ); Strings in multibyte encodings such as Shift-JIS must transcoded to a UTF-8/16/32 before being returned to Python. Character literals ================== C++ functions that accept character literals as input will receive the first character of a Python ``str`` as their input. If the string is longer than one Unicode character, trailing characters will be ignored. When a character literal is returned from C++ (such as a ``char`` or a ``wchar_t``), it will be converted to a ``str`` that represents the single character. .. code-block:: c++ m.def("pass_char", [](char c) { return c; }); m.def("pass_wchar", [](wchar_t w) { return w; }); .. code-block:: pycon >>> example.pass_char("A") 'A' While C++ will cast integers to character types (``char c = 0x65;``), pybind11 does not convert Python integers to characters implicitly. The Python function ``chr()`` can be used to convert integers to characters. .. code-block:: pycon >>> example.pass_char(0x65) TypeError >>> example.pass_char(chr(0x65)) 'A' If the desire is to work with an 8-bit integer, use ``int8_t`` or ``uint8_t`` as the argument type. Grapheme clusters ----------------- A single grapheme may be represented by two or more Unicode characters. For example 'é' is usually represented as U+00E9 but can also be expressed as the combining character sequence U+0065 U+0301 (that is, the letter 'e' followed by a combining acute accent). The combining character will be lost if the two-character sequence is passed as an argument, even though it renders as a single grapheme. .. code-block:: pycon >>> example.pass_wchar("é") 'é' >>> combining_e_acute = "e" + "\u0301" >>> combining_e_acute 'é' >>> combining_e_acute == "é" False >>> example.pass_wchar(combining_e_acute) 'e' Normalizing combining characters before passing the character literal to C++ may resolve *some* of these issues: .. code-block:: pycon >>> example.pass_wchar(unicodedata.normalize("NFC", combining_e_acute)) 'é' In some languages (Thai for example), there are `graphemes that cannot be expressed as a single Unicode code point `_, so there is no way to capture them in a C++ character type. C++17 string views ================== C++17 string views are automatically supported when compiling in C++17 mode. They follow the same rules for encoding and decoding as the corresponding STL string type (for example, a ``std::u16string_view`` argument will be passed UTF-16-encoded data, and a returned ``std::string_view`` will be decoded as UTF-8). References ========== * `The Absolute Minimum Every Software Developer Absolutely, Positively Must Know About Unicode and Character Sets (No Excuses!) `_ * `C++ - Using STL Strings at Win32 API Boundaries `_ pybind11-2.13.6/docs/advanced/classes.rst000066400000000000000000001352641467115402600201370ustar00rootroot00000000000000Classes ####### This section presents advanced binding code for classes and it is assumed that you are already familiar with the basics from :doc:`/classes`. .. _overriding_virtuals: Overriding virtual functions in Python ====================================== Suppose that a C++ class or interface has a virtual function that we'd like to override from within Python (we'll focus on the class ``Animal``; ``Dog`` is given as a specific example of how one would do this with traditional C++ code). .. code-block:: cpp class Animal { public: virtual ~Animal() { } virtual std::string go(int n_times) = 0; }; class Dog : public Animal { public: std::string go(int n_times) override { std::string result; for (int i=0; igo(3); } Normally, the binding code for these classes would look as follows: .. code-block:: cpp PYBIND11_MODULE(example, m) { py::class_(m, "Animal") .def("go", &Animal::go); py::class_(m, "Dog") .def(py::init<>()); m.def("call_go", &call_go); } However, these bindings are impossible to extend: ``Animal`` is not constructible, and we clearly require some kind of "trampoline" that redirects virtual calls back to Python. Defining a new type of ``Animal`` from within Python is possible but requires a helper class that is defined as follows: .. code-block:: cpp class PyAnimal : public Animal { public: /* Inherit the constructors */ using Animal::Animal; /* Trampoline (need one for each virtual function) */ std::string go(int n_times) override { PYBIND11_OVERRIDE_PURE( std::string, /* Return type */ Animal, /* Parent class */ go, /* Name of function in C++ (must match Python name) */ n_times /* Argument(s) */ ); } }; The macro :c:macro:`PYBIND11_OVERRIDE_PURE` should be used for pure virtual functions, and :c:macro:`PYBIND11_OVERRIDE` should be used for functions which have a default implementation. There are also two alternate macros :c:macro:`PYBIND11_OVERRIDE_PURE_NAME` and :c:macro:`PYBIND11_OVERRIDE_NAME` which take a string-valued name argument between the *Parent class* and *Name of the function* slots, which defines the name of function in Python. This is required when the C++ and Python versions of the function have different names, e.g. ``operator()`` vs ``__call__``. The binding code also needs a few minor adaptations (highlighted): .. code-block:: cpp :emphasize-lines: 2,3 PYBIND11_MODULE(example, m) { py::class_(m, "Animal") .def(py::init<>()) .def("go", &Animal::go); py::class_(m, "Dog") .def(py::init<>()); m.def("call_go", &call_go); } Importantly, pybind11 is made aware of the trampoline helper class by specifying it as an extra template argument to :class:`class_`. (This can also be combined with other template arguments such as a custom holder type; the order of template types does not matter). Following this, we are able to define a constructor as usual. Bindings should be made against the actual class, not the trampoline helper class. .. code-block:: cpp :emphasize-lines: 3 py::class_(m, "Animal"); .def(py::init<>()) .def("go", &PyAnimal::go); /* <--- THIS IS WRONG, use &Animal::go */ Note, however, that the above is sufficient for allowing python classes to extend ``Animal``, but not ``Dog``: see :ref:`virtual_and_inheritance` for the necessary steps required to providing proper overriding support for inherited classes. The Python session below shows how to override ``Animal::go`` and invoke it via a virtual method call. .. code-block:: pycon >>> from example import * >>> d = Dog() >>> call_go(d) 'woof! woof! woof! ' >>> class Cat(Animal): ... def go(self, n_times): ... return "meow! " * n_times ... >>> c = Cat() >>> call_go(c) 'meow! meow! meow! ' If you are defining a custom constructor in a derived Python class, you *must* ensure that you explicitly call the bound C++ constructor using ``__init__``, *regardless* of whether it is a default constructor or not. Otherwise, the memory for the C++ portion of the instance will be left uninitialized, which will generally leave the C++ instance in an invalid state and cause undefined behavior if the C++ instance is subsequently used. .. versionchanged:: 2.6 The default pybind11 metaclass will throw a ``TypeError`` when it detects that ``__init__`` was not called by a derived class. Here is an example: .. code-block:: python class Dachshund(Dog): def __init__(self, name): Dog.__init__(self) # Without this, a TypeError is raised. self.name = name def bark(self): return "yap!" Note that a direct ``__init__`` constructor *should be called*, and ``super()`` should not be used. For simple cases of linear inheritance, ``super()`` may work, but once you begin mixing Python and C++ multiple inheritance, things will fall apart due to differences between Python's MRO and C++'s mechanisms. Please take a look at the :ref:`macro_notes` before using this feature. .. note:: When the overridden type returns a reference or pointer to a type that pybind11 converts from Python (for example, numeric values, std::string, and other built-in value-converting types), there are some limitations to be aware of: - because in these cases there is no C++ variable to reference (the value is stored in the referenced Python variable), pybind11 provides one in the PYBIND11_OVERRIDE macros (when needed) with static storage duration. Note that this means that invoking the overridden method on *any* instance will change the referenced value stored in *all* instances of that type. - Attempts to modify a non-const reference will not have the desired effect: it will change only the static cache variable, but this change will not propagate to underlying Python instance, and the change will be replaced the next time the override is invoked. .. warning:: The :c:macro:`PYBIND11_OVERRIDE` and accompanying macros used to be called ``PYBIND11_OVERLOAD`` up until pybind11 v2.5.0, and :func:`get_override` used to be called ``get_overload``. This naming was corrected and the older macro and function names may soon be deprecated, in order to reduce confusion with overloaded functions and methods and ``py::overload_cast`` (see :ref:`classes`). .. seealso:: The file :file:`tests/test_virtual_functions.cpp` contains a complete example that demonstrates how to override virtual functions using pybind11 in more detail. .. _virtual_and_inheritance: Combining virtual functions and inheritance =========================================== When combining virtual methods with inheritance, you need to be sure to provide an override for each method for which you want to allow overrides from derived python classes. For example, suppose we extend the above ``Animal``/``Dog`` example as follows: .. code-block:: cpp class Animal { public: virtual std::string go(int n_times) = 0; virtual std::string name() { return "unknown"; } }; class Dog : public Animal { public: std::string go(int n_times) override { std::string result; for (int i=0; i class PyAnimal : public AnimalBase { public: using AnimalBase::AnimalBase; // Inherit constructors std::string go(int n_times) override { PYBIND11_OVERRIDE_PURE(std::string, AnimalBase, go, n_times); } std::string name() override { PYBIND11_OVERRIDE(std::string, AnimalBase, name, ); } }; template class PyDog : public PyAnimal { public: using PyAnimal::PyAnimal; // Inherit constructors // Override PyAnimal's pure virtual go() with a non-pure one: std::string go(int n_times) override { PYBIND11_OVERRIDE(std::string, DogBase, go, n_times); } std::string bark() override { PYBIND11_OVERRIDE(std::string, DogBase, bark, ); } }; This technique has the advantage of requiring just one trampoline method to be declared per virtual method and pure virtual method override. It does, however, require the compiler to generate at least as many methods (and possibly more, if both pure virtual and overridden pure virtual methods are exposed, as above). The classes are then registered with pybind11 using: .. code-block:: cpp py::class_> animal(m, "Animal"); py::class_> dog(m, "Dog"); py::class_> husky(m, "Husky"); // ... add animal, dog, husky definitions Note that ``Husky`` did not require a dedicated trampoline template class at all, since it neither declares any new virtual methods nor provides any pure virtual method implementations. With either the repeated-virtuals or templated trampoline methods in place, you can now create a python class that inherits from ``Dog``: .. code-block:: python class ShihTzu(Dog): def bark(self): return "yip!" .. seealso:: See the file :file:`tests/test_virtual_functions.cpp` for complete examples using both the duplication and templated trampoline approaches. .. _extended_aliases: Extended trampoline class functionality ======================================= .. _extended_class_functionality_forced_trampoline: Forced trampoline class initialisation -------------------------------------- The trampoline classes described in the previous sections are, by default, only initialized when needed. More specifically, they are initialized when a python class actually inherits from a registered type (instead of merely creating an instance of the registered type), or when a registered constructor is only valid for the trampoline class but not the registered class. This is primarily for performance reasons: when the trampoline class is not needed for anything except virtual method dispatching, not initializing the trampoline class improves performance by avoiding needing to do a run-time check to see if the inheriting python instance has an overridden method. Sometimes, however, it is useful to always initialize a trampoline class as an intermediate class that does more than just handle virtual method dispatching. For example, such a class might perform extra class initialization, extra destruction operations, and might define new members and methods to enable a more python-like interface to a class. In order to tell pybind11 that it should *always* initialize the trampoline class when creating new instances of a type, the class constructors should be declared using ``py::init_alias()`` instead of the usual ``py::init()``. This forces construction via the trampoline class, ensuring member initialization and (eventual) destruction. .. seealso:: See the file :file:`tests/test_virtual_functions.cpp` for complete examples showing both normal and forced trampoline instantiation. Different method signatures --------------------------- The macro's introduced in :ref:`overriding_virtuals` cover most of the standard use cases when exposing C++ classes to Python. Sometimes it is hard or unwieldy to create a direct one-on-one mapping between the arguments and method return type. An example would be when the C++ signature contains output arguments using references (See also :ref:`faq_reference_arguments`). Another way of solving this is to use the method body of the trampoline class to do conversions to the input and return of the Python method. The main building block to do so is the :func:`get_override`, this function allows retrieving a method implemented in Python from within the trampoline's methods. Consider for example a C++ method which has the signature ``bool myMethod(int32_t& value)``, where the return indicates whether something should be done with the ``value``. This can be made convenient on the Python side by allowing the Python function to return ``None`` or an ``int``: .. code-block:: cpp bool MyClass::myMethod(int32_t& value) { pybind11::gil_scoped_acquire gil; // Acquire the GIL while in this scope. // Try to look up the overridden method on the Python side. pybind11::function override = pybind11::get_override(this, "myMethod"); if (override) { // method is found auto obj = override(value); // Call the Python function. if (py::isinstance(obj)) { // check if it returned a Python integer type value = obj.cast(); // Cast it and assign it to the value. return true; // Return true; value should be used. } else { return false; // Python returned none, return false. } } return false; // Alternatively return MyClass::myMethod(value); } .. _custom_constructors: Custom constructors =================== The syntax for binding constructors was previously introduced, but it only works when a constructor of the appropriate arguments actually exists on the C++ side. To extend this to more general cases, pybind11 makes it possible to bind factory functions as constructors. For example, suppose you have a class like this: .. code-block:: cpp class Example { private: Example(int); // private constructor public: // Factory function: static Example create(int a) { return Example(a); } }; py::class_(m, "Example") .def(py::init(&Example::create)); While it is possible to create a straightforward binding of the static ``create`` method, it may sometimes be preferable to expose it as a constructor on the Python side. This can be accomplished by calling ``.def(py::init(...))`` with the function reference returning the new instance passed as an argument. It is also possible to use this approach to bind a function returning a new instance by raw pointer or by the holder (e.g. ``std::unique_ptr``). The following example shows the different approaches: .. code-block:: cpp class Example { private: Example(int); // private constructor public: // Factory function - returned by value: static Example create(int a) { return Example(a); } // These constructors are publicly callable: Example(double); Example(int, int); Example(std::string); }; py::class_(m, "Example") // Bind the factory function as a constructor: .def(py::init(&Example::create)) // Bind a lambda function returning a pointer wrapped in a holder: .def(py::init([](std::string arg) { return std::unique_ptr(new Example(arg)); })) // Return a raw pointer: .def(py::init([](int a, int b) { return new Example(a, b); })) // You can mix the above with regular C++ constructor bindings as well: .def(py::init()) ; When the constructor is invoked from Python, pybind11 will call the factory function and store the resulting C++ instance in the Python instance. When combining factory functions constructors with :ref:`virtual function trampolines ` there are two approaches. The first is to add a constructor to the alias class that takes a base value by rvalue-reference. If such a constructor is available, it will be used to construct an alias instance from the value returned by the factory function. The second option is to provide two factory functions to ``py::init()``: the first will be invoked when no alias class is required (i.e. when the class is being used but not inherited from in Python), and the second will be invoked when an alias is required. You can also specify a single factory function that always returns an alias instance: this will result in behaviour similar to ``py::init_alias<...>()``, as described in the :ref:`extended trampoline class documentation `. The following example shows the different factory approaches for a class with an alias: .. code-block:: cpp #include class Example { public: // ... virtual ~Example() = default; }; class PyExample : public Example { public: using Example::Example; PyExample(Example &&base) : Example(std::move(base)) {} }; py::class_(m, "Example") // Returns an Example pointer. If a PyExample is needed, the Example // instance will be moved via the extra constructor in PyExample, above. .def(py::init([]() { return new Example(); })) // Two callbacks: .def(py::init([]() { return new Example(); } /* no alias needed */, []() { return new PyExample(); } /* alias needed */)) // *Always* returns an alias instance (like py::init_alias<>()) .def(py::init([]() { return new PyExample(); })) ; Brace initialization -------------------- ``pybind11::init<>`` internally uses C++11 brace initialization to call the constructor of the target class. This means that it can be used to bind *implicit* constructors as well: .. code-block:: cpp struct Aggregate { int a; std::string b; }; py::class_(m, "Aggregate") .def(py::init()); .. note:: Note that brace initialization preferentially invokes constructor overloads taking a ``std::initializer_list``. In the rare event that this causes an issue, you can work around it by using ``py::init(...)`` with a lambda function that constructs the new object as desired. .. _classes_with_non_public_destructors: Non-public destructors ====================== If a class has a private or protected destructor (as might e.g. be the case in a singleton pattern), a compile error will occur when creating bindings via pybind11. The underlying issue is that the ``std::unique_ptr`` holder type that is responsible for managing the lifetime of instances will reference the destructor even if no deallocations ever take place. In order to expose classes with private or protected destructors, it is possible to override the holder type via a holder type argument to ``class_``. Pybind11 provides a helper class ``py::nodelete`` that disables any destructor invocations. In this case, it is crucial that instances are deallocated on the C++ side to avoid memory leaks. .. code-block:: cpp /* ... definition ... */ class MyClass { private: ~MyClass() { } }; /* ... binding code ... */ py::class_>(m, "MyClass") .def(py::init<>()) .. _destructors_that_call_python: Destructors that call Python ============================ If a Python function is invoked from a C++ destructor, an exception may be thrown of type :class:`error_already_set`. If this error is thrown out of a class destructor, ``std::terminate()`` will be called, terminating the process. Class destructors must catch all exceptions of type :class:`error_already_set` to discard the Python exception using :func:`error_already_set::discard_as_unraisable`. Every Python function should be treated as *possibly throwing*. When a Python generator stops yielding items, Python will throw a ``StopIteration`` exception, which can pass though C++ destructors if the generator's stack frame holds the last reference to C++ objects. For more information, see :ref:`the documentation on exceptions `. .. code-block:: cpp class MyClass { public: ~MyClass() { try { py::print("Even printing is dangerous in a destructor"); py::exec("raise ValueError('This is an unraisable exception')"); } catch (py::error_already_set &e) { // error_context should be information about where/why the occurred, // e.g. use __func__ to get the name of the current function e.discard_as_unraisable(__func__); } } }; .. note:: pybind11 does not support C++ destructors marked ``noexcept(false)``. .. versionadded:: 2.6 .. _implicit_conversions: Implicit conversions ==================== Suppose that instances of two types ``A`` and ``B`` are used in a project, and that an ``A`` can easily be converted into an instance of type ``B`` (examples of this could be a fixed and an arbitrary precision number type). .. code-block:: cpp py::class_(m, "A") /// ... members ... py::class_(m, "B") .def(py::init()) /// ... members ... m.def("func", [](const B &) { /* .... */ } ); To invoke the function ``func`` using a variable ``a`` containing an ``A`` instance, we'd have to write ``func(B(a))`` in Python. On the other hand, C++ will automatically apply an implicit type conversion, which makes it possible to directly write ``func(a)``. In this situation (i.e. where ``B`` has a constructor that converts from ``A``), the following statement enables similar implicit conversions on the Python side: .. code-block:: cpp py::implicitly_convertible(); .. note:: Implicit conversions from ``A`` to ``B`` only work when ``B`` is a custom data type that is exposed to Python via pybind11. To prevent runaway recursion, implicit conversions are non-reentrant: an implicit conversion invoked as part of another implicit conversion of the same type (i.e. from ``A`` to ``B``) will fail. .. _static_properties: Static properties ================= The section on :ref:`properties` discussed the creation of instance properties that are implemented in terms of C++ getters and setters. Static properties can also be created in a similar way to expose getters and setters of static class attributes. Note that the implicit ``self`` argument also exists in this case and is used to pass the Python ``type`` subclass instance. This parameter will often not be needed by the C++ side, and the following example illustrates how to instantiate a lambda getter function that ignores it: .. code-block:: cpp py::class_(m, "Foo") .def_property_readonly_static("foo", [](py::object /* self */) { return Foo(); }); Operator overloading ==================== Suppose that we're given the following ``Vector2`` class with a vector addition and scalar multiplication operation, all implemented using overloaded operators in C++. .. code-block:: cpp class Vector2 { public: Vector2(float x, float y) : x(x), y(y) { } Vector2 operator+(const Vector2 &v) const { return Vector2(x + v.x, y + v.y); } Vector2 operator*(float value) const { return Vector2(x * value, y * value); } Vector2& operator+=(const Vector2 &v) { x += v.x; y += v.y; return *this; } Vector2& operator*=(float v) { x *= v; y *= v; return *this; } friend Vector2 operator*(float f, const Vector2 &v) { return Vector2(f * v.x, f * v.y); } std::string toString() const { return "[" + std::to_string(x) + ", " + std::to_string(y) + "]"; } private: float x, y; }; The following snippet shows how the above operators can be conveniently exposed to Python. .. code-block:: cpp #include PYBIND11_MODULE(example, m) { py::class_(m, "Vector2") .def(py::init()) .def(py::self + py::self) .def(py::self += py::self) .def(py::self *= float()) .def(float() * py::self) .def(py::self * float()) .def(-py::self) .def("__repr__", &Vector2::toString); } Note that a line like .. code-block:: cpp .def(py::self * float()) is really just short hand notation for .. code-block:: cpp .def("__mul__", [](const Vector2 &a, float b) { return a * b; }, py::is_operator()) This can be useful for exposing additional operators that don't exist on the C++ side, or to perform other types of customization. The ``py::is_operator`` flag marker is needed to inform pybind11 that this is an operator, which returns ``NotImplemented`` when invoked with incompatible arguments rather than throwing a type error. .. note:: To use the more convenient ``py::self`` notation, the additional header file :file:`pybind11/operators.h` must be included. .. seealso:: The file :file:`tests/test_operator_overloading.cpp` contains a complete example that demonstrates how to work with overloaded operators in more detail. .. _pickling: Pickling support ================ Python's ``pickle`` module provides a powerful facility to serialize and de-serialize a Python object graph into a binary data stream. To pickle and unpickle C++ classes using pybind11, a ``py::pickle()`` definition must be provided. Suppose the class in question has the following signature: .. code-block:: cpp class Pickleable { public: Pickleable(const std::string &value) : m_value(value) { } const std::string &value() const { return m_value; } void setExtra(int extra) { m_extra = extra; } int extra() const { return m_extra; } private: std::string m_value; int m_extra = 0; }; Pickling support in Python is enabled by defining the ``__setstate__`` and ``__getstate__`` methods [#f3]_. For pybind11 classes, use ``py::pickle()`` to bind these two functions: .. code-block:: cpp py::class_(m, "Pickleable") .def(py::init()) .def("value", &Pickleable::value) .def("extra", &Pickleable::extra) .def("setExtra", &Pickleable::setExtra) .def(py::pickle( [](const Pickleable &p) { // __getstate__ /* Return a tuple that fully encodes the state of the object */ return py::make_tuple(p.value(), p.extra()); }, [](py::tuple t) { // __setstate__ if (t.size() != 2) throw std::runtime_error("Invalid state!"); /* Create a new C++ instance */ Pickleable p(t[0].cast()); /* Assign any additional state */ p.setExtra(t[1].cast()); return p; } )); The ``__setstate__`` part of the ``py::pickle()`` definition follows the same rules as the single-argument version of ``py::init()``. The return type can be a value, pointer or holder type. See :ref:`custom_constructors` for details. An instance can now be pickled as follows: .. code-block:: python import pickle p = Pickleable("test_value") p.setExtra(15) data = pickle.dumps(p) .. note:: If given, the second argument to ``dumps`` must be 2 or larger - 0 and 1 are not supported. Newer versions are also fine; for instance, specify ``-1`` to always use the latest available version. Beware: failure to follow these instructions will cause important pybind11 memory allocation routines to be skipped during unpickling, which will likely lead to memory corruption and/or segmentation faults. Python defaults to version 3 (Python 3-3.7) and version 4 for Python 3.8+. .. seealso:: The file :file:`tests/test_pickling.cpp` contains a complete example that demonstrates how to pickle and unpickle types using pybind11 in more detail. .. [#f3] http://docs.python.org/3/library/pickle.html#pickling-class-instances Deepcopy support ================ Python normally uses references in assignments. Sometimes a real copy is needed to prevent changing all copies. The ``copy`` module [#f5]_ provides these capabilities. A class with pickle support is automatically also (deep)copy compatible. However, performance can be improved by adding custom ``__copy__`` and ``__deepcopy__`` methods. For simple classes (deep)copy can be enabled by using the copy constructor, which should look as follows: .. code-block:: cpp py::class_(m, "Copyable") .def("__copy__", [](const Copyable &self) { return Copyable(self); }) .def("__deepcopy__", [](const Copyable &self, py::dict) { return Copyable(self); }, "memo"_a); .. note:: Dynamic attributes will not be copied in this example. .. [#f5] https://docs.python.org/3/library/copy.html Multiple Inheritance ==================== pybind11 can create bindings for types that derive from multiple base types (aka. *multiple inheritance*). To do so, specify all bases in the template arguments of the ``class_`` declaration: .. code-block:: cpp py::class_(m, "MyType") ... The base types can be specified in arbitrary order, and they can even be interspersed with alias types and holder types (discussed earlier in this document)---pybind11 will automatically find out which is which. The only requirement is that the first template argument is the type to be declared. It is also permitted to inherit multiply from exported C++ classes in Python, as well as inheriting from multiple Python and/or pybind11-exported classes. There is one caveat regarding the implementation of this feature: When only one base type is specified for a C++ type that actually has multiple bases, pybind11 will assume that it does not participate in multiple inheritance, which can lead to undefined behavior. In such cases, add the tag ``multiple_inheritance`` to the class constructor: .. code-block:: cpp py::class_(m, "MyType", py::multiple_inheritance()); The tag is redundant and does not need to be specified when multiple base types are listed. .. _module_local: Module-local class bindings =========================== When creating a binding for a class, pybind11 by default makes that binding "global" across modules. What this means is that a type defined in one module can be returned from any module resulting in the same Python type. For example, this allows the following: .. code-block:: cpp // In the module1.cpp binding code for module1: py::class_(m, "Pet") .def(py::init()) .def_readonly("name", &Pet::name); .. code-block:: cpp // In the module2.cpp binding code for module2: m.def("create_pet", [](std::string name) { return new Pet(name); }); .. code-block:: pycon >>> from module1 import Pet >>> from module2 import create_pet >>> pet1 = Pet("Kitty") >>> pet2 = create_pet("Doggy") >>> pet2.name() 'Doggy' When writing binding code for a library, this is usually desirable: this allows, for example, splitting up a complex library into multiple Python modules. In some cases, however, this can cause conflicts. For example, suppose two unrelated modules make use of an external C++ library and each provide custom bindings for one of that library's classes. This will result in an error when a Python program attempts to import both modules (directly or indirectly) because of conflicting definitions on the external type: .. code-block:: cpp // dogs.cpp // Binding for external library class: py::class(m, "Pet") .def("name", &pets::Pet::name); // Binding for local extension class: py::class(m, "Dog") .def(py::init()); .. code-block:: cpp // cats.cpp, in a completely separate project from the above dogs.cpp. // Binding for external library class: py::class(m, "Pet") .def("get_name", &pets::Pet::name); // Binding for local extending class: py::class(m, "Cat") .def(py::init()); .. code-block:: pycon >>> import cats >>> import dogs Traceback (most recent call last): File "", line 1, in ImportError: generic_type: type "Pet" is already registered! To get around this, you can tell pybind11 to keep the external class binding localized to the module by passing the ``py::module_local()`` attribute into the ``py::class_`` constructor: .. code-block:: cpp // Pet binding in dogs.cpp: py::class(m, "Pet", py::module_local()) .def("name", &pets::Pet::name); .. code-block:: cpp // Pet binding in cats.cpp: py::class(m, "Pet", py::module_local()) .def("get_name", &pets::Pet::name); This makes the Python-side ``dogs.Pet`` and ``cats.Pet`` into distinct classes, avoiding the conflict and allowing both modules to be loaded. C++ code in the ``dogs`` module that casts or returns a ``Pet`` instance will result in a ``dogs.Pet`` Python instance, while C++ code in the ``cats`` module will result in a ``cats.Pet`` Python instance. This does come with two caveats, however: First, external modules cannot return or cast a ``Pet`` instance to Python (unless they also provide their own local bindings). Second, from the Python point of view they are two distinct classes. Note that the locality only applies in the C++ -> Python direction. When passing such a ``py::module_local`` type into a C++ function, the module-local classes are still considered. This means that if the following function is added to any module (including but not limited to the ``cats`` and ``dogs`` modules above) it will be callable with either a ``dogs.Pet`` or ``cats.Pet`` argument: .. code-block:: cpp m.def("pet_name", [](const pets::Pet &pet) { return pet.name(); }); For example, suppose the above function is added to each of ``cats.cpp``, ``dogs.cpp`` and ``frogs.cpp`` (where ``frogs.cpp`` is some other module that does *not* bind ``Pets`` at all). .. code-block:: pycon >>> import cats, dogs, frogs # No error because of the added py::module_local() >>> mycat, mydog = cats.Cat("Fluffy"), dogs.Dog("Rover") >>> (cats.pet_name(mycat), dogs.pet_name(mydog)) ('Fluffy', 'Rover') >>> (cats.pet_name(mydog), dogs.pet_name(mycat), frogs.pet_name(mycat)) ('Rover', 'Fluffy', 'Fluffy') It is possible to use ``py::module_local()`` registrations in one module even if another module registers the same type globally: within the module with the module-local definition, all C++ instances will be cast to the associated bound Python type. In other modules any such values are converted to the global Python type created elsewhere. .. note:: STL bindings (as provided via the optional :file:`pybind11/stl_bind.h` header) apply ``py::module_local`` by default when the bound type might conflict with other modules; see :ref:`stl_bind` for details. .. note:: The localization of the bound types is actually tied to the shared object or binary generated by the compiler/linker. For typical modules created with ``PYBIND11_MODULE()``, this distinction is not significant. It is possible, however, when :ref:`embedding` to embed multiple modules in the same binary (see :ref:`embedding_modules`). In such a case, the localization will apply across all embedded modules within the same binary. .. seealso:: The file :file:`tests/test_local_bindings.cpp` contains additional examples that demonstrate how ``py::module_local()`` works. Binding protected member functions ================================== It's normally not possible to expose ``protected`` member functions to Python: .. code-block:: cpp class A { protected: int foo() const { return 42; } }; py::class_(m, "A") .def("foo", &A::foo); // error: 'foo' is a protected member of 'A' On one hand, this is good because non-``public`` members aren't meant to be accessed from the outside. But we may want to make use of ``protected`` functions in derived Python classes. The following pattern makes this possible: .. code-block:: cpp class A { protected: int foo() const { return 42; } }; class Publicist : public A { // helper type for exposing protected functions public: using A::foo; // inherited with different access modifier }; py::class_(m, "A") // bind the primary class .def("foo", &Publicist::foo); // expose protected methods via the publicist This works because ``&Publicist::foo`` is exactly the same function as ``&A::foo`` (same signature and address), just with a different access modifier. The only purpose of the ``Publicist`` helper class is to make the function name ``public``. If the intent is to expose ``protected`` ``virtual`` functions which can be overridden in Python, the publicist pattern can be combined with the previously described trampoline: .. code-block:: cpp class A { public: virtual ~A() = default; protected: virtual int foo() const { return 42; } }; class Trampoline : public A { public: int foo() const override { PYBIND11_OVERRIDE(int, A, foo, ); } }; class Publicist : public A { public: using A::foo; }; py::class_(m, "A") // <-- `Trampoline` here .def("foo", &Publicist::foo); // <-- `Publicist` here, not `Trampoline`! Binding final classes ===================== Some classes may not be appropriate to inherit from. In C++11, classes can use the ``final`` specifier to ensure that a class cannot be inherited from. The ``py::is_final`` attribute can be used to ensure that Python classes cannot inherit from a specified type. The underlying C++ type does not need to be declared final. .. code-block:: cpp class IsFinal final {}; py::class_(m, "IsFinal", py::is_final()); When you try to inherit from such a class in Python, you will now get this error: .. code-block:: pycon >>> class PyFinalChild(IsFinal): ... pass ... TypeError: type 'IsFinal' is not an acceptable base type .. note:: This attribute is currently ignored on PyPy .. versionadded:: 2.6 Binding classes with template parameters ======================================== pybind11 can also wrap classes that have template parameters. Consider these classes: .. code-block:: cpp struct Cat {}; struct Dog {}; template struct Cage { Cage(PetType& pet); PetType& get(); }; C++ templates may only be instantiated at compile time, so pybind11 can only wrap instantiated templated classes. You cannot wrap a non-instantiated template: .. code-block:: cpp // BROKEN (this will not compile) py::class_(m, "Cage"); .def("get", &Cage::get); You must explicitly specify each template/type combination that you want to wrap separately. .. code-block:: cpp // ok py::class_>(m, "CatCage") .def("get", &Cage::get); // ok py::class_>(m, "DogCage") .def("get", &Cage::get); If your class methods have template parameters you can wrap those as well, but once again each instantiation must be explicitly specified: .. code-block:: cpp typename struct MyClass { template T fn(V v); }; py::class>(m, "MyClassT") .def("fn", &MyClass::fn); Custom automatic downcasters ============================ As explained in :ref:`inheritance`, pybind11 comes with built-in understanding of the dynamic type of polymorphic objects in C++; that is, returning a Pet to Python produces a Python object that knows it's wrapping a Dog, if Pet has virtual methods and pybind11 knows about Dog and this Pet is in fact a Dog. Sometimes, you might want to provide this automatic downcasting behavior when creating bindings for a class hierarchy that does not use standard C++ polymorphism, such as LLVM [#f4]_. As long as there's some way to determine at runtime whether a downcast is safe, you can proceed by specializing the ``pybind11::polymorphic_type_hook`` template: .. code-block:: cpp enum class PetKind { Cat, Dog, Zebra }; struct Pet { // Not polymorphic: has no virtual methods const PetKind kind; int age = 0; protected: Pet(PetKind _kind) : kind(_kind) {} }; struct Dog : Pet { Dog() : Pet(PetKind::Dog) {} std::string sound = "woof!"; std::string bark() const { return sound; } }; namespace PYBIND11_NAMESPACE { template<> struct polymorphic_type_hook { static const void *get(const Pet *src, const std::type_info*& type) { // note that src may be nullptr if (src && src->kind == PetKind::Dog) { type = &typeid(Dog); return static_cast(src); } return src; } }; } // namespace PYBIND11_NAMESPACE When pybind11 wants to convert a C++ pointer of type ``Base*`` to a Python object, it calls ``polymorphic_type_hook::get()`` to determine if a downcast is possible. The ``get()`` function should use whatever runtime information is available to determine if its ``src`` parameter is in fact an instance of some class ``Derived`` that inherits from ``Base``. If it finds such a ``Derived``, it sets ``type = &typeid(Derived)`` and returns a pointer to the ``Derived`` object that contains ``src``. Otherwise, it just returns ``src``, leaving ``type`` at its default value of nullptr. If you set ``type`` to a type that pybind11 doesn't know about, no downcasting will occur, and the original ``src`` pointer will be used with its static type ``Base*``. It is critical that the returned pointer and ``type`` argument of ``get()`` agree with each other: if ``type`` is set to something non-null, the returned pointer must point to the start of an object whose type is ``type``. If the hierarchy being exposed uses only single inheritance, a simple ``return src;`` will achieve this just fine, but in the general case, you must cast ``src`` to the appropriate derived-class pointer (e.g. using ``static_cast(src)``) before allowing it to be returned as a ``void*``. .. [#f4] https://llvm.org/docs/HowToSetUpLLVMStyleRTTI.html .. note:: pybind11's standard support for downcasting objects whose types have virtual methods is implemented using ``polymorphic_type_hook`` too, using the standard C++ ability to determine the most-derived type of a polymorphic object using ``typeid()`` and to cast a base pointer to that most-derived type (even if you don't know what it is) using ``dynamic_cast``. .. seealso:: The file :file:`tests/test_tagbased_polymorphic.cpp` contains a more complete example, including a demonstration of how to provide automatic downcasting for an entire class hierarchy without writing one get() function for each class. Accessing the type object ========================= You can get the type object from a C++ class that has already been registered using: .. code-block:: cpp py::type T_py = py::type::of(); You can directly use ``py::type::of(ob)`` to get the type object from any python object, just like ``type(ob)`` in Python. .. note:: Other types, like ``py::type::of()``, do not work, see :ref:`type-conversions`. .. versionadded:: 2.6 Custom type setup ================= For advanced use cases, such as enabling garbage collection support, you may wish to directly manipulate the ``PyHeapTypeObject`` corresponding to a ``py::class_`` definition. You can do that using ``py::custom_type_setup``: .. code-block:: cpp struct OwnsPythonObjects { py::object value = py::none(); }; py::class_ cls( m, "OwnsPythonObjects", py::custom_type_setup([](PyHeapTypeObject *heap_type) { auto *type = &heap_type->ht_type; type->tp_flags |= Py_TPFLAGS_HAVE_GC; type->tp_traverse = [](PyObject *self_base, visitproc visit, void *arg) { auto &self = py::cast(py::handle(self_base)); Py_VISIT(self.value.ptr()); return 0; }; type->tp_clear = [](PyObject *self_base) { auto &self = py::cast(py::handle(self_base)); self.value = py::none(); return 0; }; })); cls.def(py::init<>()); cls.def_readwrite("value", &OwnsPythonObjects::value); .. versionadded:: 2.8 pybind11-2.13.6/docs/advanced/embedding.rst000066400000000000000000000204141467115402600204060ustar00rootroot00000000000000.. _embedding: Embedding the interpreter ######################### While pybind11 is mainly focused on extending Python using C++, it's also possible to do the reverse: embed the Python interpreter into a C++ program. All of the other documentation pages still apply here, so refer to them for general pybind11 usage. This section will cover a few extra things required for embedding. Getting started =============== A basic executable with an embedded interpreter can be created with just a few lines of CMake and the ``pybind11::embed`` target, as shown below. For more information, see :doc:`/compiling`. .. code-block:: cmake cmake_minimum_required(VERSION 3.5...3.29) project(example) find_package(pybind11 REQUIRED) # or `add_subdirectory(pybind11)` add_executable(example main.cpp) target_link_libraries(example PRIVATE pybind11::embed) The essential structure of the ``main.cpp`` file looks like this: .. code-block:: cpp #include // everything needed for embedding namespace py = pybind11; int main() { py::scoped_interpreter guard{}; // start the interpreter and keep it alive py::print("Hello, World!"); // use the Python API } The interpreter must be initialized before using any Python API, which includes all the functions and classes in pybind11. The RAII guard class ``scoped_interpreter`` takes care of the interpreter lifetime. After the guard is destroyed, the interpreter shuts down and clears its memory. No Python functions can be called after this. Executing Python code ===================== There are a few different ways to run Python code. One option is to use ``eval``, ``exec`` or ``eval_file``, as explained in :ref:`eval`. Here is a quick example in the context of an executable with an embedded interpreter: .. code-block:: cpp #include namespace py = pybind11; int main() { py::scoped_interpreter guard{}; py::exec(R"( kwargs = dict(name="World", number=42) message = "Hello, {name}! The answer is {number}".format(**kwargs) print(message) )"); } Alternatively, similar results can be achieved using pybind11's API (see :doc:`/advanced/pycpp/index` for more details). .. code-block:: cpp #include namespace py = pybind11; using namespace py::literals; int main() { py::scoped_interpreter guard{}; auto kwargs = py::dict("name"_a="World", "number"_a=42); auto message = "Hello, {name}! The answer is {number}"_s.format(**kwargs); py::print(message); } The two approaches can also be combined: .. code-block:: cpp #include #include namespace py = pybind11; using namespace py::literals; int main() { py::scoped_interpreter guard{}; auto locals = py::dict("name"_a="World", "number"_a=42); py::exec(R"( message = "Hello, {name}! The answer is {number}".format(**locals()) )", py::globals(), locals); auto message = locals["message"].cast(); std::cout << message; } Importing modules ================= Python modules can be imported using ``module_::import()``: .. code-block:: cpp py::module_ sys = py::module_::import("sys"); py::print(sys.attr("path")); For convenience, the current working directory is included in ``sys.path`` when embedding the interpreter. This makes it easy to import local Python files: .. code-block:: python """calc.py located in the working directory""" def add(i, j): return i + j .. code-block:: cpp py::module_ calc = py::module_::import("calc"); py::object result = calc.attr("add")(1, 2); int n = result.cast(); assert(n == 3); Modules can be reloaded using ``module_::reload()`` if the source is modified e.g. by an external process. This can be useful in scenarios where the application imports a user defined data processing script which needs to be updated after changes by the user. Note that this function does not reload modules recursively. .. _embedding_modules: Adding embedded modules ======================= Embedded binary modules can be added using the ``PYBIND11_EMBEDDED_MODULE`` macro. Note that the definition must be placed at global scope. They can be imported like any other module. .. code-block:: cpp #include namespace py = pybind11; PYBIND11_EMBEDDED_MODULE(fast_calc, m) { // `m` is a `py::module_` which is used to bind functions and classes m.def("add", [](int i, int j) { return i + j; }); } int main() { py::scoped_interpreter guard{}; auto fast_calc = py::module_::import("fast_calc"); auto result = fast_calc.attr("add")(1, 2).cast(); assert(result == 3); } Unlike extension modules where only a single binary module can be created, on the embedded side an unlimited number of modules can be added using multiple ``PYBIND11_EMBEDDED_MODULE`` definitions (as long as they have unique names). These modules are added to Python's list of builtins, so they can also be imported in pure Python files loaded by the interpreter. Everything interacts naturally: .. code-block:: python """py_module.py located in the working directory""" import cpp_module a = cpp_module.a b = a + 1 .. code-block:: cpp #include namespace py = pybind11; PYBIND11_EMBEDDED_MODULE(cpp_module, m) { m.attr("a") = 1; } int main() { py::scoped_interpreter guard{}; auto py_module = py::module_::import("py_module"); auto locals = py::dict("fmt"_a="{} + {} = {}", **py_module.attr("__dict__")); assert(locals["a"].cast() == 1); assert(locals["b"].cast() == 2); py::exec(R"( c = a + b message = fmt.format(a, b, c) )", py::globals(), locals); assert(locals["c"].cast() == 3); assert(locals["message"].cast() == "1 + 2 = 3"); } Interpreter lifetime ==================== The Python interpreter shuts down when ``scoped_interpreter`` is destroyed. After this, creating a new instance will restart the interpreter. Alternatively, the ``initialize_interpreter`` / ``finalize_interpreter`` pair of functions can be used to directly set the state at any time. Modules created with pybind11 can be safely re-initialized after the interpreter has been restarted. However, this may not apply to third-party extension modules. The issue is that Python itself cannot completely unload extension modules and there are several caveats with regard to interpreter restarting. In short, not all memory may be freed, either due to Python reference cycles or user-created global data. All the details can be found in the CPython documentation. .. warning:: Creating two concurrent ``scoped_interpreter`` guards is a fatal error. So is calling ``initialize_interpreter`` for a second time after the interpreter has already been initialized. Do not use the raw CPython API functions ``Py_Initialize`` and ``Py_Finalize`` as these do not properly handle the lifetime of pybind11's internal data. Sub-interpreter support ======================= Creating multiple copies of ``scoped_interpreter`` is not possible because it represents the main Python interpreter. Sub-interpreters are something different and they do permit the existence of multiple interpreters. This is an advanced feature of the CPython API and should be handled with care. pybind11 does not currently offer a C++ interface for sub-interpreters, so refer to the CPython documentation for all the details regarding this feature. We'll just mention a couple of caveats the sub-interpreters support in pybind11: 1. Sub-interpreters will not receive independent copies of embedded modules. Instead, these are shared and modifications in one interpreter may be reflected in another. 2. Managing multiple threads, multiple interpreters and the GIL can be challenging and there are several caveats here, even within the pure CPython API (please refer to the Python docs for details). As for pybind11, keep in mind that ``gil_scoped_release`` and ``gil_scoped_acquire`` do not take sub-interpreters into account. pybind11-2.13.6/docs/advanced/exceptions.rst000066400000000000000000000426661467115402600206660ustar00rootroot00000000000000Exceptions ########## Built-in C++ to Python exception translation ============================================ When Python calls C++ code through pybind11, pybind11 provides a C++ exception handler that will trap C++ exceptions, translate them to the corresponding Python exception, and raise them so that Python code can handle them. pybind11 defines translations for ``std::exception`` and its standard subclasses, and several special exception classes that translate to specific Python exceptions. Note that these are not actually Python exceptions, so they cannot be examined using the Python C API. Instead, they are pure C++ objects that pybind11 will translate the corresponding Python exception when they arrive at its exception handler. .. tabularcolumns:: |p{0.5\textwidth}|p{0.45\textwidth}| +--------------------------------------+--------------------------------------+ | Exception thrown by C++ | Translated to Python exception type | +======================================+======================================+ | :class:`std::exception` | ``RuntimeError`` | +--------------------------------------+--------------------------------------+ | :class:`std::bad_alloc` | ``MemoryError`` | +--------------------------------------+--------------------------------------+ | :class:`std::domain_error` | ``ValueError`` | +--------------------------------------+--------------------------------------+ | :class:`std::invalid_argument` | ``ValueError`` | +--------------------------------------+--------------------------------------+ | :class:`std::length_error` | ``ValueError`` | +--------------------------------------+--------------------------------------+ | :class:`std::out_of_range` | ``IndexError`` | +--------------------------------------+--------------------------------------+ | :class:`std::range_error` | ``ValueError`` | +--------------------------------------+--------------------------------------+ | :class:`std::overflow_error` | ``OverflowError`` | +--------------------------------------+--------------------------------------+ | :class:`pybind11::stop_iteration` | ``StopIteration`` (used to implement | | | custom iterators) | +--------------------------------------+--------------------------------------+ | :class:`pybind11::index_error` | ``IndexError`` (used to indicate out | | | of bounds access in ``__getitem__``, | | | ``__setitem__``, etc.) | +--------------------------------------+--------------------------------------+ | :class:`pybind11::key_error` | ``KeyError`` (used to indicate out | | | of bounds access in ``__getitem__``, | | | ``__setitem__`` in dict-like | | | objects, etc.) | +--------------------------------------+--------------------------------------+ | :class:`pybind11::value_error` | ``ValueError`` (used to indicate | | | wrong value passed in | | | ``container.remove(...)``) | +--------------------------------------+--------------------------------------+ | :class:`pybind11::type_error` | ``TypeError`` | +--------------------------------------+--------------------------------------+ | :class:`pybind11::buffer_error` | ``BufferError`` | +--------------------------------------+--------------------------------------+ | :class:`pybind11::import_error` | ``ImportError`` | +--------------------------------------+--------------------------------------+ | :class:`pybind11::attribute_error` | ``AttributeError`` | +--------------------------------------+--------------------------------------+ | Any other exception | ``RuntimeError`` | +--------------------------------------+--------------------------------------+ Exception translation is not bidirectional. That is, *catching* the C++ exceptions defined above will not trap exceptions that originate from Python. For that, catch :class:`pybind11::error_already_set`. See :ref:`below ` for further details. There is also a special exception :class:`cast_error` that is thrown by :func:`handle::call` when the input arguments cannot be converted to Python objects. Registering custom translators ============================== If the default exception conversion policy described above is insufficient, pybind11 also provides support for registering custom exception translators. Similar to pybind11 classes, exception translators can be local to the module they are defined in or global to the entire python session. To register a simple exception conversion that translates a C++ exception into a new Python exception using the C++ exception's ``what()`` method, a helper function is available: .. code-block:: cpp py::register_exception(module, "PyExp"); This call creates a Python exception class with the name ``PyExp`` in the given module and automatically converts any encountered exceptions of type ``CppExp`` into Python exceptions of type ``PyExp``. A matching function is available for registering a local exception translator: .. code-block:: cpp py::register_local_exception(module, "PyExp"); It is possible to specify base class for the exception using the third parameter, a ``handle``: .. code-block:: cpp py::register_exception(module, "PyExp", PyExc_RuntimeError); py::register_local_exception(module, "PyExp", PyExc_RuntimeError); Then ``PyExp`` can be caught both as ``PyExp`` and ``RuntimeError``. The class objects of the built-in Python exceptions are listed in the Python documentation on `Standard Exceptions `_. The default base class is ``PyExc_Exception``. When more advanced exception translation is needed, the functions ``py::register_exception_translator(translator)`` and ``py::register_local_exception_translator(translator)`` can be used to register functions that can translate arbitrary exception types (and which may include additional logic to do so). The functions takes a stateless callable (e.g. a function pointer or a lambda function without captured variables) with the call signature ``void(std::exception_ptr)``. When a C++ exception is thrown, the registered exception translators are tried in reverse order of registration (i.e. the last registered translator gets the first shot at handling the exception). All local translators will be tried before a global translator is tried. Inside the translator, ``std::rethrow_exception`` should be used within a try block to re-throw the exception. One or more catch clauses to catch the appropriate exceptions should then be used with each clause using ``py::set_error()`` (see below). To declare a custom Python exception type, declare a ``py::exception`` variable and use this in the associated exception translator (note: it is often useful to make this a static declaration when using it inside a lambda expression without requiring capturing). The following example demonstrates this for a hypothetical exception classes ``MyCustomException`` and ``OtherException``: the first is translated to a custom python exception ``MyCustomError``, while the second is translated to a standard python RuntimeError: .. code-block:: cpp PYBIND11_CONSTINIT static py::gil_safe_call_once_and_store exc_storage; exc_storage.call_once_and_store_result( [&]() { return py::exception(m, "MyCustomError"); }); py::register_exception_translator([](std::exception_ptr p) { try { if (p) std::rethrow_exception(p); } catch (const MyCustomException &e) { py::set_error(exc_storage.get_stored(), e.what()); } catch (const OtherException &e) { py::set_error(PyExc_RuntimeError, e.what()); } }); Multiple exceptions can be handled by a single translator, as shown in the example above. If the exception is not caught by the current translator, the previously registered one gets a chance. If none of the registered exception translators is able to handle the exception, it is handled by the default converter as described in the previous section. .. seealso:: The file :file:`tests/test_exceptions.cpp` contains examples of various custom exception translators and custom exception types. .. note:: Call ``py::set_error()`` for every exception caught in a custom exception translator. Failure to do so will cause Python to crash with ``SystemError: error return without exception set``. Exceptions that you do not plan to handle should simply not be caught, or may be explicitly (re-)thrown to delegate it to the other, previously-declared existing exception translators. Note that ``libc++`` and ``libstdc++`` `behave differently under macOS `_ with ``-fvisibility=hidden``. Therefore exceptions that are used across ABI boundaries need to be explicitly exported, as exercised in ``tests/test_exceptions.h``. See also: "Problems with C++ exceptions" under `GCC Wiki `_. Local vs Global Exception Translators ===================================== When a global exception translator is registered, it will be applied across all modules in the reverse order of registration. This can create behavior where the order of module import influences how exceptions are translated. If module1 has the following translator: .. code-block:: cpp py::register_exception_translator([](std::exception_ptr p) { try { if (p) std::rethrow_exception(p); } catch (const std::invalid_argument &e) { py::set_error(PyExc_ArgumentError, "module1 handled this"); } } and module2 has the following similar translator: .. code-block:: cpp py::register_exception_translator([](std::exception_ptr p) { try { if (p) std::rethrow_exception(p); } catch (const std::invalid_argument &e) { py::set_error(PyExc_ArgumentError, "module2 handled this"); } } then which translator handles the invalid_argument will be determined by the order that module1 and module2 are imported. Since exception translators are applied in the reverse order of registration, which ever module was imported last will "win" and that translator will be applied. If there are multiple pybind11 modules that share exception types (either standard built-in or custom) loaded into a single python instance and consistent error handling behavior is needed, then local translators should be used. Changing the previous example to use ``register_local_exception_translator`` would mean that when invalid_argument is thrown in the module2 code, the module2 translator will always handle it, while in module1, the module1 translator will do the same. .. _handling_python_exceptions_cpp: Handling exceptions from Python in C++ ====================================== When C++ calls Python functions, such as in a callback function or when manipulating Python objects, and Python raises an ``Exception``, pybind11 converts the Python exception into a C++ exception of type :class:`pybind11::error_already_set` whose payload contains a C++ string textual summary and the actual Python exception. ``error_already_set`` is used to propagate Python exception back to Python (or possibly, handle them in C++). .. tabularcolumns:: |p{0.5\textwidth}|p{0.45\textwidth}| +--------------------------------------+--------------------------------------+ | Exception raised in Python | Thrown as C++ exception type | +======================================+======================================+ | Any Python ``Exception`` | :class:`pybind11::error_already_set` | +--------------------------------------+--------------------------------------+ For example: .. code-block:: cpp try { // open("missing.txt", "r") auto file = py::module_::import("io").attr("open")("missing.txt", "r"); auto text = file.attr("read")(); file.attr("close")(); } catch (py::error_already_set &e) { if (e.matches(PyExc_FileNotFoundError)) { py::print("missing.txt not found"); } else if (e.matches(PyExc_PermissionError)) { py::print("missing.txt found but not accessible"); } else { throw; } } Note that C++ to Python exception translation does not apply here, since that is a method for translating C++ exceptions to Python, not vice versa. The error raised from Python is always ``error_already_set``. This example illustrates this behavior: .. code-block:: cpp try { py::eval("raise ValueError('The Ring')"); } catch (py::value_error &boromir) { // Boromir never gets the ring assert(false); } catch (py::error_already_set &frodo) { // Frodo gets the ring py::print("I will take the ring"); } try { // py::value_error is a request for pybind11 to raise a Python exception throw py::value_error("The ball"); } catch (py::error_already_set &cat) { // cat won't catch the ball since // py::value_error is not a Python exception assert(false); } catch (py::value_error &dog) { // dog will catch the ball py::print("Run Spot run"); throw; // Throw it again (pybind11 will raise ValueError) } Handling errors from the Python C API ===================================== Where possible, use :ref:`pybind11 wrappers ` instead of calling the Python C API directly. When calling the Python C API directly, in addition to manually managing reference counts, one must follow the pybind11 error protocol, which is outlined here. After calling the Python C API, if Python returns an error, ``throw py::error_already_set();``, which allows pybind11 to deal with the exception and pass it back to the Python interpreter. This includes calls to the error setting functions such as ``py::set_error()``. .. code-block:: cpp py::set_error(PyExc_TypeError, "C API type error demo"); throw py::error_already_set(); // But it would be easier to simply... throw py::type_error("pybind11 wrapper type error"); Alternately, to ignore the error, call `PyErr_Clear `_. Any Python error must be thrown or cleared, or Python/pybind11 will be left in an invalid state. Chaining exceptions ('raise from') ================================== Python has a mechanism for indicating that exceptions were caused by other exceptions: .. code-block:: py try: print(1 / 0) except Exception as exc: raise RuntimeError("could not divide by zero") from exc To do a similar thing in pybind11, you can use the ``py::raise_from`` function. It sets the current python error indicator, so to continue propagating the exception you should ``throw py::error_already_set()``. .. code-block:: cpp try { py::eval("print(1 / 0")); } catch (py::error_already_set &e) { py::raise_from(e, PyExc_RuntimeError, "could not divide by zero"); throw py::error_already_set(); } .. versionadded:: 2.8 .. _unraisable_exceptions: Handling unraisable exceptions ============================== If a Python function invoked from a C++ destructor or any function marked ``noexcept(true)`` (collectively, "noexcept functions") throws an exception, there is no way to propagate the exception, as such functions may not throw. Should they throw or fail to catch any exceptions in their call graph, the C++ runtime calls ``std::terminate()`` to abort immediately. Similarly, Python exceptions raised in a class's ``__del__`` method do not propagate, but are logged by Python as an unraisable error. In Python 3.8+, a `system hook is triggered `_ and an auditing event is logged. Any noexcept function should have a try-catch block that traps class:`error_already_set` (or any other exception that can occur). Note that pybind11 wrappers around Python exceptions such as :class:`pybind11::value_error` are *not* Python exceptions; they are C++ exceptions that pybind11 catches and converts to Python exceptions. Noexcept functions cannot propagate these exceptions either. A useful approach is to convert them to Python exceptions and then ``discard_as_unraisable`` as shown below. .. code-block:: cpp void nonthrowing_func() noexcept(true) { try { // ... } catch (py::error_already_set &eas) { // Discard the Python error using Python APIs, using the C++ magic // variable __func__. Python already knows the type and value and of the // exception object. eas.discard_as_unraisable(__func__); } catch (const std::exception &e) { // Log and discard C++ exceptions. third_party::log(e); } } .. versionadded:: 2.6 pybind11-2.13.6/docs/advanced/functions.rst000066400000000000000000000641471467115402600205130ustar00rootroot00000000000000Functions ######### Before proceeding with this section, make sure that you are already familiar with the basics of binding functions and classes, as explained in :doc:`/basics` and :doc:`/classes`. The following guide is applicable to both free and member functions, i.e. *methods* in Python. .. _return_value_policies: Return value policies ===================== Python and C++ use fundamentally different ways of managing the memory and lifetime of objects managed by them. This can lead to issues when creating bindings for functions that return a non-trivial type. Just by looking at the type information, it is not clear whether Python should take charge of the returned value and eventually free its resources, or if this is handled on the C++ side. For this reason, pybind11 provides several *return value policy* annotations that can be passed to the :func:`module_::def` and :func:`class_::def` functions. The default policy is :enum:`return_value_policy::automatic`. Return value policies are tricky, and it's very important to get them right. Just to illustrate what can go wrong, consider the following simple example: .. code-block:: cpp /* Function declaration */ Data *get_data() { return _data; /* (pointer to a static data structure) */ } ... /* Binding code */ m.def("get_data", &get_data); // <-- KABOOM, will cause crash when called from Python What's going on here? When ``get_data()`` is called from Python, the return value (a native C++ type) must be wrapped to turn it into a usable Python type. In this case, the default return value policy (:enum:`return_value_policy::automatic`) causes pybind11 to assume ownership of the static ``_data`` instance. When Python's garbage collector eventually deletes the Python wrapper, pybind11 will also attempt to delete the C++ instance (via ``operator delete()``) due to the implied ownership. At this point, the entire application will come crashing down, though errors could also be more subtle and involve silent data corruption. In the above example, the policy :enum:`return_value_policy::reference` should have been specified so that the global data instance is only *referenced* without any implied transfer of ownership, i.e.: .. code-block:: cpp m.def("get_data", &get_data, py::return_value_policy::reference); On the other hand, this is not the right policy for many other situations, where ignoring ownership could lead to resource leaks. As a developer using pybind11, it's important to be familiar with the different return value policies, including which situation calls for which one of them. The following table provides an overview of available policies: .. tabularcolumns:: |p{0.5\textwidth}|p{0.45\textwidth}| +--------------------------------------------------+----------------------------------------------------------------------------+ | Return value policy | Description | +==================================================+============================================================================+ | :enum:`return_value_policy::take_ownership` | Reference an existing object (i.e. do not create a new copy) and take | | | ownership. Python will call the destructor and delete operator when the | | | object's reference count reaches zero. Undefined behavior ensues when the | | | C++ side does the same, or when the data was not dynamically allocated. | +--------------------------------------------------+----------------------------------------------------------------------------+ | :enum:`return_value_policy::copy` | Create a new copy of the returned object, which will be owned by Python. | | | This policy is comparably safe because the lifetimes of the two instances | | | are decoupled. | +--------------------------------------------------+----------------------------------------------------------------------------+ | :enum:`return_value_policy::move` | Use ``std::move`` to move the return value contents into a new instance | | | that will be owned by Python. This policy is comparably safe because the | | | lifetimes of the two instances (move source and destination) are decoupled.| +--------------------------------------------------+----------------------------------------------------------------------------+ | :enum:`return_value_policy::reference` | Reference an existing object, but do not take ownership. The C++ side is | | | responsible for managing the object's lifetime and deallocating it when | | | it is no longer used. Warning: undefined behavior will ensue when the C++ | | | side deletes an object that is still referenced and used by Python. | +--------------------------------------------------+----------------------------------------------------------------------------+ | :enum:`return_value_policy::reference_internal` | Indicates that the lifetime of the return value is tied to the lifetime | | | of a parent object, namely the implicit ``this``, or ``self`` argument of | | | the called method or property. Internally, this policy works just like | | | :enum:`return_value_policy::reference` but additionally applies a | | | ``keep_alive<0, 1>`` *call policy* (described in the next section) that | | | prevents the parent object from being garbage collected as long as the | | | return value is referenced by Python. This is the default policy for | | | property getters created via ``def_property``, ``def_readwrite``, etc. | +--------------------------------------------------+----------------------------------------------------------------------------+ | :enum:`return_value_policy::automatic` | This policy falls back to the policy | | | :enum:`return_value_policy::take_ownership` when the return value is a | | | pointer. Otherwise, it uses :enum:`return_value_policy::move` or | | | :enum:`return_value_policy::copy` for rvalue and lvalue references, | | | respectively. See above for a description of what all of these different | | | policies do. This is the default policy for ``py::class_``-wrapped types. | +--------------------------------------------------+----------------------------------------------------------------------------+ | :enum:`return_value_policy::automatic_reference` | As above, but use policy :enum:`return_value_policy::reference` when the | | | return value is a pointer. This is the default conversion policy for | | | function arguments when calling Python functions manually from C++ code | | | (i.e. via ``handle::operator()``) and the casters in ``pybind11/stl.h``. | | | You probably won't need to use this explicitly. | +--------------------------------------------------+----------------------------------------------------------------------------+ Return value policies can also be applied to properties: .. code-block:: cpp class_(m, "MyClass") .def_property("data", &MyClass::getData, &MyClass::setData, py::return_value_policy::copy); Technically, the code above applies the policy to both the getter and the setter function, however, the setter doesn't really care about *return* value policies which makes this a convenient terse syntax. Alternatively, targeted arguments can be passed through the :class:`cpp_function` constructor: .. code-block:: cpp class_(m, "MyClass") .def_property("data", py::cpp_function(&MyClass::getData, py::return_value_policy::copy), py::cpp_function(&MyClass::setData) ); .. warning:: Code with invalid return value policies might access uninitialized memory or free data structures multiple times, which can lead to hard-to-debug non-determinism and segmentation faults, hence it is worth spending the time to understand all the different options in the table above. .. note:: One important aspect of the above policies is that they only apply to instances which pybind11 has *not* seen before, in which case the policy clarifies essential questions about the return value's lifetime and ownership. When pybind11 knows the instance already (as identified by its type and address in memory), it will return the existing Python object wrapper rather than creating a new copy. .. note:: The next section on :ref:`call_policies` discusses *call policies* that can be specified *in addition* to a return value policy from the list above. Call policies indicate reference relationships that can involve both return values and parameters of functions. .. note:: As an alternative to elaborate call policies and lifetime management logic, consider using smart pointers (see the section on :ref:`smart_pointers` for details). Smart pointers can tell whether an object is still referenced from C++ or Python, which generally eliminates the kinds of inconsistencies that can lead to crashes or undefined behavior. For functions returning smart pointers, it is not necessary to specify a return value policy. .. _call_policies: Additional call policies ======================== In addition to the above return value policies, further *call policies* can be specified to indicate dependencies between parameters or ensure a certain state for the function call. Keep alive ---------- In general, this policy is required when the C++ object is any kind of container and another object is being added to the container. ``keep_alive`` indicates that the argument with index ``Patient`` should be kept alive at least until the argument with index ``Nurse`` is freed by the garbage collector. Argument indices start at one, while zero refers to the return value. For methods, index ``1`` refers to the implicit ``this`` pointer, while regular arguments begin at index ``2``. Arbitrarily many call policies can be specified. When a ``Nurse`` with value ``None`` is detected at runtime, the call policy does nothing. When the nurse is not a pybind11-registered type, the implementation internally relies on the ability to create a *weak reference* to the nurse object. When the nurse object is not a pybind11-registered type and does not support weak references, an exception will be thrown. If you use an incorrect argument index, you will get a ``RuntimeError`` saying ``Could not activate keep_alive!``. You should review the indices you're using. Consider the following example: here, the binding code for a list append operation ties the lifetime of the newly added element to the underlying container: .. code-block:: cpp py::class_(m, "List") .def("append", &List::append, py::keep_alive<1, 2>()); For consistency, the argument indexing is identical for constructors. Index ``1`` still refers to the implicit ``this`` pointer, i.e. the object which is being constructed. Index ``0`` refers to the return type which is presumed to be ``void`` when a constructor is viewed like a function. The following example ties the lifetime of the constructor element to the constructed object: .. code-block:: cpp py::class_(m, "Nurse") .def(py::init(), py::keep_alive<1, 2>()); .. note:: ``keep_alive`` is analogous to the ``with_custodian_and_ward`` (if Nurse, Patient != 0) and ``with_custodian_and_ward_postcall`` (if Nurse/Patient == 0) policies from Boost.Python. Call guard ---------- The ``call_guard`` policy allows any scope guard type ``T`` to be placed around the function call. For example, this definition: .. code-block:: cpp m.def("foo", foo, py::call_guard()); is equivalent to the following pseudocode: .. code-block:: cpp m.def("foo", [](args...) { T scope_guard; return foo(args...); // forwarded arguments }); The only requirement is that ``T`` is default-constructible, but otherwise any scope guard will work. This is very useful in combination with ``gil_scoped_release``. See :ref:`gil`. Multiple guards can also be specified as ``py::call_guard``. The constructor order is left to right and destruction happens in reverse. .. seealso:: The file :file:`tests/test_call_policies.cpp` contains a complete example that demonstrates using `keep_alive` and `call_guard` in more detail. .. _python_objects_as_args: Python objects as arguments =========================== pybind11 exposes all major Python types using thin C++ wrapper classes. These wrapper classes can also be used as parameters of functions in bindings, which makes it possible to directly work with native Python types on the C++ side. For instance, the following statement iterates over a Python ``dict``: .. code-block:: cpp void print_dict(const py::dict& dict) { /* Easily interact with Python types */ for (auto item : dict) std::cout << "key=" << std::string(py::str(item.first)) << ", " << "value=" << std::string(py::str(item.second)) << std::endl; } It can be exported: .. code-block:: cpp m.def("print_dict", &print_dict); And used in Python as usual: .. code-block:: pycon >>> print_dict({"foo": 123, "bar": "hello"}) key=foo, value=123 key=bar, value=hello For more information on using Python objects in C++, see :doc:`/advanced/pycpp/index`. Accepting \*args and \*\*kwargs =============================== Python provides a useful mechanism to define functions that accept arbitrary numbers of arguments and keyword arguments: .. code-block:: python def generic(*args, **kwargs): ... # do something with args and kwargs Such functions can also be created using pybind11: .. code-block:: cpp void generic(py::args args, const py::kwargs& kwargs) { /// .. do something with args if (kwargs) /// .. do something with kwargs } /// Binding code m.def("generic", &generic); The class ``py::args`` derives from ``py::tuple`` and ``py::kwargs`` derives from ``py::dict``. You may also use just one or the other, and may combine these with other arguments. Note, however, that ``py::kwargs`` must always be the last argument of the function, and ``py::args`` implies that any further arguments are keyword-only (see :ref:`keyword_only_arguments`). Please refer to the other examples for details on how to iterate over these, and on how to cast their entries into C++ objects. A demonstration is also available in ``tests/test_kwargs_and_defaults.cpp``. .. note:: When combining \*args or \*\*kwargs with :ref:`keyword_args` you should *not* include ``py::arg`` tags for the ``py::args`` and ``py::kwargs`` arguments. Default arguments revisited =========================== The section on :ref:`default_args` previously discussed basic usage of default arguments using pybind11. One noteworthy aspect of their implementation is that default arguments are converted to Python objects right at declaration time. Consider the following example: .. code-block:: cpp py::class_("MyClass") .def("myFunction", py::arg("arg") = SomeType(123)); In this case, pybind11 must already be set up to deal with values of the type ``SomeType`` (via a prior instantiation of ``py::class_``), or an exception will be thrown. Another aspect worth highlighting is that the "preview" of the default argument in the function signature is generated using the object's ``__repr__`` method. If not available, the signature may not be very helpful, e.g.: .. code-block:: pycon FUNCTIONS ... | myFunction(...) | Signature : (MyClass, arg : SomeType = ) -> NoneType ... The first way of addressing this is by defining ``SomeType.__repr__``. Alternatively, it is possible to specify the human-readable preview of the default argument manually using the ``arg_v`` notation: .. code-block:: cpp py::class_("MyClass") .def("myFunction", py::arg_v("arg", SomeType(123), "SomeType(123)")); Sometimes it may be necessary to pass a null pointer value as a default argument. In this case, remember to cast it to the underlying type in question, like so: .. code-block:: cpp py::class_("MyClass") .def("myFunction", py::arg("arg") = static_cast(nullptr)); .. _keyword_only_arguments: Keyword-only arguments ====================== Python implements keyword-only arguments by specifying an unnamed ``*`` argument in a function definition: .. code-block:: python def f(a, *, b): # a can be positional or via keyword; b must be via keyword pass f(a=1, b=2) # good f(b=2, a=1) # good f(1, b=2) # good f(1, 2) # TypeError: f() takes 1 positional argument but 2 were given Pybind11 provides a ``py::kw_only`` object that allows you to implement the same behaviour by specifying the object between positional and keyword-only argument annotations when registering the function: .. code-block:: cpp m.def("f", [](int a, int b) { /* ... */ }, py::arg("a"), py::kw_only(), py::arg("b")); .. versionadded:: 2.6 A ``py::args`` argument implies that any following arguments are keyword-only, as if ``py::kw_only()`` had been specified in the same relative location of the argument list as the ``py::args`` argument. The ``py::kw_only()`` may be included to be explicit about this, but is not required. .. versionchanged:: 2.9 This can now be combined with ``py::args``. Before, ``py::args`` could only occur at the end of the argument list, or immediately before a ``py::kwargs`` argument at the end. Positional-only arguments ========================= Python 3.8 introduced a new positional-only argument syntax, using ``/`` in the function definition (note that this has been a convention for CPython positional arguments, such as in ``pow()``, since Python 2). You can do the same thing in any version of Python using ``py::pos_only()``: .. code-block:: cpp m.def("f", [](int a, int b) { /* ... */ }, py::arg("a"), py::pos_only(), py::arg("b")); You now cannot give argument ``a`` by keyword. This can be combined with keyword-only arguments, as well. .. versionadded:: 2.6 .. _nonconverting_arguments: Non-converting arguments ======================== Certain argument types may support conversion from one type to another. Some examples of conversions are: * :ref:`implicit_conversions` declared using ``py::implicitly_convertible()`` * Calling a method accepting a double with an integer argument * Calling a ``std::complex`` argument with a non-complex python type (for example, with a float). (Requires the optional ``pybind11/complex.h`` header). * Calling a function taking an Eigen matrix reference with a numpy array of the wrong type or of an incompatible data layout. (Requires the optional ``pybind11/eigen.h`` header). This behaviour is sometimes undesirable: the binding code may prefer to raise an error rather than convert the argument. This behaviour can be obtained through ``py::arg`` by calling the ``.noconvert()`` method of the ``py::arg`` object, such as: .. code-block:: cpp m.def("floats_only", [](double f) { return 0.5 * f; }, py::arg("f").noconvert()); m.def("floats_preferred", [](double f) { return 0.5 * f; }, py::arg("f")); Attempting the call the second function (the one without ``.noconvert()``) with an integer will succeed, but attempting to call the ``.noconvert()`` version will fail with a ``TypeError``: .. code-block:: pycon >>> floats_preferred(4) 2.0 >>> floats_only(4) Traceback (most recent call last): File "", line 1, in TypeError: floats_only(): incompatible function arguments. The following argument types are supported: 1. (f: float) -> float Invoked with: 4 You may, of course, combine this with the :var:`_a` shorthand notation (see :ref:`keyword_args`) and/or :ref:`default_args`. It is also permitted to omit the argument name by using the ``py::arg()`` constructor without an argument name, i.e. by specifying ``py::arg().noconvert()``. .. note:: When specifying ``py::arg`` options it is necessary to provide the same number of options as the bound function has arguments. Thus if you want to enable no-convert behaviour for just one of several arguments, you will need to specify a ``py::arg()`` annotation for each argument with the no-convert argument modified to ``py::arg().noconvert()``. .. _none_arguments: Allow/Prohibiting None arguments ================================ When a C++ type registered with :class:`py::class_` is passed as an argument to a function taking the instance as pointer or shared holder (e.g. ``shared_ptr`` or a custom, copyable holder as described in :ref:`smart_pointers`), pybind allows ``None`` to be passed from Python which results in calling the C++ function with ``nullptr`` (or an empty holder) for the argument. To explicitly enable or disable this behaviour, using the ``.none`` method of the :class:`py::arg` object: .. code-block:: cpp py::class_(m, "Dog").def(py::init<>()); py::class_(m, "Cat").def(py::init<>()); m.def("bark", [](Dog *dog) -> std::string { if (dog) return "woof!"; /* Called with a Dog instance */ else return "(no dog)"; /* Called with None, dog == nullptr */ }, py::arg("dog").none(true)); m.def("meow", [](Cat *cat) -> std::string { // Can't be called with None argument return "meow"; }, py::arg("cat").none(false)); With the above, the Python call ``bark(None)`` will return the string ``"(no dog)"``, while attempting to call ``meow(None)`` will raise a ``TypeError``: .. code-block:: pycon >>> from animals import Dog, Cat, bark, meow >>> bark(Dog()) 'woof!' >>> meow(Cat()) 'meow' >>> bark(None) '(no dog)' >>> meow(None) Traceback (most recent call last): File "", line 1, in TypeError: meow(): incompatible function arguments. The following argument types are supported: 1. (cat: animals.Cat) -> str Invoked with: None The default behaviour when the tag is unspecified is to allow ``None``. .. note:: Even when ``.none(true)`` is specified for an argument, ``None`` will be converted to a ``nullptr`` *only* for custom and :ref:`opaque ` types. Pointers to built-in types (``double *``, ``int *``, ...) and STL types (``std::vector *``, ...; if ``pybind11/stl.h`` is included) are copied when converted to C++ (see :doc:`/advanced/cast/overview`) and will not allow ``None`` as argument. To pass optional argument of these copied types consider using ``std::optional`` .. _overload_resolution: Overload resolution order ========================= When a function or method with multiple overloads is called from Python, pybind11 determines which overload to call in two passes. The first pass attempts to call each overload without allowing argument conversion (as if every argument had been specified as ``py::arg().noconvert()`` as described above). If no overload succeeds in the no-conversion first pass, a second pass is attempted in which argument conversion is allowed (except where prohibited via an explicit ``py::arg().noconvert()`` attribute in the function definition). If the second pass also fails a ``TypeError`` is raised. Within each pass, overloads are tried in the order they were registered with pybind11. If the ``py::prepend()`` tag is added to the definition, a function can be placed at the beginning of the overload sequence instead, allowing user overloads to proceed built in functions. What this means in practice is that pybind11 will prefer any overload that does not require conversion of arguments to an overload that does, but otherwise prefers earlier-defined overloads to later-defined ones. .. note:: pybind11 does *not* further prioritize based on the number/pattern of overloaded arguments. That is, pybind11 does not prioritize a function requiring one conversion over one requiring three, but only prioritizes overloads requiring no conversion at all to overloads that require conversion of at least one argument. .. versionadded:: 2.6 The ``py::prepend()`` tag. Binding functions with template parameters ========================================== You can bind functions that have template parameters. Here's a function: .. code-block:: cpp template void set(T t); C++ templates cannot be instantiated at runtime, so you cannot bind the non-instantiated function: .. code-block:: cpp // BROKEN (this will not compile) m.def("set", &set); You must bind each instantiated function template separately. You may bind each instantiation with the same name, which will be treated the same as an overloaded function: .. code-block:: cpp m.def("set", &set); m.def("set", &set); Sometimes it's more clear to bind them with separate names, which is also an option: .. code-block:: cpp m.def("setInt", &set); m.def("setString", &set); pybind11-2.13.6/docs/advanced/misc.rst000066400000000000000000000403071467115402600174260ustar00rootroot00000000000000Miscellaneous ############# .. _macro_notes: General notes regarding convenience macros ========================================== pybind11 provides a few convenience macros such as :func:`PYBIND11_DECLARE_HOLDER_TYPE` and ``PYBIND11_OVERRIDE_*``. Since these are "just" macros that are evaluated in the preprocessor (which has no concept of types), they *will* get confused by commas in a template argument; for example, consider: .. code-block:: cpp PYBIND11_OVERRIDE(MyReturnType, Class, func) The limitation of the C preprocessor interprets this as five arguments (with new arguments beginning after each comma) rather than three. To get around this, there are two alternatives: you can use a type alias, or you can wrap the type using the ``PYBIND11_TYPE`` macro: .. code-block:: cpp // Version 1: using a type alias using ReturnType = MyReturnType; using ClassType = Class; PYBIND11_OVERRIDE(ReturnType, ClassType, func); // Version 2: using the PYBIND11_TYPE macro: PYBIND11_OVERRIDE(PYBIND11_TYPE(MyReturnType), PYBIND11_TYPE(Class), func) The ``PYBIND11_MAKE_OPAQUE`` macro does *not* require the above workarounds. .. _gil: Global Interpreter Lock (GIL) ============================= The Python C API dictates that the Global Interpreter Lock (GIL) must always be held by the current thread to safely access Python objects. As a result, when Python calls into C++ via pybind11 the GIL must be held, and pybind11 will never implicitly release the GIL. .. code-block:: cpp void my_function() { /* GIL is held when this function is called from Python */ } PYBIND11_MODULE(example, m) { m.def("my_function", &my_function); } pybind11 will ensure that the GIL is held when it knows that it is calling Python code. For example, if a Python callback is passed to C++ code via ``std::function``, when C++ code calls the function the built-in wrapper will acquire the GIL before calling the Python callback. Similarly, the ``PYBIND11_OVERRIDE`` family of macros will acquire the GIL before calling back into Python. When writing C++ code that is called from other C++ code, if that code accesses Python state, it must explicitly acquire and release the GIL. The classes :class:`gil_scoped_release` and :class:`gil_scoped_acquire` can be used to acquire and release the global interpreter lock in the body of a C++ function call. In this way, long-running C++ code can be parallelized using multiple Python threads, **but great care must be taken** when any :class:`gil_scoped_release` appear: if there is any way that the C++ code can access Python objects, :class:`gil_scoped_acquire` should be used to reacquire the GIL. Taking :ref:`overriding_virtuals` as an example, this could be realized as follows (important changes highlighted): .. code-block:: cpp :emphasize-lines: 8,30,31 class PyAnimal : public Animal { public: /* Inherit the constructors */ using Animal::Animal; /* Trampoline (need one for each virtual function) */ std::string go(int n_times) { /* PYBIND11_OVERRIDE_PURE will acquire the GIL before accessing Python state */ PYBIND11_OVERRIDE_PURE( std::string, /* Return type */ Animal, /* Parent class */ go, /* Name of function */ n_times /* Argument(s) */ ); } }; PYBIND11_MODULE(example, m) { py::class_ animal(m, "Animal"); animal .def(py::init<>()) .def("go", &Animal::go); py::class_(m, "Dog", animal) .def(py::init<>()); m.def("call_go", [](Animal *animal) -> std::string { // GIL is held when called from Python code. Release GIL before // calling into (potentially long-running) C++ code py::gil_scoped_release release; return call_go(animal); }); } The ``call_go`` wrapper can also be simplified using the ``call_guard`` policy (see :ref:`call_policies`) which yields the same result: .. code-block:: cpp m.def("call_go", &call_go, py::call_guard()); Common Sources Of Global Interpreter Lock Errors ================================================================== Failing to properly hold the Global Interpreter Lock (GIL) is one of the more common sources of bugs within code that uses pybind11. If you are running into GIL related errors, we highly recommend you consult the following checklist. - Do you have any global variables that are pybind11 objects or invoke pybind11 functions in either their constructor or destructor? You are generally not allowed to invoke any Python function in a global static context. We recommend using lazy initialization and then intentionally leaking at the end of the program. - Do you have any pybind11 objects that are members of other C++ structures? One commonly overlooked requirement is that pybind11 objects have to increase their reference count whenever their copy constructor is called. Thus, you need to be holding the GIL to invoke the copy constructor of any C++ class that has a pybind11 member. This can sometimes be very tricky to track for complicated programs Think carefully when you make a pybind11 object a member in another struct. - C++ destructors that invoke Python functions can be particularly troublesome as destructors can sometimes get invoked in weird and unexpected circumstances as a result of exceptions. - You should try running your code in a debug build. That will enable additional assertions within pybind11 that will throw exceptions on certain GIL handling errors (reference counting operations). Binding sequence data types, iterators, the slicing protocol, etc. ================================================================== Please refer to the supplemental example for details. .. seealso:: The file :file:`tests/test_sequences_and_iterators.cpp` contains a complete example that shows how to bind a sequence data type, including length queries (``__len__``), iterators (``__iter__``), the slicing protocol and other kinds of useful operations. Partitioning code over multiple extension modules ================================================= It's straightforward to split binding code over multiple extension modules, while referencing types that are declared elsewhere. Everything "just" works without any special precautions. One exception to this rule occurs when extending a type declared in another extension module. Recall the basic example from Section :ref:`inheritance`. .. code-block:: cpp py::class_ pet(m, "Pet"); pet.def(py::init()) .def_readwrite("name", &Pet::name); py::class_(m, "Dog", pet /* <- specify parent */) .def(py::init()) .def("bark", &Dog::bark); Suppose now that ``Pet`` bindings are defined in a module named ``basic``, whereas the ``Dog`` bindings are defined somewhere else. The challenge is of course that the variable ``pet`` is not available anymore though it is needed to indicate the inheritance relationship to the constructor of ``class_``. However, it can be acquired as follows: .. code-block:: cpp py::object pet = (py::object) py::module_::import("basic").attr("Pet"); py::class_(m, "Dog", pet) .def(py::init()) .def("bark", &Dog::bark); Alternatively, you can specify the base class as a template parameter option to ``class_``, which performs an automated lookup of the corresponding Python type. Like the above code, however, this also requires invoking the ``import`` function once to ensure that the pybind11 binding code of the module ``basic`` has been executed: .. code-block:: cpp py::module_::import("basic"); py::class_(m, "Dog") .def(py::init()) .def("bark", &Dog::bark); Naturally, both methods will fail when there are cyclic dependencies. Note that pybind11 code compiled with hidden-by-default symbol visibility (e.g. via the command line flag ``-fvisibility=hidden`` on GCC/Clang), which is required for proper pybind11 functionality, can interfere with the ability to access types defined in another extension module. Working around this requires manually exporting types that are accessed by multiple extension modules; pybind11 provides a macro to do just this: .. code-block:: cpp class PYBIND11_EXPORT Dog : public Animal { ... }; Note also that it is possible (although would rarely be required) to share arbitrary C++ objects between extension modules at runtime. Internal library data is shared between modules using capsule machinery [#f6]_ which can be also utilized for storing, modifying and accessing user-defined data. Note that an extension module will "see" other extensions' data if and only if they were built with the same pybind11 version. Consider the following example: .. code-block:: cpp auto data = reinterpret_cast(py::get_shared_data("mydata")); if (!data) data = static_cast(py::set_shared_data("mydata", new MyData(42))); If the above snippet was used in several separately compiled extension modules, the first one to be imported would create a ``MyData`` instance and associate a ``"mydata"`` key with a pointer to it. Extensions that are imported later would be then able to access the data behind the same pointer. .. [#f6] https://docs.python.org/3/extending/extending.html#using-capsules Module Destructors ================== pybind11 does not provide an explicit mechanism to invoke cleanup code at module destruction time. In rare cases where such functionality is required, it is possible to emulate it using Python capsules or weak references with a destruction callback. .. code-block:: cpp auto cleanup_callback = []() { // perform cleanup here -- this function is called with the GIL held }; m.add_object("_cleanup", py::capsule(cleanup_callback)); This approach has the potential downside that instances of classes exposed within the module may still be alive when the cleanup callback is invoked (whether this is acceptable will generally depend on the application). Alternatively, the capsule may also be stashed within a type object, which ensures that it not called before all instances of that type have been collected: .. code-block:: cpp auto cleanup_callback = []() { /* ... */ }; m.attr("BaseClass").attr("_cleanup") = py::capsule(cleanup_callback); Both approaches also expose a potentially dangerous ``_cleanup`` attribute in Python, which may be undesirable from an API standpoint (a premature explicit call from Python might lead to undefined behavior). Yet another approach that avoids this issue involves weak reference with a cleanup callback: .. code-block:: cpp // Register a callback function that is invoked when the BaseClass object is collected py::cpp_function cleanup_callback( [](py::handle weakref) { // perform cleanup here -- this function is called with the GIL held weakref.dec_ref(); // release weak reference } ); // Create a weak reference with a cleanup callback and initially leak it (void) py::weakref(m.attr("BaseClass"), cleanup_callback).release(); .. note:: PyPy does not garbage collect objects when the interpreter exits. An alternative approach (which also works on CPython) is to use the :py:mod:`atexit` module [#f7]_, for example: .. code-block:: cpp auto atexit = py::module_::import("atexit"); atexit.attr("register")(py::cpp_function([]() { // perform cleanup here -- this function is called with the GIL held })); .. [#f7] https://docs.python.org/3/library/atexit.html Generating documentation using Sphinx ===================================== Sphinx [#f4]_ has the ability to inspect the signatures and documentation strings in pybind11-based extension modules to automatically generate beautiful documentation in a variety formats. The python_example repository [#f5]_ contains a simple example repository which uses this approach. There are two potential gotchas when using this approach: first, make sure that the resulting strings do not contain any :kbd:`TAB` characters, which break the docstring parsing routines. You may want to use C++11 raw string literals, which are convenient for multi-line comments. Conveniently, any excess indentation will be automatically be removed by Sphinx. However, for this to work, it is important that all lines are indented consistently, i.e.: .. code-block:: cpp // ok m.def("foo", &foo, R"mydelimiter( The foo function Parameters ---------- )mydelimiter"); // *not ok* m.def("foo", &foo, R"mydelimiter(The foo function Parameters ---------- )mydelimiter"); By default, pybind11 automatically generates and prepends a signature to the docstring of a function registered with ``module_::def()`` and ``class_::def()``. Sometimes this behavior is not desirable, because you want to provide your own signature or remove the docstring completely to exclude the function from the Sphinx documentation. The class ``options`` allows you to selectively suppress auto-generated signatures: .. code-block:: cpp PYBIND11_MODULE(example, m) { py::options options; options.disable_function_signatures(); m.def("add", [](int a, int b) { return a + b; }, "A function which adds two numbers"); } pybind11 also appends all members of an enum to the resulting enum docstring. This default behavior can be disabled by using the ``disable_enum_members_docstring()`` function of the ``options`` class. With ``disable_user_defined_docstrings()`` all user defined docstrings of ``module_::def()``, ``class_::def()`` and ``enum_()`` are disabled, but the function signatures and enum members are included in the docstring, unless they are disabled separately. Note that changes to the settings affect only function bindings created during the lifetime of the ``options`` instance. When it goes out of scope at the end of the module's init function, the default settings are restored to prevent unwanted side effects. .. [#f4] http://www.sphinx-doc.org .. [#f5] http://github.com/pybind/python_example .. _avoiding-cpp-types-in-docstrings: Avoiding C++ types in docstrings ================================ Docstrings are generated at the time of the declaration, e.g. when ``.def(...)`` is called. At this point parameter and return types should be known to pybind11. If a custom type is not exposed yet through a ``py::class_`` constructor or a custom type caster, its C++ type name will be used instead to generate the signature in the docstring: .. code-block:: text | __init__(...) | __init__(self: example.Foo, arg0: ns::Bar) -> None ^^^^^^^ This limitation can be circumvented by ensuring that C++ classes are registered with pybind11 before they are used as a parameter or return type of a function: .. code-block:: cpp PYBIND11_MODULE(example, m) { auto pyFoo = py::class_(m, "Foo"); auto pyBar = py::class_(m, "Bar"); pyFoo.def(py::init()); pyBar.def(py::init()); } Setting inner type hints in docstrings ====================================== When you use pybind11 wrappers for ``list``, ``dict``, and other generic python types, the docstring will just display the generic type. You can convey the inner types in the docstring by using a special 'typed' version of the generic type. .. code-block:: cpp PYBIND11_MODULE(example, m) { m.def("pass_list_of_str", [](py::typing::List arg) { // arg can be used just like py::list )); } The resulting docstring will be ``pass_list_of_str(arg0: list[str]) -> None``. The following special types are available in ``pybind11/typing.h``: * ``py::Tuple`` * ``py::Dict`` * ``py::List`` * ``py::Set`` * ``py::Callable`` .. warning:: Just like in python, these are merely hints. They don't actually enforce the types of their contents at runtime or compile time. pybind11-2.13.6/docs/advanced/pycpp/000077500000000000000000000000001467115402600170705ustar00rootroot00000000000000pybind11-2.13.6/docs/advanced/pycpp/index.rst000066400000000000000000000004261467115402600207330ustar00rootroot00000000000000Python C++ interface #################### pybind11 exposes Python types and functions using thin C++ wrappers, which makes it possible to conveniently call Python code from C++ without resorting to Python's C API. .. toctree:: :maxdepth: 2 object numpy utilities pybind11-2.13.6/docs/advanced/pycpp/numpy.rst000066400000000000000000000413301467115402600207730ustar00rootroot00000000000000.. _numpy: NumPy ##### Buffer protocol =============== Python supports an extremely general and convenient approach for exchanging data between plugin libraries. Types can expose a buffer view [#f2]_, which provides fast direct access to the raw internal data representation. Suppose we want to bind the following simplistic Matrix class: .. code-block:: cpp class Matrix { public: Matrix(size_t rows, size_t cols) : m_rows(rows), m_cols(cols) { m_data = new float[rows*cols]; } float *data() { return m_data; } size_t rows() const { return m_rows; } size_t cols() const { return m_cols; } private: size_t m_rows, m_cols; float *m_data; }; The following binding code exposes the ``Matrix`` contents as a buffer object, making it possible to cast Matrices into NumPy arrays. It is even possible to completely avoid copy operations with Python expressions like ``np.array(matrix_instance, copy = False)``. .. code-block:: cpp py::class_(m, "Matrix", py::buffer_protocol()) .def_buffer([](Matrix &m) -> py::buffer_info { return py::buffer_info( m.data(), /* Pointer to buffer */ sizeof(float), /* Size of one scalar */ py::format_descriptor::format(), /* Python struct-style format descriptor */ 2, /* Number of dimensions */ { m.rows(), m.cols() }, /* Buffer dimensions */ { sizeof(float) * m.cols(), /* Strides (in bytes) for each index */ sizeof(float) } ); }); Supporting the buffer protocol in a new type involves specifying the special ``py::buffer_protocol()`` tag in the ``py::class_`` constructor and calling the ``def_buffer()`` method with a lambda function that creates a ``py::buffer_info`` description record on demand describing a given matrix instance. The contents of ``py::buffer_info`` mirror the Python buffer protocol specification. .. code-block:: cpp struct buffer_info { void *ptr; py::ssize_t itemsize; std::string format; py::ssize_t ndim; std::vector shape; std::vector strides; }; To create a C++ function that can take a Python buffer object as an argument, simply use the type ``py::buffer`` as one of its arguments. Buffers can exist in a great variety of configurations, hence some safety checks are usually necessary in the function body. Below, you can see a basic example on how to define a custom constructor for the Eigen double precision matrix (``Eigen::MatrixXd``) type, which supports initialization from compatible buffer objects (e.g. a NumPy matrix). .. code-block:: cpp /* Bind MatrixXd (or some other Eigen type) to Python */ typedef Eigen::MatrixXd Matrix; typedef Matrix::Scalar Scalar; constexpr bool rowMajor = Matrix::Flags & Eigen::RowMajorBit; py::class_(m, "Matrix", py::buffer_protocol()) .def(py::init([](py::buffer b) { typedef Eigen::Stride Strides; /* Request a buffer descriptor from Python */ py::buffer_info info = b.request(); /* Some basic validation checks ... */ if (info.format != py::format_descriptor::format()) throw std::runtime_error("Incompatible format: expected a double array!"); if (info.ndim != 2) throw std::runtime_error("Incompatible buffer dimension!"); auto strides = Strides( info.strides[rowMajor ? 0 : 1] / (py::ssize_t)sizeof(Scalar), info.strides[rowMajor ? 1 : 0] / (py::ssize_t)sizeof(Scalar)); auto map = Eigen::Map( static_cast(info.ptr), info.shape[0], info.shape[1], strides); return Matrix(map); })); For reference, the ``def_buffer()`` call for this Eigen data type should look as follows: .. code-block:: cpp .def_buffer([](Matrix &m) -> py::buffer_info { return py::buffer_info( m.data(), /* Pointer to buffer */ sizeof(Scalar), /* Size of one scalar */ py::format_descriptor::format(), /* Python struct-style format descriptor */ 2, /* Number of dimensions */ { m.rows(), m.cols() }, /* Buffer dimensions */ { sizeof(Scalar) * (rowMajor ? m.cols() : 1), sizeof(Scalar) * (rowMajor ? 1 : m.rows()) } /* Strides (in bytes) for each index */ ); }) For a much easier approach of binding Eigen types (although with some limitations), refer to the section on :doc:`/advanced/cast/eigen`. .. seealso:: The file :file:`tests/test_buffers.cpp` contains a complete example that demonstrates using the buffer protocol with pybind11 in more detail. .. [#f2] http://docs.python.org/3/c-api/buffer.html Arrays ====== By exchanging ``py::buffer`` with ``py::array`` in the above snippet, we can restrict the function so that it only accepts NumPy arrays (rather than any type of Python object satisfying the buffer protocol). In many situations, we want to define a function which only accepts a NumPy array of a certain data type. This is possible via the ``py::array_t`` template. For instance, the following function requires the argument to be a NumPy array containing double precision values. .. code-block:: cpp void f(py::array_t array); When it is invoked with a different type (e.g. an integer or a list of integers), the binding code will attempt to cast the input into a NumPy array of the requested type. This feature requires the :file:`pybind11/numpy.h` header to be included. Note that :file:`pybind11/numpy.h` does not depend on the NumPy headers, and thus can be used without declaring a build-time dependency on NumPy; NumPy>=1.7.0 is a runtime dependency. Data in NumPy arrays is not guaranteed to packed in a dense manner; furthermore, entries can be separated by arbitrary column and row strides. Sometimes, it can be useful to require a function to only accept dense arrays using either the C (row-major) or Fortran (column-major) ordering. This can be accomplished via a second template argument with values ``py::array::c_style`` or ``py::array::f_style``. .. code-block:: cpp void f(py::array_t array); The ``py::array::forcecast`` argument is the default value of the second template parameter, and it ensures that non-conforming arguments are converted into an array satisfying the specified requirements instead of trying the next function overload. There are several methods on arrays; the methods listed below under references work, as well as the following functions based on the NumPy API: - ``.dtype()`` returns the type of the contained values. - ``.strides()`` returns a pointer to the strides of the array (optionally pass an integer axis to get a number). - ``.flags()`` returns the flag settings. ``.writable()`` and ``.owndata()`` are directly available. - ``.offset_at()`` returns the offset (optionally pass indices). - ``.squeeze()`` returns a view with length-1 axes removed. - ``.view(dtype)`` returns a view of the array with a different dtype. - ``.reshape({i, j, ...})`` returns a view of the array with a different shape. ``.resize({...})`` is also available. - ``.index_at(i, j, ...)`` gets the count from the beginning to a given index. There are also several methods for getting references (described below). Structured types ================ In order for ``py::array_t`` to work with structured (record) types, we first need to register the memory layout of the type. This can be done via ``PYBIND11_NUMPY_DTYPE`` macro, called in the plugin definition code, which expects the type followed by field names: .. code-block:: cpp struct A { int x; double y; }; struct B { int z; A a; }; // ... PYBIND11_MODULE(test, m) { // ... PYBIND11_NUMPY_DTYPE(A, x, y); PYBIND11_NUMPY_DTYPE(B, z, a); /* now both A and B can be used as template arguments to py::array_t */ } The structure should consist of fundamental arithmetic types, ``std::complex``, previously registered substructures, and arrays of any of the above. Both C++ arrays and ``std::array`` are supported. While there is a static assertion to prevent many types of unsupported structures, it is still the user's responsibility to use only "plain" structures that can be safely manipulated as raw memory without violating invariants. Vectorizing functions ===================== Suppose we want to bind a function with the following signature to Python so that it can process arbitrary NumPy array arguments (vectors, matrices, general N-D arrays) in addition to its normal arguments: .. code-block:: cpp double my_func(int x, float y, double z); After including the ``pybind11/numpy.h`` header, this is extremely simple: .. code-block:: cpp m.def("vectorized_func", py::vectorize(my_func)); Invoking the function like below causes 4 calls to be made to ``my_func`` with each of the array elements. The significant advantage of this compared to solutions like ``numpy.vectorize()`` is that the loop over the elements runs entirely on the C++ side and can be crunched down into a tight, optimized loop by the compiler. The result is returned as a NumPy array of type ``numpy.dtype.float64``. .. code-block:: pycon >>> x = np.array([[1, 3], [5, 7]]) >>> y = np.array([[2, 4], [6, 8]]) >>> z = 3 >>> result = vectorized_func(x, y, z) The scalar argument ``z`` is transparently replicated 4 times. The input arrays ``x`` and ``y`` are automatically converted into the right types (they are of type ``numpy.dtype.int64`` but need to be ``numpy.dtype.int32`` and ``numpy.dtype.float32``, respectively). .. note:: Only arithmetic, complex, and POD types passed by value or by ``const &`` reference are vectorized; all other arguments are passed through as-is. Functions taking rvalue reference arguments cannot be vectorized. In cases where the computation is too complicated to be reduced to ``vectorize``, it will be necessary to create and access the buffer contents manually. The following snippet contains a complete example that shows how this works (the code is somewhat contrived, since it could have been done more simply using ``vectorize``). .. code-block:: cpp #include #include namespace py = pybind11; py::array_t add_arrays(py::array_t input1, py::array_t input2) { py::buffer_info buf1 = input1.request(), buf2 = input2.request(); if (buf1.ndim != 1 || buf2.ndim != 1) throw std::runtime_error("Number of dimensions must be one"); if (buf1.size != buf2.size) throw std::runtime_error("Input shapes must match"); /* No pointer is passed, so NumPy will allocate the buffer */ auto result = py::array_t(buf1.size); py::buffer_info buf3 = result.request(); double *ptr1 = static_cast(buf1.ptr); double *ptr2 = static_cast(buf2.ptr); double *ptr3 = static_cast(buf3.ptr); for (size_t idx = 0; idx < buf1.shape[0]; idx++) ptr3[idx] = ptr1[idx] + ptr2[idx]; return result; } PYBIND11_MODULE(test, m) { m.def("add_arrays", &add_arrays, "Add two NumPy arrays"); } .. seealso:: The file :file:`tests/test_numpy_vectorize.cpp` contains a complete example that demonstrates using :func:`vectorize` in more detail. Direct access ============= For performance reasons, particularly when dealing with very large arrays, it is often desirable to directly access array elements without internal checking of dimensions and bounds on every access when indices are known to be already valid. To avoid such checks, the ``array`` class and ``array_t`` template class offer an unchecked proxy object that can be used for this unchecked access through the ``unchecked`` and ``mutable_unchecked`` methods, where ``N`` gives the required dimensionality of the array: .. code-block:: cpp m.def("sum_3d", [](py::array_t x) { auto r = x.unchecked<3>(); // x must have ndim = 3; can be non-writeable double sum = 0; for (py::ssize_t i = 0; i < r.shape(0); i++) for (py::ssize_t j = 0; j < r.shape(1); j++) for (py::ssize_t k = 0; k < r.shape(2); k++) sum += r(i, j, k); return sum; }); m.def("increment_3d", [](py::array_t x) { auto r = x.mutable_unchecked<3>(); // Will throw if ndim != 3 or flags.writeable is false for (py::ssize_t i = 0; i < r.shape(0); i++) for (py::ssize_t j = 0; j < r.shape(1); j++) for (py::ssize_t k = 0; k < r.shape(2); k++) r(i, j, k) += 1.0; }, py::arg().noconvert()); To obtain the proxy from an ``array`` object, you must specify both the data type and number of dimensions as template arguments, such as ``auto r = myarray.mutable_unchecked()``. If the number of dimensions is not known at compile time, you can omit the dimensions template parameter (i.e. calling ``arr_t.unchecked()`` or ``arr.unchecked()``. This will give you a proxy object that works in the same way, but results in less optimizable code and thus a small efficiency loss in tight loops. Note that the returned proxy object directly references the array's data, and only reads its shape, strides, and writeable flag when constructed. You must take care to ensure that the referenced array is not destroyed or reshaped for the duration of the returned object, typically by limiting the scope of the returned instance. The returned proxy object supports some of the same methods as ``py::array`` so that it can be used as a drop-in replacement for some existing, index-checked uses of ``py::array``: - ``.ndim()`` returns the number of dimensions - ``.data(1, 2, ...)`` and ``r.mutable_data(1, 2, ...)``` returns a pointer to the ``const T`` or ``T`` data, respectively, at the given indices. The latter is only available to proxies obtained via ``a.mutable_unchecked()``. - ``.itemsize()`` returns the size of an item in bytes, i.e. ``sizeof(T)``. - ``.shape(n)`` returns the size of dimension ``n`` - ``.size()`` returns the total number of elements (i.e. the product of the shapes). - ``.nbytes()`` returns the number of bytes used by the referenced elements (i.e. ``itemsize()`` times ``size()``). .. seealso:: The file :file:`tests/test_numpy_array.cpp` contains additional examples demonstrating the use of this feature. Ellipsis ======== Python provides a convenient ``...`` ellipsis notation that is often used to slice multidimensional arrays. For instance, the following snippet extracts the middle dimensions of a tensor with the first and last index set to zero. .. code-block:: python a = ... # a NumPy array b = a[0, ..., 0] The function ``py::ellipsis()`` function can be used to perform the same operation on the C++ side: .. code-block:: cpp py::array a = /* A NumPy array */; py::array b = a[py::make_tuple(0, py::ellipsis(), 0)]; Memory view =========== For a case when we simply want to provide a direct accessor to C/C++ buffer without a concrete class object, we can return a ``memoryview`` object. Suppose we wish to expose a ``memoryview`` for 2x4 uint8_t array, we can do the following: .. code-block:: cpp const uint8_t buffer[] = { 0, 1, 2, 3, 4, 5, 6, 7 }; m.def("get_memoryview2d", []() { return py::memoryview::from_buffer( buffer, // buffer pointer { 2, 4 }, // shape (rows, cols) { sizeof(uint8_t) * 4, sizeof(uint8_t) } // strides in bytes ); }); This approach is meant for providing a ``memoryview`` for a C/C++ buffer not managed by Python. The user is responsible for managing the lifetime of the buffer. Using a ``memoryview`` created in this way after deleting the buffer in C++ side results in undefined behavior. We can also use ``memoryview::from_memory`` for a simple 1D contiguous buffer: .. code-block:: cpp m.def("get_memoryview1d", []() { return py::memoryview::from_memory( buffer, // buffer pointer sizeof(uint8_t) * 8 // buffer size ); }); .. versionchanged:: 2.6 ``memoryview::from_memory`` added. pybind11-2.13.6/docs/advanced/pycpp/object.rst000066400000000000000000000215061467115402600210740ustar00rootroot00000000000000Python types ############ .. _wrappers: Available wrappers ================== All major Python types are available as thin C++ wrapper classes. These can also be used as function parameters -- see :ref:`python_objects_as_args`. Available types include :class:`handle`, :class:`object`, :class:`bool_`, :class:`int_`, :class:`float_`, :class:`str`, :class:`bytes`, :class:`tuple`, :class:`list`, :class:`dict`, :class:`slice`, :class:`none`, :class:`capsule`, :class:`iterable`, :class:`iterator`, :class:`function`, :class:`buffer`, :class:`array`, and :class:`array_t`. .. warning:: Be sure to review the :ref:`pytypes_gotchas` before using this heavily in your C++ API. .. _instantiating_compound_types: Instantiating compound Python types from C++ ============================================ Dictionaries can be initialized in the :class:`dict` constructor: .. code-block:: cpp using namespace pybind11::literals; // to bring in the `_a` literal py::dict d("spam"_a=py::none(), "eggs"_a=42); A tuple of python objects can be instantiated using :func:`py::make_tuple`: .. code-block:: cpp py::tuple tup = py::make_tuple(42, py::none(), "spam"); Each element is converted to a supported Python type. A `simple namespace`_ can be instantiated using .. code-block:: cpp using namespace pybind11::literals; // to bring in the `_a` literal py::object SimpleNamespace = py::module_::import("types").attr("SimpleNamespace"); py::object ns = SimpleNamespace("spam"_a=py::none(), "eggs"_a=42); Attributes on a namespace can be modified with the :func:`py::delattr`, :func:`py::getattr`, and :func:`py::setattr` functions. Simple namespaces can be useful as lightweight stand-ins for class instances. .. _simple namespace: https://docs.python.org/3/library/types.html#types.SimpleNamespace .. _casting_back_and_forth: Casting back and forth ====================== In this kind of mixed code, it is often necessary to convert arbitrary C++ types to Python, which can be done using :func:`py::cast`: .. code-block:: cpp MyClass *cls = ...; py::object obj = py::cast(cls); The reverse direction uses the following syntax: .. code-block:: cpp py::object obj = ...; MyClass *cls = obj.cast(); When conversion fails, both directions throw the exception :class:`cast_error`. .. _python_libs: Accessing Python libraries from C++ =================================== It is also possible to import objects defined in the Python standard library or available in the current Python environment (``sys.path``) and work with these in C++. This example obtains a reference to the Python ``Decimal`` class. .. code-block:: cpp // Equivalent to "from decimal import Decimal" py::object Decimal = py::module_::import("decimal").attr("Decimal"); .. code-block:: cpp // Try to import scipy py::object scipy = py::module_::import("scipy"); return scipy.attr("__version__"); .. _calling_python_functions: Calling Python functions ======================== It is also possible to call Python classes, functions and methods via ``operator()``. .. code-block:: cpp // Construct a Python object of class Decimal py::object pi = Decimal("3.14159"); .. code-block:: cpp // Use Python to make our directories py::object os = py::module_::import("os"); py::object makedirs = os.attr("makedirs"); makedirs("/tmp/path/to/somewhere"); One can convert the result obtained from Python to a pure C++ version if a ``py::class_`` or type conversion is defined. .. code-block:: cpp py::function f = <...>; py::object result_py = f(1234, "hello", some_instance); MyClass &result = result_py.cast(); .. _calling_python_methods: Calling Python methods ======================== To call an object's method, one can again use ``.attr`` to obtain access to the Python method. .. code-block:: cpp // Calculate e^π in decimal py::object exp_pi = pi.attr("exp")(); py::print(py::str(exp_pi)); In the example above ``pi.attr("exp")`` is a *bound method*: it will always call the method for that same instance of the class. Alternately one can create an *unbound method* via the Python class (instead of instance) and pass the ``self`` object explicitly, followed by other arguments. .. code-block:: cpp py::object decimal_exp = Decimal.attr("exp"); // Compute the e^n for n=0..4 for (int n = 0; n < 5; n++) { py::print(decimal_exp(Decimal(n)); } Keyword arguments ================= Keyword arguments are also supported. In Python, there is the usual call syntax: .. code-block:: python def f(number, say, to): ... # function code f(1234, say="hello", to=some_instance) # keyword call in Python In C++, the same call can be made using: .. code-block:: cpp using namespace pybind11::literals; // to bring in the `_a` literal f(1234, "say"_a="hello", "to"_a=some_instance); // keyword call in C++ Unpacking arguments =================== Unpacking of ``*args`` and ``**kwargs`` is also possible and can be mixed with other arguments: .. code-block:: cpp // * unpacking py::tuple args = py::make_tuple(1234, "hello", some_instance); f(*args); // ** unpacking py::dict kwargs = py::dict("number"_a=1234, "say"_a="hello", "to"_a=some_instance); f(**kwargs); // mixed keywords, * and ** unpacking py::tuple args = py::make_tuple(1234); py::dict kwargs = py::dict("to"_a=some_instance); f(*args, "say"_a="hello", **kwargs); Generalized unpacking according to PEP448_ is also supported: .. code-block:: cpp py::dict kwargs1 = py::dict("number"_a=1234); py::dict kwargs2 = py::dict("to"_a=some_instance); f(**kwargs1, "say"_a="hello", **kwargs2); .. seealso:: The file :file:`tests/test_pytypes.cpp` contains a complete example that demonstrates passing native Python types in more detail. The file :file:`tests/test_callbacks.cpp` presents a few examples of calling Python functions from C++, including keywords arguments and unpacking. .. _PEP448: https://www.python.org/dev/peps/pep-0448/ .. _implicit_casting: Implicit casting ================ When using the C++ interface for Python types, or calling Python functions, objects of type :class:`object` are returned. It is possible to invoke implicit conversions to subclasses like :class:`dict`. The same holds for the proxy objects returned by ``operator[]`` or ``obj.attr()``. Casting to subtypes improves code readability and allows values to be passed to C++ functions that require a specific subtype rather than a generic :class:`object`. .. code-block:: cpp #include using namespace pybind11::literals; py::module_ os = py::module_::import("os"); py::module_ path = py::module_::import("os.path"); // like 'import os.path as path' py::module_ np = py::module_::import("numpy"); // like 'import numpy as np' py::str curdir_abs = path.attr("abspath")(path.attr("curdir")); py::print(py::str("Current directory: ") + curdir_abs); py::dict environ = os.attr("environ"); py::print(environ["HOME"]); py::array_t arr = np.attr("ones")(3, "dtype"_a="float32"); py::print(py::repr(arr + py::int_(1))); These implicit conversions are available for subclasses of :class:`object`; there is no need to call ``obj.cast()`` explicitly as for custom classes, see :ref:`casting_back_and_forth`. .. note:: If a trivial conversion via move constructor is not possible, both implicit and explicit casting (calling ``obj.cast()``) will attempt a "rich" conversion. For instance, ``py::list env = os.attr("environ");`` will succeed and is equivalent to the Python code ``env = list(os.environ)`` that produces a list of the dict keys. .. TODO: Adapt text once PR #2349 has landed Handling exceptions =================== Python exceptions from wrapper classes will be thrown as a ``py::error_already_set``. See :ref:`Handling exceptions from Python in C++ ` for more information on handling exceptions raised when calling C++ wrapper classes. .. _pytypes_gotchas: Gotchas ======= Default-Constructed Wrappers ---------------------------- When a wrapper type is default-constructed, it is **not** a valid Python object (i.e. it is not ``py::none()``). It is simply the same as ``PyObject*`` null pointer. To check for this, use ``static_cast(my_wrapper)``. Assigning py::none() to wrappers -------------------------------- You may be tempted to use types like ``py::str`` and ``py::dict`` in C++ signatures (either pure C++, or in bound signatures), and assign them default values of ``py::none()``. However, in a best case scenario, it will fail fast because ``None`` is not convertible to that type (e.g. ``py::dict``), or in a worse case scenario, it will silently work but corrupt the types you want to work with (e.g. ``py::str(py::none())`` will yield ``"None"`` in Python). pybind11-2.13.6/docs/advanced/pycpp/utilities.rst000066400000000000000000000131161467115402600216370ustar00rootroot00000000000000Utilities ######### Using Python's print function in C++ ==================================== The usual way to write output in C++ is using ``std::cout`` while in Python one would use ``print``. Since these methods use different buffers, mixing them can lead to output order issues. To resolve this, pybind11 modules can use the :func:`py::print` function which writes to Python's ``sys.stdout`` for consistency. Python's ``print`` function is replicated in the C++ API including optional keyword arguments ``sep``, ``end``, ``file``, ``flush``. Everything works as expected in Python: .. code-block:: cpp py::print(1, 2.0, "three"); // 1 2.0 three py::print(1, 2.0, "three", "sep"_a="-"); // 1-2.0-three auto args = py::make_tuple("unpacked", true); py::print("->", *args, "end"_a="<-"); // -> unpacked True <- .. _ostream_redirect: Capturing standard output from ostream ====================================== Often, a library will use the streams ``std::cout`` and ``std::cerr`` to print, but this does not play well with Python's standard ``sys.stdout`` and ``sys.stderr`` redirection. Replacing a library's printing with ``py::print `` may not be feasible. This can be fixed using a guard around the library function that redirects output to the corresponding Python streams: .. code-block:: cpp #include ... // Add a scoped redirect for your noisy code m.def("noisy_func", []() { py::scoped_ostream_redirect stream( std::cout, // std::ostream& py::module_::import("sys").attr("stdout") // Python output ); call_noisy_func(); }); .. warning:: The implementation in ``pybind11/iostream.h`` is NOT thread safe. Multiple threads writing to a redirected ostream concurrently cause data races and potentially buffer overflows. Therefore it is currently a requirement that all (possibly) concurrent redirected ostream writes are protected by a mutex. #HelpAppreciated: Work on iostream.h thread safety. For more background see the discussions under `PR #2982 `_ and `PR #2995 `_. This method respects flushes on the output streams and will flush if needed when the scoped guard is destroyed. This allows the output to be redirected in real time, such as to a Jupyter notebook. The two arguments, the C++ stream and the Python output, are optional, and default to standard output if not given. An extra type, ``py::scoped_estream_redirect ``, is identical except for defaulting to ``std::cerr`` and ``sys.stderr``; this can be useful with ``py::call_guard``, which allows multiple items, but uses the default constructor: .. code-block:: cpp // Alternative: Call single function using call guard m.def("noisy_func", &call_noisy_function, py::call_guard()); The redirection can also be done in Python with the addition of a context manager, using the ``py::add_ostream_redirect() `` function: .. code-block:: cpp py::add_ostream_redirect(m, "ostream_redirect"); The name in Python defaults to ``ostream_redirect`` if no name is passed. This creates the following context manager in Python: .. code-block:: python with ostream_redirect(stdout=True, stderr=True): noisy_function() It defaults to redirecting both streams, though you can use the keyword arguments to disable one of the streams if needed. .. note:: The above methods will not redirect C-level output to file descriptors, such as ``fprintf``. For those cases, you'll need to redirect the file descriptors either directly in C or with Python's ``os.dup2`` function in an operating-system dependent way. .. _eval: Evaluating Python expressions from strings and files ==================================================== pybind11 provides the ``eval``, ``exec`` and ``eval_file`` functions to evaluate Python expressions and statements. The following example illustrates how they can be used. .. code-block:: cpp // At beginning of file #include ... // Evaluate in scope of main module py::object scope = py::module_::import("__main__").attr("__dict__"); // Evaluate an isolated expression int result = py::eval("my_variable + 10", scope).cast(); // Evaluate a sequence of statements py::exec( "print('Hello')\n" "print('world!');", scope); // Evaluate the statements in an separate Python file on disk py::eval_file("script.py", scope); C++11 raw string literals are also supported and quite handy for this purpose. The only requirement is that the first statement must be on a new line following the raw string delimiter ``R"(``, ensuring all lines have common leading indent: .. code-block:: cpp py::exec(R"( x = get_answer() if x == 42: print('Hello World!') else: print('Bye!') )", scope ); .. note:: `eval` and `eval_file` accept a template parameter that describes how the string/file should be interpreted. Possible choices include ``eval_expr`` (isolated expression), ``eval_single_statement`` (a single statement, return value is always ``none``), and ``eval_statements`` (sequence of statements, return value is always ``none``). `eval` defaults to ``eval_expr``, `eval_file` defaults to ``eval_statements`` and `exec` is just a shortcut for ``eval``. pybind11-2.13.6/docs/advanced/smart_ptrs.rst000066400000000000000000000143461467115402600206750ustar00rootroot00000000000000Smart pointers ############## std::unique_ptr =============== Given a class ``Example`` with Python bindings, it's possible to return instances wrapped in C++11 unique pointers, like so .. code-block:: cpp std::unique_ptr create_example() { return std::unique_ptr(new Example()); } .. code-block:: cpp m.def("create_example", &create_example); In other words, there is nothing special that needs to be done. While returning unique pointers in this way is allowed, it is *illegal* to use them as function arguments. For instance, the following function signature cannot be processed by pybind11. .. code-block:: cpp void do_something_with_example(std::unique_ptr ex) { ... } The above signature would imply that Python needs to give up ownership of an object that is passed to this function, which is generally not possible (for instance, the object might be referenced elsewhere). std::shared_ptr =============== The binding generator for classes, :class:`class_`, can be passed a template type that denotes a special *holder* type that is used to manage references to the object. If no such holder type template argument is given, the default for a type named ``Type`` is ``std::unique_ptr``, which means that the object is deallocated when Python's reference count goes to zero. It is possible to switch to other types of reference counting wrappers or smart pointers, which is useful in codebases that rely on them. For instance, the following snippet causes ``std::shared_ptr`` to be used instead. .. code-block:: cpp py::class_ /* <- holder type */> obj(m, "Example"); Note that any particular class can only be associated with a single holder type. One potential stumbling block when using holder types is that they need to be applied consistently. Can you guess what's broken about the following binding code? .. code-block:: cpp class Child { }; class Parent { public: Parent() : child(std::make_shared()) { } Child *get_child() { return child.get(); } /* Hint: ** DON'T DO THIS ** */ private: std::shared_ptr child; }; PYBIND11_MODULE(example, m) { py::class_>(m, "Child"); py::class_>(m, "Parent") .def(py::init<>()) .def("get_child", &Parent::get_child); } The following Python code will cause undefined behavior (and likely a segmentation fault). .. code-block:: python from example import Parent print(Parent().get_child()) The problem is that ``Parent::get_child()`` returns a pointer to an instance of ``Child``, but the fact that this instance is already managed by ``std::shared_ptr<...>`` is lost when passing raw pointers. In this case, pybind11 will create a second independent ``std::shared_ptr<...>`` that also claims ownership of the pointer. In the end, the object will be freed **twice** since these shared pointers have no way of knowing about each other. There are two ways to resolve this issue: 1. For types that are managed by a smart pointer class, never use raw pointers in function arguments or return values. In other words: always consistently wrap pointers into their designated holder types (such as ``std::shared_ptr<...>``). In this case, the signature of ``get_child()`` should be modified as follows: .. code-block:: cpp std::shared_ptr get_child() { return child; } 2. Adjust the definition of ``Child`` by specifying ``std::enable_shared_from_this`` (see cppreference_ for details) as a base class. This adds a small bit of information to ``Child`` that allows pybind11 to realize that there is already an existing ``std::shared_ptr<...>`` and communicate with it. In this case, the declaration of ``Child`` should look as follows: .. _cppreference: http://en.cppreference.com/w/cpp/memory/enable_shared_from_this .. code-block:: cpp class Child : public std::enable_shared_from_this { }; .. _smart_pointers: Custom smart pointers ===================== pybind11 supports ``std::unique_ptr`` and ``std::shared_ptr`` right out of the box. For any other custom smart pointer, transparent conversions can be enabled using a macro invocation similar to the following. It must be declared at the top namespace level before any binding code: .. code-block:: cpp PYBIND11_DECLARE_HOLDER_TYPE(T, SmartPtr) The first argument of :func:`PYBIND11_DECLARE_HOLDER_TYPE` should be a placeholder name that is used as a template parameter of the second argument. Thus, feel free to use any identifier, but use it consistently on both sides; also, don't use the name of a type that already exists in your codebase. The macro also accepts a third optional boolean parameter that is set to false by default. Specify .. code-block:: cpp PYBIND11_DECLARE_HOLDER_TYPE(T, SmartPtr, true) if ``SmartPtr`` can always be initialized from a ``T*`` pointer without the risk of inconsistencies (such as multiple independent ``SmartPtr`` instances believing that they are the sole owner of the ``T*`` pointer). A common situation where ``true`` should be passed is when the ``T`` instances use *intrusive* reference counting. Please take a look at the :ref:`macro_notes` before using this feature. By default, pybind11 assumes that your custom smart pointer has a standard interface, i.e. provides a ``.get()`` member function to access the underlying raw pointer. If this is not the case, pybind11's ``holder_helper`` must be specialized: .. code-block:: cpp // Always needed for custom holder types PYBIND11_DECLARE_HOLDER_TYPE(T, SmartPtr) // Only needed if the type's `.get()` goes by another name namespace PYBIND11_NAMESPACE { namespace detail { template struct holder_helper> { // <-- specialization static const T *get(const SmartPtr &p) { return p.getPointer(); } }; }} The above specialization informs pybind11 that the custom ``SmartPtr`` class provides ``.get()`` functionality via ``.getPointer()``. .. seealso:: The file :file:`tests/test_smart_ptr.cpp` contains a complete example that demonstrates how to work with custom reference-counting holder types in more detail. pybind11-2.13.6/docs/basics.rst000066400000000000000000000224611467115402600161730ustar00rootroot00000000000000.. _basics: First steps ########### This sections demonstrates the basic features of pybind11. Before getting started, make sure that development environment is set up to compile the included set of test cases. Compiling the test cases ======================== Linux/macOS ----------- On Linux you'll need to install the **python-dev** or **python3-dev** packages as well as **cmake**. On macOS, the included python version works out of the box, but **cmake** must still be installed. After installing the prerequisites, run .. code-block:: bash mkdir build cd build cmake .. make check -j 4 The last line will both compile and run the tests. Windows ------- On Windows, only **Visual Studio 2017** and newer are supported. .. Note:: To use the C++17 in Visual Studio 2017 (MSVC 14.1), pybind11 requires the flag ``/permissive-`` to be passed to the compiler `to enforce standard conformance`_. When building with Visual Studio 2019, this is not strictly necessary, but still advised. .. _`to enforce standard conformance`: https://docs.microsoft.com/en-us/cpp/build/reference/permissive-standards-conformance?view=vs-2017 To compile and run the tests: .. code-block:: batch mkdir build cd build cmake .. cmake --build . --config Release --target check This will create a Visual Studio project, compile and run the target, all from the command line. .. Note:: If all tests fail, make sure that the Python binary and the testcases are compiled for the same processor type and bitness (i.e. either **i386** or **x86_64**). You can specify **x86_64** as the target architecture for the generated Visual Studio project using ``cmake -A x64 ..``. .. seealso:: Advanced users who are already familiar with Boost.Python may want to skip the tutorial and look at the test cases in the :file:`tests` directory, which exercise all features of pybind11. Header and namespace conventions ================================ For brevity, all code examples assume that the following two lines are present: .. code-block:: cpp #include namespace py = pybind11; .. note:: ``pybind11/pybind11.h`` includes ``Python.h``, as such it must be the first file included in any source file or header for `the same reasons as Python.h`_. .. _`the same reasons as Python.h`: https://docs.python.org/3/extending/extending.html#a-simple-example Some features may require additional headers, but those will be specified as needed. .. _simple_example: Creating bindings for a simple function ======================================= Let's start by creating Python bindings for an extremely simple function, which adds two numbers and returns their result: .. code-block:: cpp int add(int i, int j) { return i + j; } For simplicity [#f1]_, we'll put both this function and the binding code into a file named :file:`example.cpp` with the following contents: .. code-block:: cpp #include int add(int i, int j) { return i + j; } PYBIND11_MODULE(example, m) { m.doc() = "pybind11 example plugin"; // optional module docstring m.def("add", &add, "A function that adds two numbers"); } .. [#f1] In practice, implementation and binding code will generally be located in separate files. The :func:`PYBIND11_MODULE` macro creates a function that will be called when an ``import`` statement is issued from within Python. The module name (``example``) is given as the first macro argument (it should not be in quotes). The second argument (``m``) defines a variable of type :class:`py::module_ ` which is the main interface for creating bindings. The method :func:`module_::def` generates binding code that exposes the ``add()`` function to Python. .. note:: Notice how little code was needed to expose our function to Python: all details regarding the function's parameters and return value were automatically inferred using template metaprogramming. This overall approach and the used syntax are borrowed from Boost.Python, though the underlying implementation is very different. pybind11 is a header-only library, hence it is not necessary to link against any special libraries and there are no intermediate (magic) translation steps. On Linux, the above example can be compiled using the following command: .. code-block:: bash $ c++ -O3 -Wall -shared -std=c++11 -fPIC $(python3 -m pybind11 --includes) example.cpp -o example$(python3-config --extension-suffix) .. note:: If you used :ref:`include_as_a_submodule` to get the pybind11 source, then use ``$(python3-config --includes) -Iextern/pybind11/include`` instead of ``$(python3 -m pybind11 --includes)`` in the above compilation, as explained in :ref:`building_manually`. For more details on the required compiler flags on Linux and macOS, see :ref:`building_manually`. For complete cross-platform compilation instructions, refer to the :ref:`compiling` page. The `python_example`_ and `cmake_example`_ repositories are also a good place to start. They are both complete project examples with cross-platform build systems. The only difference between the two is that `python_example`_ uses Python's ``setuptools`` to build the module, while `cmake_example`_ uses CMake (which may be preferable for existing C++ projects). .. _python_example: https://github.com/pybind/python_example .. _cmake_example: https://github.com/pybind/cmake_example Building the above C++ code will produce a binary module file that can be imported to Python. Assuming that the compiled module is located in the current directory, the following interactive Python session shows how to load and execute the example: .. code-block:: pycon $ python Python 3.9.10 (main, Jan 15 2022, 11:48:04) [Clang 13.0.0 (clang-1300.0.29.3)] on darwin Type "help", "copyright", "credits" or "license" for more information. >>> import example >>> example.add(1, 2) 3 >>> .. _keyword_args: Keyword arguments ================= With a simple code modification, it is possible to inform Python about the names of the arguments ("i" and "j" in this case). .. code-block:: cpp m.def("add", &add, "A function which adds two numbers", py::arg("i"), py::arg("j")); :class:`arg` is one of several special tag classes which can be used to pass metadata into :func:`module_::def`. With this modified binding code, we can now call the function using keyword arguments, which is a more readable alternative particularly for functions taking many parameters: .. code-block:: pycon >>> import example >>> example.add(i=1, j=2) 3L The keyword names also appear in the function signatures within the documentation. .. code-block:: pycon >>> help(example) .... FUNCTIONS add(...) Signature : (i: int, j: int) -> int A function which adds two numbers A shorter notation for named arguments is also available: .. code-block:: cpp // regular notation m.def("add1", &add, py::arg("i"), py::arg("j")); // shorthand using namespace pybind11::literals; m.def("add2", &add, "i"_a, "j"_a); The :var:`_a` suffix forms a C++11 literal which is equivalent to :class:`arg`. Note that the literal operator must first be made visible with the directive ``using namespace pybind11::literals``. This does not bring in anything else from the ``pybind11`` namespace except for literals. .. _default_args: Default arguments ================= Suppose now that the function to be bound has default arguments, e.g.: .. code-block:: cpp int add(int i = 1, int j = 2) { return i + j; } Unfortunately, pybind11 cannot automatically extract these parameters, since they are not part of the function's type information. However, they are simple to specify using an extension of :class:`arg`: .. code-block:: cpp m.def("add", &add, "A function which adds two numbers", py::arg("i") = 1, py::arg("j") = 2); The default values also appear within the documentation. .. code-block:: pycon >>> help(example) .... FUNCTIONS add(...) Signature : (i: int = 1, j: int = 2) -> int A function which adds two numbers The shorthand notation is also available for default arguments: .. code-block:: cpp // regular notation m.def("add1", &add, py::arg("i") = 1, py::arg("j") = 2); // shorthand m.def("add2", &add, "i"_a=1, "j"_a=2); Exporting variables =================== To expose a value from C++, use the ``attr`` function to register it in a module as shown below. Built-in types and general objects (more on that later) are automatically converted when assigned as attributes, and can be explicitly converted using the function ``py::cast``. .. code-block:: cpp PYBIND11_MODULE(example, m) { m.attr("the_answer") = 42; py::object world = py::cast("World"); m.attr("what") = world; } These are then accessible from Python: .. code-block:: pycon >>> import example >>> example.the_answer 42 >>> example.what 'World' .. _supported_types: Supported data types ==================== A large number of data types are supported out of the box and can be used seamlessly as functions arguments, return values or with ``py::cast`` in general. For a full overview, see the :doc:`advanced/cast/index` section. pybind11-2.13.6/docs/benchmark.py000066400000000000000000000055111467115402600164760ustar00rootroot00000000000000from __future__ import annotations import datetime as dt import os import random nfns = 4 # Functions per class nargs = 4 # Arguments per function def generate_dummy_code_pybind11(nclasses=10): decl = "" bindings = "" for cl in range(nclasses): decl += f"class cl{cl:03};\n" decl += "\n" for cl in range(nclasses): decl += f"class {cl:03} {{\n" decl += "public:\n" bindings += f' py::class_(m, "cl{cl:03}")\n' for fn in range(nfns): ret = random.randint(0, nclasses - 1) params = [random.randint(0, nclasses - 1) for i in range(nargs)] decl += f" cl{ret:03} *fn_{fn:03}(" decl += ", ".join(f"cl{p:03} *" for p in params) decl += ");\n" bindings += f' .def("fn_{fn:03}", &cl{cl:03}::fn_{fn:03})\n' decl += "};\n\n" bindings += " ;\n" result = "#include \n\n" result += "namespace py = pybind11;\n\n" result += decl + "\n" result += "PYBIND11_MODULE(example, m) {\n" result += bindings result += "}" return result def generate_dummy_code_boost(nclasses=10): decl = "" bindings = "" for cl in range(nclasses): decl += f"class cl{cl:03};\n" decl += "\n" for cl in range(nclasses): decl += "class cl%03i {\n" % cl decl += "public:\n" bindings += f' py::class_("cl{cl:03}")\n' for fn in range(nfns): ret = random.randint(0, nclasses - 1) params = [random.randint(0, nclasses - 1) for i in range(nargs)] decl += f" cl{ret:03} *fn_{fn:03}(" decl += ", ".join(f"cl{p:03} *" for p in params) decl += ");\n" bindings += f' .def("fn_{fn:03}", &cl{cl:03}::fn_{fn:03}, py::return_value_policy())\n' decl += "};\n\n" bindings += " ;\n" result = "#include \n\n" result += "namespace py = boost::python;\n\n" result += decl + "\n" result += "BOOST_PYTHON_MODULE(example) {\n" result += bindings result += "}" return result for codegen in [generate_dummy_code_pybind11, generate_dummy_code_boost]: print("{") for i in range(10): nclasses = 2**i with open("test.cpp", "w") as f: f.write(codegen(nclasses)) n1 = dt.datetime.now() os.system( "g++ -Os -shared -rdynamic -undefined dynamic_lookup " "-fvisibility=hidden -std=c++14 test.cpp -I include " "-I /System/Library/Frameworks/Python.framework/Headers -o test.so" ) n2 = dt.datetime.now() elapsed = (n2 - n1).total_seconds() size = os.stat("test.so").st_size print(" {%i, %f, %i}," % (nclasses * nfns, elapsed, size)) print("}") pybind11-2.13.6/docs/benchmark.rst000066400000000000000000000061401467115402600166550ustar00rootroot00000000000000Benchmark ========= The following is the result of a synthetic benchmark comparing both compilation time and module size of pybind11 against Boost.Python. A detailed report about a Boost.Python to pybind11 conversion of a real project is available here: [#f1]_. .. [#f1] http://graylab.jhu.edu/RosettaCon2016/PyRosetta-4.pdf Setup ----- A python script (see the ``docs/benchmark.py`` file) was used to generate a set of files with dummy classes whose count increases for each successive benchmark (between 1 and 2048 classes in powers of two). Each class has four methods with a randomly generated signature with a return value and four arguments. (There was no particular reason for this setup other than the desire to generate many unique function signatures whose count could be controlled in a simple way.) Here is an example of the binding code for one class: .. code-block:: cpp ... class cl034 { public: cl279 *fn_000(cl084 *, cl057 *, cl065 *, cl042 *); cl025 *fn_001(cl098 *, cl262 *, cl414 *, cl121 *); cl085 *fn_002(cl445 *, cl297 *, cl145 *, cl421 *); cl470 *fn_003(cl200 *, cl323 *, cl332 *, cl492 *); }; ... PYBIND11_MODULE(example, m) { ... py::class_(m, "cl034") .def("fn_000", &cl034::fn_000) .def("fn_001", &cl034::fn_001) .def("fn_002", &cl034::fn_002) .def("fn_003", &cl034::fn_003) ... } The Boost.Python version looks almost identical except that a return value policy had to be specified as an argument to ``def()``. For both libraries, compilation was done with .. code-block:: bash Apple LLVM version 7.0.2 (clang-700.1.81) and the following compilation flags .. code-block:: bash g++ -Os -shared -rdynamic -undefined dynamic_lookup -fvisibility=hidden -std=c++14 Compilation time ---------------- The following log-log plot shows how the compilation time grows for an increasing number of class and function declarations. pybind11 includes many fewer headers, which initially leads to shorter compilation times, but the performance is ultimately fairly similar (pybind11 is 19.8 seconds faster for the largest largest file with 2048 classes and a total of 8192 methods -- a modest **1.2x** speedup relative to Boost.Python, which required 116.35 seconds). .. only:: not latex .. image:: pybind11_vs_boost_python1.svg .. only:: latex .. image:: pybind11_vs_boost_python1.png Module size ----------- Differences between the two libraries become much more pronounced when considering the file size of the generated Python plugin: for the largest file, the binary generated by Boost.Python required 16.8 MiB, which was **2.17 times** / **9.1 megabytes** larger than the output generated by pybind11. For very small inputs, Boost.Python has an edge in the plot below -- however, note that it stores many definitions in an external library, whose size was not included here, hence the comparison is slightly shifted in Boost.Python's favor. .. only:: not latex .. image:: pybind11_vs_boost_python2.svg .. only:: latex .. image:: pybind11_vs_boost_python2.png pybind11-2.13.6/docs/changelog.rst000066400000000000000000004112761467115402600166640ustar00rootroot00000000000000.. _changelog: Changelog ######### Starting with version 1.8.0, pybind11 releases use a `semantic versioning `_ policy. Changes will be added here periodically from the "Suggested changelog entry" block in pull request descriptions. IN DEVELOPMENT -------------- Changes will be summarized here periodically. New Features: * Support for Python 3.7 was removed. (Official end-of-life: 2023-06-27). `#5191 `_ * stl.h ``list|set|map_caster`` were made more user friendly: it is no longer necessary to explicitly convert Python iterables to ``tuple()``, ``set()``, or ``map()`` in many common situations. `#4686 `_ * Support for CMake older than 3.15 removed. CMake 3.15-3.30 supported. `#5304 `_ * The ``array_caster`` in pybind11/stl.h was enhanced to support value types that are not default-constructible. `#5305 `_ * Added ``py::warnings`` namespace with ``py::warnings::warn`` and ``py::warnings::new_warning_type`` that provides the interface for Python warnings. `#5291 `_ Version 2.13.6 (September 13, 2024) ----------------------------------- New Features: * A new ``self._pybind11_conduit_v1_()`` method is automatically added to all ``py::class_``-wrapped types, to enable type-safe interoperability between different independent Python/C++ bindings systems, including pybind11 versions with different ``PYBIND11_INTERNALS_VERSION``'s. Supported on pybind11 2.11.2, 2.12.1, and 2.13.6+. `#5296 `_ Bug fixes: * Using ``__cpp_nontype_template_args`` instead of ``__cpp_nontype_template_parameter_class``. `#5330 `_ * Properly translate C++ exception to Python exception when creating Python buffer from wrapped object. `#5324 `_ Documentation: * Adds an answer (FAQ) for "What is a highly conclusive and simple way to find memory leaks?". `#5340 `_ Version 2.13.5 (August 22, 2024) -------------------------------- Bug fixes: * Fix includes when using Windows long paths (``\\?\`` prefix). `#5321 `_ * Support ``-Wpedantic`` in C++20 mode. `#5322 `_ * Fix and test ```` support for ``py::tuple`` and ``py::list``. `#5314 `_ Version 2.13.4 (August 14, 2024) -------------------------------- Bug fixes: * Fix paths with spaces, including on Windows. (Replaces regression from `#5302 `_) `#4874 `_ Documentation: * Remove repetitive words. `#5308 `_ Version 2.13.3 (August 13, 2024) -------------------------------- Bug fixes: * Quote paths from pybind11-config `#5302 `_ * Fix typo in Emscripten support when in config mode (CMake) `#5301 `_ Version 2.13.2 (August 13, 2024) -------------------------------- New Features: * A ``pybind11::detail::type_caster_std_function_specializations`` feature was added, to support specializations for ``std::function``'s with return types that require custom to-Python conversion behavior (to primary use case is to catch and convert exceptions). `#4597 `_ Changes: * Use ``PyMutex`` instead of ``std::mutex`` for internal locking in the free-threaded build. `#5219 `_ * Add a special type annotation for C++ empty tuple. `#5214 `_ * When compiling for WebAssembly, add the required exception flags (CMake 3.13+). `#5298 `_ Bug fixes: * Make ``gil_safe_call_once_and_store`` thread-safe in free-threaded CPython. `#5246 `_ * A missing ``#include `` in pybind11/typing.h was added to fix build errors (in case user code does not already depend on that include). `#5208 `_ * Fix regression introduced in #5201 for GCC<10.3 in C++20 mode. `#5205 `_ .. fix(cmake) * Remove extra = when assigning flto value in the case for Clang in CMake. `#5207 `_ Tests: * Adding WASM testing to our CI (Pyodide / Emscripten via scikit-build-core). `#4745 `_ * clang-tidy (in GitHub Actions) was updated from clang 15 to clang 18. `#5272 `_ Version 2.13.1 (June 26, 2024) ------------------------------ New Features: * Add support for ``Typing.Callable[..., T]``. `#5202 `_ Bug fixes: * Avoid aligned allocation in free-threaded build in order to support macOS versions before 10.14. `#5200 `_ Version 2.13.0 (June 25, 2024) ------------------------------ New Features: * Support free-threaded CPython (3.13t). Add ``py::mod_gil_not_used()`` tag to indicate if a module supports running with the GIL disabled. `#5148 `_ * Support for Python 3.6 was removed. (Official end-of-life: 2021-12-23). `#5177 `_ * ``py::list`` gained a ``.clear()`` method. `#5153 `_ .. feat(types) * Support for ``Union``, ``Optional``, ``type[T]``, ``typing.TypeGuard``, ``typing.TypeIs``, ``typing.Never``, ``typing.NoReturn`` and ``typing.Literal`` was added to ``pybind11/typing.h``. `#5166 `_ `#5165 `_ `#5194 `_ `#5193 `_ `#5192 `_ .. feat(cmake) * In CMake, if ``PYBIND11_USE_CROSSCOMPILING`` is enabled, then ``CMAKE_CROSSCOMPILING`` will be respected and will keep pybind11 from accessing the interpreter during configuration. Several CMake variables will be required in this case, but can be deduced from the environment variable ``SETUPTOOLS_EXT_SUFFIX``. The default (currently ``OFF``) may be changed in the future. `#5083 `_ Bug fixes: * A refcount bug (leading to heap-use-after-free) involving trampoline functions with ``PyObject *`` return type was fixed. `#5156 `_ * Return ``py::ssize_t`` from ``.ref_count()`` instead of ``int``. `#5139 `_ * A subtle bug involving C++ types with unusual ``operator&`` overrides was fixed. `#5189 `_ * Support Python 3.13 with minor fix, add to CI. `#5127 `_ .. fix(cmake) * Fix mistake affecting old cmake and old boost. `#5149 `_ Documentation: * Build docs updated to feature scikit-build-core and meson-python, and updated setuptools instructions. `#5168 `_ Tests: * Avoid immortal objects in tests. `#5150 `_ CI: * Compile against Python 3.13t in CI. * Use ``macos-13`` (Intel) for CI jobs for now (will drop Python 3.7 soon). `#5109 `_ * Releases now have artifact attestations, visible at https://github.com/pybind/pybind11/attestations. `#5196 `_ Other: * Some cleanup in preparation for 3.13 support. `#5137 `_ * Avoid a warning by ensuring an iterator end check is included in release mode. `#5129 `_ * Bump max cmake to 3.29. `#5075 `_ * Update docs and noxfile. `#5071 `_ Version 2.12.1 (September 13, 2024) ----------------------------------- New Features: * A new ``self._pybind11_conduit_v1_()`` method is automatically added to all ``py::class_``-wrapped types, to enable type-safe interoperability between different independent Python/C++ bindings systems, including pybind11 versions with different ``PYBIND11_INTERNALS_VERSION``'s. Supported on pybind11 2.11.2, 2.12.1, and 2.13.6+. `#5296 `_ Version 2.12.0 (March 27, 2024) ------------------------------- New Features: * ``pybind11`` now supports compiling for `NumPy 2 `_. Most code shouldn't change (see :ref:`upgrade-guide-2.12` for details). However, if you experience issues you can define ``PYBIND11_NUMPY_1_ONLY`` to disable the new support for now, but this will be removed in the future. `#5050 `_ * ``pybind11/gil_safe_call_once.h`` was added (it needs to be included explicitly). The primary use case is GIL-safe initialization of C++ ``static`` variables. `#4877 `_ * Support move-only iterators in ``py::make_iterator``, ``py::make_key_iterator``, ``py::make_value_iterator``. `#4834 `_ * Two simple ``py::set_error()`` functions were added and the documentation was updated accordingly. In particular, ``py::exception<>::operator()`` was deprecated (use one of the new functions instead). The documentation for ``py::exception<>`` was further updated to not suggest code that may result in undefined behavior. `#4772 `_ Bug fixes: * Removes potential for Undefined Behavior during process teardown. `#4897 `_ * Improve compatibility with the nvcc compiler (especially CUDA 12.1/12.2). `#4893 `_ * ``pybind11/numpy.h`` now imports NumPy's ``multiarray`` and ``_internal`` submodules with paths depending on the installed version of NumPy (for compatibility with NumPy 2). `#4857 `_ * Builtins collections names in docstrings are now consistently rendered in lowercase (list, set, dict, tuple), in accordance with PEP 585. `#4833 `_ * Added ``py::typing::Iterator``, ``py::typing::Iterable``. `#4832 `_ * Render ``py::function`` as ``Callable`` in docstring. `#4829 `_ * Also bump ``PYBIND11_INTERNALS_VERSION`` for MSVC, which unlocks two new features without creating additional incompatibilities. `#4819 `_ * Guard against crashes/corruptions caused by modules built with different MSVC versions. `#4779 `_ * A long-standing bug in the handling of Python multiple inheritance was fixed. See PR #4762 for the rather complex details. `#4762 `_ * Fix ``bind_map`` with ``using`` declarations. `#4952 `_ * Qualify ``py::detail::concat`` usage to avoid ADL selecting one from somewhere else, such as modernjson's concat. `#4955 `_ * Use new PyCode API on Python 3.12+. `#4916 `_ * Minor cleanup from warnings reported by Clazy. `#4988 `_ * Remove typing and duplicate ``class_`` for ``KeysView``/``ValuesView``/``ItemsView``. `#4985 `_ * Use ``PyObject_VisitManagedDict()`` and ``PyObject_ClearManagedDict()`` on Python 3.13 and newer. `#4973 `_ * Update ``make_static_property_type()`` to make it compatible with Python 3.13. `#4971 `_ .. fix(types) * Render typed iterators for ``make_iterator``, ``make_key_iterator``, ``make_value_iterator``. `#4876 `_ * Add several missing type name specializations. `#5073 `_ * Change docstring render for ``py::buffer``, ``py::sequence`` and ``py::handle`` (to ``Buffer``, ``Sequence``, ``Any``). `#4831 `_ * Fixed ``base_enum.__str__`` docstring. `#4827 `_ * Enforce single line docstring signatures. `#4735 `_ * Special 'typed' wrappers now available in ``typing.h`` to annotate tuple, dict, list, set, and function. `#4259 `_ * Create ``handle_type_name`` specialization to type-hint variable length tuples. `#5051 `_ .. fix(build) * Setting ``PYBIND11_FINDPYTHON`` to OFF will force the old FindPythonLibs mechanism to be used. `#5042 `_ * Skip empty ``PYBIND11_PYTHON_EXECUTABLE_LAST`` for the first cmake run. `#4856 `_ * Fix FindPython mode exports & avoid ``pkg_resources`` if ``importlib.metadata`` available. `#4941 `_ * ``Python_ADDITIONAL_VERSIONS`` (classic search) now includes 3.12. `#4909 `_ * ``pybind11.pc`` is now relocatable by default as long as install destinations are not absolute paths. `#4830 `_ * Correctly detect CMake FindPython removal when used as a subdirectory. `#4806 `_ * Don't require the libs component on CMake 3.18+ when using PYBIND11_FINDPYTHON (fixes manylinux builds). `#4805 `_ * ``pybind11_strip`` is no longer automatically applied when ``CMAKE_BUILD_TYPE`` is unset. `#4780 `_ * Support ``DEBUG_POSFIX`` correctly for debug builds. `#4761 `_ * Hardcode lto/thin lto for Emscripten cross-compiles. `#4642 `_ * Upgrade maximum supported CMake version to 3.27 to fix CMP0148 warnings. `#4786 `_ Documentation: * Small fix to grammar in ``functions.rst``. `#4791 `_ * Remove upper bound in example pyproject.toml for setuptools. `#4774 `_ CI: * CI: Update NVHPC to 23.5 and Ubuntu 20.04. `#4764 `_ * Test on PyPy 3.10. `#4714 `_ Other: * Use Ruff formatter instead of Black. `#4912 `_ * An ``assert()`` was added to help Coverty avoid generating a false positive. `#4817 `_ Version 2.11.2 (September 13, 2024) ----------------------------------- New Features: * A new ``self._pybind11_conduit_v1_()`` method is automatically added to all ``py::class_``-wrapped types, to enable type-safe interoperability between different independent Python/C++ bindings systems, including pybind11 versions with different ``PYBIND11_INTERNALS_VERSION``'s. Supported on pybind11 2.11.2, 2.12.1, and 2.13.6+. `#5296 `_ Version 2.11.1 (July 17, 2023) ------------------------------ Changes: * ``PYBIND11_NO_ASSERT_GIL_HELD_INCREF_DECREF`` is now provided as an option for disabling the default-on ``PyGILState_Check()``'s in ``pybind11::handle``'s ``inc_ref()`` & ``dec_ref()``. `#4753 `_ * ``PYBIND11_ASSERT_GIL_HELD_INCREF_DECREF`` was disabled for PyPy in general (not just PyPy Windows). `#4751 `_ Version 2.11.0 (July 14, 2023) ------------------------------ New features: * The newly added ``pybind11::detail::is_move_constructible`` trait can be specialized for cases in which ``std::is_move_constructible`` does not work as needed. This is very similar to the long-established ``pybind11::detail::is_copy_constructible``. `#4631 `_ * Introduce ``recursive_container_traits``. `#4623 `_ * ``pybind11/type_caster_pyobject_ptr.h`` was added to support automatic wrapping of APIs that make use of ``PyObject *``. This header needs to included explicitly (i.e. it is not included implicitly with ``pybind/pybind11.h``). `#4601 `_ * ``format_descriptor<>`` & ``npy_format_descriptor<>`` ``PyObject *`` specializations were added. The latter enables ``py::array_t`` to/from-python conversions. `#4674 `_ * ``buffer_info`` gained an ``item_type_is_equivalent_to()`` member function. `#4674 `_ * The ``capsule`` API gained a user-friendly constructor (``py::capsule(ptr, "name", dtor)``). `#4720 `_ Changes: * ``PyGILState_Check()``'s in ``pybind11::handle``'s ``inc_ref()`` & ``dec_ref()`` are now enabled by default again. `#4246 `_ * ``py::initialize_interpreter()`` using ``PyConfig_InitPythonConfig()`` instead of ``PyConfig_InitIsolatedConfig()``, to obtain complete ``sys.path``. `#4473 `_ * Cast errors now always include Python type information, even if ``PYBIND11_DETAILED_ERROR_MESSAGES`` is not defined. This increases binary sizes slightly (~1.5%) but the error messages are much more informative. `#4463 `_ * The docstring generation for the ``std::array``-list caster was fixed. Previously, signatures included the size of the list in a non-standard, non-spec compliant way. The new format conforms to PEP 593. **Tooling for processing the docstrings may need to be updated accordingly.** `#4679 `_ * Setter return values (which are inaccessible for all practical purposes) are no longer converted to Python (only to be discarded). `#4621 `_ * Allow lambda specified to function definition to be ``noexcept(true)`` in C++17. `#4593 `_ * Get rid of recursive template instantiations for concatenating type signatures on C++17 and higher. `#4587 `_ * Compatibility with Python 3.12 (beta). Note that the minimum pybind11 ABI version for Python 3.12 is version 5. (The default ABI version for Python versions up to and including 3.11 is still version 4.). `#4570 `_ * With ``PYBIND11_INTERNALS_VERSION 5`` (default for Python 3.12+), MSVC builds use ``std::hash`` and ``std::equal_to`` instead of string-based type comparisons. This resolves issues when binding types defined in the unnamed namespace. `#4319 `_ * Python exception ``__notes__`` (introduced with Python 3.11) are now added to the ``error_already_set::what()`` output. `#4678 `_ Build system improvements: * CMake 3.27 support was added, CMake 3.4 support was dropped. FindPython will be used if ``FindPythonInterp`` is not present. `#4719 `_ * Update clang-tidy to 15 in CI. `#4387 `_ * Moved the linting framework over to Ruff. `#4483 `_ * Skip ``lto`` checks and target generation when ``CMAKE_INTERPROCEDURAL_OPTIMIZATION`` is defined. `#4643 `_ * No longer inject ``-stdlib=libc++``, not needed for modern Pythons (macOS 10.9+). `#4639 `_ * PyPy 3.10 support was added, PyPy 3.7 support was dropped. `#4728 `_ * Testing with Python 3.12 beta releases was added. `#4713 `_ Version 2.10.4 (Mar 16, 2023) ----------------------------- Changes: * ``python3 -m pybind11`` gained a ``--version`` option (prints the version and exits). `#4526 `_ Bug Fixes: * Fix a warning when pydebug is enabled on Python 3.11. `#4461 `_ * Ensure ``gil_scoped_release`` RAII is non-copyable. `#4490 `_ * Ensure the tests dir does not show up with new versions of setuptools. `#4510 `_ * Better stacklevel for a warning in setuptools helpers. `#4516 `_ Version 2.10.3 (Jan 3, 2023) ---------------------------- Changes: * Temporarily made our GIL status assertions (added in 2.10.2) disabled by default (re-enable manually by defining ``PYBIND11_ASSERT_GIL_HELD_INCREF_DECREF``, will be enabled in 2.11). `#4432 `_ * Improved error messages when ``inc_ref``/``dec_ref`` are called with an invalid GIL state. `#4427 `_ `#4436 `_ Bug Fixes: * Some minor touchups found by static analyzers. `#4440 `_ Version 2.10.2 (Dec 20, 2022) ----------------------------- Changes: * ``scoped_interpreter`` constructor taking ``PyConfig``. `#4330 `_ * ``pybind11/eigen/tensor.h`` adds converters to and from ``Eigen::Tensor`` and ``Eigen::TensorMap``. `#4201 `_ * ``PyGILState_Check()``'s were integrated to ``pybind11::handle`` ``inc_ref()`` & ``dec_ref()``. The added GIL checks are guarded by ``PYBIND11_ASSERT_GIL_HELD_INCREF_DECREF``, which is the default only if ``NDEBUG`` is not defined. (Made non-default in 2.10.3, will be active in 2.11) `#4246 `_ * Add option for enable/disable enum members in docstring. `#2768 `_ * Fixed typing of ``KeysView``, ``ValuesView`` and ``ItemsView`` in ``bind_map``. `#4353 `_ Bug fixes: * Bug fix affecting only Python 3.6 under very specific, uncommon conditions: move ``PyEval_InitThreads()`` call to the correct location. `#4350 `_ * Fix segfault bug when passing foreign native functions to functional.h. `#4254 `_ Build system improvements: * Support setting PYTHON_LIBRARIES manually for Windows ARM cross-compilation (classic mode). `#4406 `_ * Extend IPO/LTO detection for ICX (a.k.a IntelLLVM) compiler. `#4402 `_ * Allow calling ``find_package(pybind11 CONFIG)`` multiple times from separate directories in the same CMake project and properly link Python (new mode). `#4401 `_ * ``multiprocessing_set_spawn`` in pytest fixture for added safety. `#4377 `_ * Fixed a bug in two pybind11/tools cmake scripts causing "Unknown arguments specified" errors. `#4327 `_ Version 2.10.1 (Oct 31, 2022) ----------------------------- This is the first version to fully support embedding the newly released Python 3.11. Changes: * Allow ``pybind11::capsule`` constructor to take null destructor pointers. `#4221 `_ * ``embed.h`` was changed so that ``PYTHONPATH`` is used also with Python 3.11 (established behavior). `#4119 `_ * A ``PYBIND11_SIMPLE_GIL_MANAGEMENT`` option was added (cmake, C++ define), along with many additional tests in ``test_gil_scoped.py``. The option may be useful to try when debugging GIL-related issues, to determine if the more complex default implementation is or is not to blame. See #4216 for background. WARNING: Please be careful to not create ODR violations when using the option: everything that is linked together with mutual symbol visibility needs to be rebuilt. `#4216 `_ * ``PYBIND11_EXPORT_EXCEPTION`` was made non-empty only under macOS. This makes Linux builds safer, and enables the removal of warning suppression pragmas for Windows. `#4298 `_ Bug fixes: * Fixed a bug where ``UnicodeDecodeError`` was not propagated from various ``py::str`` ctors when decoding surrogate utf characters. `#4294 `_ * Revert perfect forwarding for ``make_iterator``. This broke at least one valid use case. May revisit later. `#4234 `_ * Fix support for safe casts to ``void*`` (regression in 2.10.0). `#4275 `_ * Fix ``char8_t`` support (regression in 2.9). `#4278 `_ * Unicode surrogate character in Python exception message leads to process termination in ``error_already_set::what()``. `#4297 `_ * Fix MSVC 2019 v.1924 & C++14 mode error for ``overload_cast``. `#4188 `_ * Make augmented assignment operators non-const for the object-api. Behavior was previously broken for augmented assignment operators. `#4065 `_ * Add proper error checking to C++ bindings for Python list append and insert. `#4208 `_ * Work-around for Nvidia's CUDA nvcc compiler in versions 11.4.0 - 11.8.0. `#4220 `_ * A workaround for PyPy was added in the ``py::error_already_set`` implementation, related to PR `#1895 `_ released with v2.10.0. `#4079 `_ * Fixed compiler errors when C++23 ``std::forward_like`` is available. `#4136 `_ * Properly raise exceptions in contains methods (like when an object in unhashable). `#4209 `_ * Further improve another error in exception handling. `#4232 `_ * ``get_local_internals()`` was made compatible with ``finalize_interpreter()``, fixing potential freezes during interpreter finalization. `#4192 `_ Performance and style: * Reserve space in set and STL map casters if possible. This will prevent unnecessary rehashing / resizing by knowing the number of keys ahead of time for Python to C++ casting. This improvement will greatly speed up the casting of large unordered maps and sets. `#4194 `_ * GIL RAII scopes are non-copyable to avoid potential bugs. `#4183 `_ * Explicitly default all relevant ctors for pytypes in the ``PYBIND11_OBJECT`` macros and enforce the clang-tidy checks ``modernize-use-equals-default`` in macros as well. `#4017 `_ * Optimize iterator advancement in C++ bindings. `#4237 `_ * Use the modern ``PyObject_GenericGetDict`` and ``PyObject_GenericSetDict`` for handling dynamic attribute dictionaries. `#4106 `_ * Document that users should use ``PYBIND11_NAMESPACE`` instead of using ``pybind11`` when opening namespaces. Using namespace declarations and namespace qualification remain the same as ``pybind11``. This is done to ensure consistent symbol visibility. `#4098 `_ * Mark ``detail::forward_like`` as constexpr. `#4147 `_ * Optimize unpacking_collector when processing ``arg_v`` arguments. `#4219 `_ * Optimize casting C++ object to ``None``. `#4269 `_ Build system improvements: * CMake: revert overwrite behavior, now opt-in with ``PYBIND11_PYTHONLIBS_OVERRWRITE OFF``. `#4195 `_ * Include a pkg-config file when installing pybind11, such as in the Python package. `#4077 `_ * Avoid stripping debug symbols when ``CMAKE_BUILD_TYPE`` is set to ``DEBUG`` instead of ``Debug``. `#4078 `_ * Followup to `#3948 `_, fixing vcpkg again. `#4123 `_ Version 2.10.0 (Jul 15, 2022) ----------------------------- Removed support for Python 2.7, Python 3.5, and MSVC 2015. Support for MSVC 2017 is limited due to availability of CI runners; we highly recommend MSVC 2019 or 2022 be used. Initial support added for Python 3.11. New features: * ``py::anyset`` & ``py::frozenset`` were added, with copying (cast) to ``std::set`` (similar to ``set``). `#3901 `_ * Support bytearray casting to string. `#3707 `_ * ``type_caster`` was added. ``std::monostate`` is a tag type that allows ``std::variant`` to act as an optional, or allows default construction of a ``std::variant`` holding a non-default constructible type. `#3818 `_ * ``pybind11::capsule::set_name`` added to mutate the name of the capsule instance. `#3866 `_ * NumPy: dtype constructor from type number added, accessors corresponding to Python API ``dtype.num``, ``dtype.byteorder``, ``dtype.flags`` and ``dtype.alignment`` added. `#3868 `_ Changes: * Python 3.6 is now the minimum supported version. `#3688 `_ `#3719 `_ * The minimum version for MSVC is now 2017. `#3722 `_ * Fix issues with CPython 3.11 betas and add to supported test matrix. `#3923 `_ * ``error_already_set`` is now safer and more performant, especially for exceptions with long tracebacks, by delaying computation. `#1895 `_ * Improve exception handling in python ``str`` bindings. `#3826 `_ * The bindings for capsules now have more consistent exception handling. `#3825 `_ * ``PYBIND11_OBJECT_CVT`` and ``PYBIND11_OBJECT_CVT_DEFAULT`` macro can now be used to define classes in namespaces other than pybind11. `#3797 `_ * Error printing code now uses ``PYBIND11_DETAILED_ERROR_MESSAGES`` instead of requiring ``NDEBUG``, allowing use with release builds if desired. `#3913 `_ * Implicit conversion of the literal ``0`` to ``pybind11::handle`` is now disabled. `#4008 `_ Bug fixes: * Fix exception handling when ``pybind11::weakref()`` fails. `#3739 `_ * ``module_::def_submodule`` was missing proper error handling. This is fixed now. `#3973 `_ * The behavior or ``error_already_set`` was made safer and the highly opaque "Unknown internal error occurred" message was replaced with a more helpful message. `#3982 `_ * ``error_already_set::what()`` now handles non-normalized exceptions correctly. `#3971 `_ * Support older C++ compilers where filesystem is not yet part of the standard library and is instead included in ``std::experimental::filesystem``. `#3840 `_ * Fix ``-Wfree-nonheap-object`` warnings produced by GCC by avoiding returning pointers to static objects with ``return_value_policy::take_ownership``. `#3946 `_ * Fix cast from pytype rvalue to another pytype. `#3949 `_ * Ensure proper behavior when garbage collecting classes with dynamic attributes in Python >=3.9. `#4051 `_ * A couple long-standing ``PYBIND11_NAMESPACE`` ``__attribute__((visibility("hidden")))`` inconsistencies are now fixed (affects only unusual environments). `#4043 `_ * ``pybind11::detail::get_internals()`` is now resilient to in-flight Python exceptions. `#3981 `_ * Arrays with a dimension of size 0 are now properly converted to dynamic Eigen matrices (more common in NumPy 1.23). `#4038 `_ * Avoid catching unrelated errors when importing NumPy. `#3974 `_ Performance and style: * Added an accessor overload of ``(object &&key)`` to reference steal the object when using python types as keys. This prevents unnecessary reference count overhead for attr, dictionary, tuple, and sequence look ups. Added additional regression tests. Fixed a performance bug the caused accessor assignments to potentially perform unnecessary copies. `#3970 `_ * Perfect forward all args of ``make_iterator``. `#3980 `_ * Avoid potential bug in pycapsule destructor by adding an ``error_guard`` to one of the dtors. `#3958 `_ * Optimize dictionary access in ``strip_padding`` for numpy. `#3994 `_ * ``stl_bind.h`` bindings now take slice args as a const-ref. `#3852 `_ * Made slice constructor more consistent, and improve performance of some casters by allowing reference stealing. `#3845 `_ * Change numpy dtype from_args method to use const ref. `#3878 `_ * Follow rule of three to ensure ``PyErr_Restore`` is called only once. `#3872 `_ * Added missing perfect forwarding for ``make_iterator`` functions. `#3860 `_ * Optimize c++ to python function casting by using the rvalue caster. `#3966 `_ * Optimize Eigen sparse matrix casting by removing unnecessary temporary. `#4064 `_ * Avoid potential implicit copy/assignment constructors causing double free in ``strdup_gaurd``. `#3905 `_ * Enable clang-tidy checks ``misc-definitions-in-headers``, ``modernize-loop-convert``, and ``modernize-use-nullptr``. `#3881 `_ `#3988 `_ Build system improvements: * CMake: Fix file extension on Windows with cp36 and cp37 using FindPython. `#3919 `_ * CMake: Support multiple Python targets (such as on vcpkg). `#3948 `_ * CMake: Fix issue with NVCC on Windows. `#3947 `_ * CMake: Drop the bitness check on cross compiles (like targeting WebAssembly via Emscripten). `#3959 `_ * Add MSVC builds in debug mode to CI. `#3784 `_ * MSVC 2022 C++20 coverage was added to GitHub Actions, including Eigen. `#3732 `_, `#3741 `_ Backend and tidying up: * New theme for the documentation. `#3109 `_ * Remove idioms in code comments. Use more inclusive language. `#3809 `_ * ``#include `` was removed from the ``pybind11/stl.h`` header. Your project may break if it has a transitive dependency on this include. The fix is to "Include What You Use". `#3928 `_ * Avoid ``setup.py `` usage in internal tests. `#3734 `_ Version 2.9.2 (Mar 29, 2022) ---------------------------- Changes: * Enum now has an ``__index__`` method on Python <3.8 too. `#3700 `_ * Local internals are now cleared after finalizing the interpreter. `#3744 `_ Bug fixes: * Better support for Python 3.11 alphas. `#3694 `_ * ``PYBIND11_TYPE_CASTER`` now uses fully qualified symbols, so it can be used outside of ``pybind11::detail``. `#3758 `_ * Some fixes for PyPy 3.9. `#3768 `_ * Fixed a potential memleak in PyPy in ``get_type_override``. `#3774 `_ * Fix usage of ``VISIBILITY_INLINES_HIDDEN``. `#3721 `_ Build system improvements: * Uses ``sysconfig`` module to determine installation locations on Python >= 3.10, instead of ``distutils`` which has been deprecated. `#3764 `_ * Support Catch 2.13.5+ (supporting GLIBC 2.34+). `#3679 `_ * Fix test failures with numpy 1.22 by ignoring whitespace when comparing ``str()`` of dtypes. `#3682 `_ Backend and tidying up: * clang-tidy: added ``readability-qualified-auto``, ``readability-braces-around-statements``, ``cppcoreguidelines-prefer-member-initializer``, ``clang-analyzer-optin.performance.Padding``, ``cppcoreguidelines-pro-type-static-cast-downcast``, and ``readability-inconsistent-declaration-parameter-name``. `#3702 `_, `#3699 `_, `#3716 `_, `#3709 `_ * clang-format was added to the pre-commit actions, and the entire code base automatically reformatted (after several iterations preparing for this leap). `#3713 `_ Version 2.9.1 (Feb 2, 2022) --------------------------- Changes: * If possible, attach Python exception with ``py::raise_from`` to ``TypeError`` when casting from C++ to Python. This will give additional info if Python exceptions occur in the caster. Adds a test case of trying to convert a set from C++ to Python when the hash function is not defined in Python. `#3605 `_ * Add a mapping of C++11 nested exceptions to their Python exception equivalent using ``py::raise_from``. This attaches the nested exceptions in Python using the ``__cause__`` field. `#3608 `_ * Propagate Python exception traceback using ``raise_from`` if a pybind11 function runs out of overloads. `#3671 `_ * ``py::multiple_inheritance`` is now only needed when C++ bases are hidden from pybind11. `#3650 `_ and `#3659 `_ Bug fixes: * Remove a boolean cast in ``numpy.h`` that causes MSVC C4800 warnings when compiling against Python 3.10 or newer. `#3669 `_ * Render ``py::bool_`` and ``py::float_`` as ``bool`` and ``float`` respectively. `#3622 `_ Build system improvements: * Fix CMake extension suffix computation on Python 3.10+. `#3663 `_ * Allow ``CMAKE_ARGS`` to override CMake args in pybind11's own ``setup.py``. `#3577 `_ * Remove a few deprecated c-headers. `#3610 `_ * More uniform handling of test targets. `#3590 `_ * Add clang-tidy readability check to catch potentially swapped function args. `#3611 `_ Version 2.9.0 (Dec 28, 2021) ---------------------------- This is the last version to support Python 2.7 and 3.5. New Features: * Allow ``py::args`` to be followed by other arguments; the remaining arguments are implicitly keyword-only, as if a ``py::kw_only{}`` annotation had been used. `#3402 `_ Changes: * Make str/bytes/memoryview more interoperable with ``std::string_view``. `#3521 `_ * Replace ``_`` with ``const_name`` in internals, avoid defining ``pybind::_`` if ``_`` defined as macro (common gettext usage) `#3423 `_ Bug fixes: * Fix a rare warning about extra copy in an Eigen constructor. `#3486 `_ * Fix caching of the C++ overrides. `#3465 `_ * Add missing ``std::forward`` calls to some ``cpp_function`` overloads. `#3443 `_ * Support PyPy 7.3.7 and the PyPy3.8 beta. Test python-3.11 on PRs with the ``python dev`` label. `#3419 `_ * Replace usage of deprecated ``Eigen::MappedSparseMatrix`` with ``Eigen::Map>`` for Eigen 3.3+. `#3499 `_ * Tweaks to support Microsoft Visual Studio 2022. `#3497 `_ Build system improvements: * Nicer CMake printout and IDE organisation for pybind11's own tests. `#3479 `_ * CMake: report version type as part of the version string to avoid a spurious space in the package status message. `#3472 `_ * Flags starting with ``-g`` in ``$CFLAGS`` and ``$CPPFLAGS`` are no longer overridden by ``.Pybind11Extension``. `#3436 `_ * Ensure ThreadPool is closed in ``setup_helpers``. `#3548 `_ * Avoid LTS on ``mips64`` and ``ppc64le`` (reported broken). `#3557 `_ v2.8.1 (Oct 27, 2021) --------------------- Changes and additions: * The simple namespace creation shortcut added in 2.8.0 was deprecated due to usage of CPython internal API, and will be removed soon. Use ``py::module_::import("types").attr("SimpleNamespace")``. `#3374 `_ * Add C++ Exception type to throw and catch ``AttributeError``. Useful for defining custom ``__setattr__`` and ``__getattr__`` methods. `#3387 `_ Fixes: * Fixed the potential for dangling references when using properties with ``std::optional`` types. `#3376 `_ * Modernize usage of ``PyCodeObject`` on Python 3.9+ (moving toward support for Python 3.11a1) `#3368 `_ * A long-standing bug in ``eigen.h`` was fixed (originally PR #3343). The bug was unmasked by newly added ``static_assert``'s in the Eigen 3.4.0 release. `#3352 `_ * Support multiple raw inclusion of CMake helper files (Conan.io does this for multi-config generators). `#3420 `_ * Fix harmless warning on upcoming CMake 3.22. `#3368 `_ * Fix 2.8.0 regression with MSVC 2017 + C++17 mode + Python 3. `#3407 `_ * Fix 2.8.0 regression that caused undefined behavior (typically segfaults) in ``make_key_iterator``/``make_value_iterator`` if dereferencing the iterator returned a temporary value instead of a reference. `#3348 `_ v2.8.0 (Oct 4, 2021) -------------------- New features: * Added ``py::raise_from`` to enable chaining exceptions. `#3215 `_ * Allow exception translators to be optionally registered local to a module instead of applying globally across all pybind11 modules. Use ``register_local_exception_translator(ExceptionTranslator&& translator)`` instead of ``register_exception_translator(ExceptionTranslator&& translator)`` to keep your exception remapping code local to the module. `#2650 `_ * Add ``make_simple_namespace`` function for instantiating Python ``SimpleNamespace`` objects. **Deprecated in 2.8.1.** `#2840 `_ * ``pybind11::scoped_interpreter`` and ``initialize_interpreter`` have new arguments to allow ``sys.argv`` initialization. `#2341 `_ * Allow Python builtins to be used as callbacks in CPython. `#1413 `_ * Added ``view`` to view arrays with a different datatype. `#987 `_ * Implemented ``reshape`` on arrays. `#984 `_ * Enable defining custom ``__new__`` methods on classes by fixing bug preventing overriding methods if they have non-pybind11 siblings. `#3265 `_ * Add ``make_value_iterator()``, and fix ``make_key_iterator()`` to return references instead of copies. `#3293 `_ * Improve the classes generated by ``bind_map``: `#3310 `_ * Change ``.items`` from an iterator to a dictionary view. * Add ``.keys`` and ``.values`` (both dictionary views). * Allow ``__contains__`` to take any object. * ``pybind11::custom_type_setup`` was added, for customizing the ``PyHeapTypeObject`` corresponding to a class, which may be useful for enabling garbage collection support, among other things. `#3287 `_ Changes: * Set ``__file__`` constant when running ``eval_file`` in an embedded interpreter. `#3233 `_ * Python objects and (C++17) ``std::optional`` now accepted in ``py::slice`` constructor. `#1101 `_ * The pybind11 proxy types ``str``, ``bytes``, ``bytearray``, ``tuple``, ``list`` now consistently support passing ``ssize_t`` values for sizes and indexes. Previously, only ``size_t`` was accepted in several interfaces. `#3219 `_ * Avoid evaluating ``PYBIND11_TLS_REPLACE_VALUE`` arguments more than once. `#3290 `_ Fixes: * Bug fix: enum value's ``__int__`` returning non-int when underlying type is bool or of char type. `#1334 `_ * Fixes bug in setting error state in Capsule's pointer methods. `#3261 `_ * A long-standing memory leak in ``py::cpp_function::initialize`` was fixed. `#3229 `_ * Fixes thread safety for some ``pybind11::type_caster`` which require lifetime extension, such as for ``std::string_view``. `#3237 `_ * Restore compatibility with gcc 4.8.4 as distributed by ubuntu-trusty, linuxmint-17. `#3270 `_ Build system improvements: * Fix regression in CMake Python package config: improper use of absolute path. `#3144 `_ * Cached Python version information could become stale when CMake was re-run with a different Python version. The build system now detects this and updates this information. `#3299 `_ * Specified UTF8-encoding in setup.py calls of open(). `#3137 `_ * Fix a harmless warning from CMake 3.21 with the classic Python discovery. `#3220 `_ * Eigen repo and version can now be specified as cmake options. `#3324 `_ Backend and tidying up: * Reduced thread-local storage required for keeping alive temporary data for type conversion to one key per ABI version, rather than one key per extension module. This makes the total thread-local storage required by pybind11 2 keys per ABI version. `#3275 `_ * Optimize NumPy array construction with additional moves. `#3183 `_ * Conversion to ``std::string`` and ``std::string_view`` now avoids making an extra copy of the data on Python >= 3.3. `#3257 `_ * Remove const modifier from certain C++ methods on Python collections (``list``, ``set``, ``dict``) such as (``clear()``, ``append()``, ``insert()``, etc...) and annotated them with ``py-non-const``. * Enable readability ``clang-tidy-const-return`` and remove useless consts. `#3254 `_ `#3194 `_ * The clang-tidy ``google-explicit-constructor`` option was enabled. `#3250 `_ * Mark a pytype move constructor as noexcept (perf). `#3236 `_ * Enable clang-tidy check to guard against inheritance slicing. `#3210 `_ * Legacy warning suppression pragma were removed from eigen.h. On Unix platforms, please use -isystem for Eigen include directories, to suppress compiler warnings originating from Eigen headers. Note that CMake does this by default. No adjustments are needed for Windows. `#3198 `_ * Format pybind11 with isort consistent ordering of imports `#3195 `_ * The warnings-suppression "pragma clamp" at the top/bottom of pybind11 was removed, clearing the path to refactoring and IWYU cleanup. `#3186 `_ * Enable most bugprone checks in clang-tidy and fix the found potential bugs and poor coding styles. `#3166 `_ * Add ``clang-tidy-readability`` rules to make boolean casts explicit improving code readability. Also enabled other misc and readability clang-tidy checks. `#3148 `_ * Move object in ``.pop()`` for list. `#3116 `_ v2.7.1 (Aug 3, 2021) --------------------- Minor missing functionality added: * Allow Python builtins to be used as callbacks in CPython. `#1413 `_ Bug fixes: * Fix regression in CMake Python package config: improper use of absolute path. `#3144 `_ * Fix Mingw64 and add to the CI testing matrix. `#3132 `_ * Specified UTF8-encoding in setup.py calls of open(). `#3137 `_ * Add clang-tidy-readability rules to make boolean casts explicit improving code readability. Also enabled other misc and readability clang-tidy checks. `#3148 `_ * Move object in ``.pop()`` for list. `#3116 `_ Backend and tidying up: * Removed and fixed warning suppressions. `#3127 `_ `#3129 `_ `#3135 `_ `#3141 `_ `#3142 `_ `#3150 `_ `#3152 `_ `#3160 `_ `#3161 `_ v2.7.0 (Jul 16, 2021) --------------------- New features: * Enable ``py::implicitly_convertible`` for ``py::class_``-wrapped types. `#3059 `_ * Allow function pointer extraction from overloaded functions. `#2944 `_ * NumPy: added ``.char_()`` to type which gives the NumPy public ``char`` result, which also distinguishes types by bit length (unlike ``.kind()``). `#2864 `_ * Add ``pybind11::bytearray`` to manipulate ``bytearray`` similar to ``bytes``. `#2799 `_ * ``pybind11/stl/filesystem.h`` registers a type caster that, on C++17/Python 3.6+, converts ``std::filesystem::path`` to ``pathlib.Path`` and any ``os.PathLike`` to ``std::filesystem::path``. `#2730 `_ * A ``PYBIND11_VERSION_HEX`` define was added, similar to ``PY_VERSION_HEX``. `#3120 `_ Changes: * ``py::str`` changed to exclusively hold ``PyUnicodeObject``. Previously ``py::str`` could also hold ``bytes``, which is probably surprising, was never documented, and can mask bugs (e.g. accidental use of ``py::str`` instead of ``py::bytes``). `#2409 `_ * Add a safety guard to ensure that the Python GIL is held when C++ calls back into Python via ``object_api<>::operator()`` (e.g. ``py::function`` ``__call__``). (This feature is available for Python 3.6+ only.) `#2919 `_ * Catch a missing ``self`` argument in calls to ``__init__()``. `#2914 `_ * Use ``std::string_view`` if available to avoid a copy when passing an object to a ``std::ostream``. `#3042 `_ * An important warning about thread safety was added to the ``iostream.h`` documentation; attempts to make ``py::scoped_ostream_redirect`` thread safe have been removed, as it was only partially effective. `#2995 `_ Fixes: * Performance: avoid unnecessary strlen calls. `#3058 `_ * Fix auto-generated documentation string when using ``const T`` in ``pyarray_t``. `#3020 `_ * Unify error messages thrown by ``simple_collector``/``unpacking_collector``. `#3013 `_ * ``pybind11::builtin_exception`` is now explicitly exported, which means the types included/defined in different modules are identical, and exceptions raised in different modules can be caught correctly. The documentation was updated to explain that custom exceptions that are used across module boundaries need to be explicitly exported as well. `#2999 `_ * Fixed exception when printing UTF-8 to a ``scoped_ostream_redirect``. `#2982 `_ * Pickle support enhancement: ``setstate`` implementation will attempt to ``setattr`` ``__dict__`` only if the unpickled ``dict`` object is not empty, to not force use of ``py::dynamic_attr()`` unnecessarily. `#2972 `_ * Allow negative timedelta values to roundtrip. `#2870 `_ * Fix unchecked errors could potentially swallow signals/other exceptions. `#2863 `_ * Add null pointer check with ``std::localtime``. `#2846 `_ * Fix the ``weakref`` constructor from ``py::object`` to create a new ``weakref`` on conversion. `#2832 `_ * Avoid relying on exceptions in C++17 when getting a ``shared_ptr`` holder from a ``shared_from_this`` class. `#2819 `_ * Allow the codec's exception to be raised instead of :code:`RuntimeError` when casting from :code:`py::str` to :code:`std::string`. `#2903 `_ Build system improvements: * In ``setup_helpers.py``, test for platforms that have some multiprocessing features but lack semaphores, which ``ParallelCompile`` requires. `#3043 `_ * Fix ``pybind11_INCLUDE_DIR`` in case ``CMAKE_INSTALL_INCLUDEDIR`` is absolute. `#3005 `_ * Fix bug not respecting ``WITH_SOABI`` or ``WITHOUT_SOABI`` to CMake. `#2938 `_ * Fix the default ``Pybind11Extension`` compilation flags with a Mingw64 python. `#2921 `_ * Clang on Windows: do not pass ``/MP`` (ignored flag). `#2824 `_ * ``pybind11.setup_helpers.intree_extensions`` can be used to generate ``Pybind11Extension`` instances from cpp files placed in the Python package source tree. `#2831 `_ Backend and tidying up: * Enable clang-tidy performance, readability, and modernization checks throughout the codebase to enforce best coding practices. `#3046 `_, `#3049 `_, `#3051 `_, `#3052 `_, `#3080 `_, and `#3094 `_ * Checks for common misspellings were added to the pre-commit hooks. `#3076 `_ * Changed ``Werror`` to stricter ``Werror-all`` for Intel compiler and fixed minor issues. `#2948 `_ * Fixed compilation with GCC < 5 when the user defines ``_GLIBCXX_USE_CXX11_ABI``. `#2956 `_ * Added nox support for easier local testing and linting of contributions. `#3101 `_ and `#3121 `_ * Avoid RTD style issue with docutils 0.17+. `#3119 `_ * Support pipx run, such as ``pipx run pybind11 --include`` for a quick compile. `#3117 `_ v2.6.2 (Jan 26, 2021) --------------------- Minor missing functionality added: * enum: add missing Enum.value property. `#2739 `_ * Allow thread termination to be avoided during shutdown for CPython 3.7+ via ``.disarm`` for ``gil_scoped_acquire``/``gil_scoped_release``. `#2657 `_ Fixed or improved behavior in a few special cases: * Fix bug where the constructor of ``object`` subclasses would not throw on being passed a Python object of the wrong type. `#2701 `_ * The ``type_caster`` for integers does not convert Python objects with ``__int__`` anymore with ``noconvert`` or during the first round of trying overloads. `#2698 `_ * When casting to a C++ integer, ``__index__`` is always called and not considered as conversion, consistent with Python 3.8+. `#2801 `_ Build improvements: * Setup helpers: ``extra_compile_args`` and ``extra_link_args`` automatically set by Pybind11Extension are now prepended, which allows them to be overridden by user-set ``extra_compile_args`` and ``extra_link_args``. `#2808 `_ * Setup helpers: Don't trigger unused parameter warning. `#2735 `_ * CMake: Support running with ``--warn-uninitialized`` active. `#2806 `_ * CMake: Avoid error if included from two submodule directories. `#2804 `_ * CMake: Fix ``STATIC`` / ``SHARED`` being ignored in FindPython mode. `#2796 `_ * CMake: Respect the setting for ``CMAKE_CXX_VISIBILITY_PRESET`` if defined. `#2793 `_ * CMake: Fix issue with FindPython2/FindPython3 not working with ``pybind11::embed``. `#2662 `_ * CMake: mixing local and installed pybind11's would prioritize the installed one over the local one (regression in 2.6.0). `#2716 `_ Bug fixes: * Fixed segfault in multithreaded environments when using ``scoped_ostream_redirect``. `#2675 `_ * Leave docstring unset when all docstring-related options are disabled, rather than set an empty string. `#2745 `_ * The module key in builtins that pybind11 uses to store its internals changed from std::string to a python str type (more natural on Python 2, no change on Python 3). `#2814 `_ * Fixed assertion error related to unhandled (later overwritten) exception in CPython 3.8 and 3.9 debug builds. `#2685 `_ * Fix ``py::gil_scoped_acquire`` assert with CPython 3.9 debug build. `#2683 `_ * Fix issue with a test failing on pytest 6.2. `#2741 `_ Warning fixes: * Fix warning modifying constructor parameter 'flag' that shadows a field of 'set_flag' ``[-Wshadow-field-in-constructor-modified]``. `#2780 `_ * Suppressed some deprecation warnings about old-style ``__init__``/``__setstate__`` in the tests. `#2759 `_ Valgrind work: * Fix invalid access when calling a pybind11 ``__init__`` on a non-pybind11 class instance. `#2755 `_ * Fixed various minor memory leaks in pybind11's test suite. `#2758 `_ * Resolved memory leak in cpp_function initialization when exceptions occurred. `#2756 `_ * Added a Valgrind build, checking for leaks and memory-related UB, to CI. `#2746 `_ Compiler support: * Intel compiler was not activating C++14 support due to a broken define. `#2679 `_ * Support ICC and NVIDIA HPC SDK in C++17 mode. `#2729 `_ * Support Intel OneAPI compiler (ICC 20.2) and add to CI. `#2573 `_ v2.6.1 (Nov 11, 2020) --------------------- * ``py::exec``, ``py::eval``, and ``py::eval_file`` now add the builtins module as ``"__builtins__"`` to their ``globals`` argument, better matching ``exec`` and ``eval`` in pure Python. `#2616 `_ * ``setup_helpers`` will no longer set a minimum macOS version higher than the current version. `#2622 `_ * Allow deleting static properties. `#2629 `_ * Seal a leak in ``def_buffer``, cleaning up the ``capture`` object after the ``class_`` object goes out of scope. `#2634 `_ * ``pybind11_INCLUDE_DIRS`` was incorrect, potentially causing a regression if it was expected to include ``PYTHON_INCLUDE_DIRS`` (please use targets instead). `#2636 `_ * Added parameter names to the ``py::enum_`` constructor and methods, avoiding ``arg0`` in the generated docstrings. `#2637 `_ * Added ``needs_recompile`` optional function to the ``ParallelCompiler`` helper, to allow a recompile to be skipped based on a user-defined function. `#2643 `_ v2.6.0 (Oct 21, 2020) --------------------- See :ref:`upgrade-guide-2.6` for help upgrading to the new version. New features: * Keyword-only arguments supported in Python 2 or 3 with ``py::kw_only()``. `#2100 `_ * Positional-only arguments supported in Python 2 or 3 with ``py::pos_only()``. `#2459 `_ * ``py::is_final()`` class modifier to block subclassing (CPython only). `#2151 `_ * Added ``py::prepend()``, allowing a function to be placed at the beginning of the overload chain. `#1131 `_ * Access to the type object now provided with ``py::type::of()`` and ``py::type::of(h)``. `#2364 `_ * Perfect forwarding support for methods. `#2048 `_ * Added ``py::error_already_set::discard_as_unraisable()``. `#2372 `_ * ``py::hash`` is now public. `#2217 `_ * ``py::class_`` is now supported. Note that writing to one data member of the union and reading another (type punning) is UB in C++. Thus pybind11-bound enums should never be used for such conversions. `#2320 `_. * Classes now check local scope when registering members, allowing a subclass to have a member with the same name as a parent (such as an enum). `#2335 `_ Code correctness features: * Error now thrown when ``__init__`` is forgotten on subclasses. `#2152 `_ * Throw error if conversion to a pybind11 type if the Python object isn't a valid instance of that type, such as ``py::bytes(o)`` when ``py::object o`` isn't a bytes instance. `#2349 `_ * Throw if conversion to ``str`` fails. `#2477 `_ API changes: * ``py::module`` was renamed ``py::module_`` to avoid issues with C++20 when used unqualified, but an alias ``py::module`` is provided for backward compatibility. `#2489 `_ * Public constructors for ``py::module_`` have been deprecated; please use ``pybind11::module_::create_extension_module`` if you were using the public constructor (fairly rare after ``PYBIND11_MODULE`` was introduced). `#2552 `_ * ``PYBIND11_OVERLOAD*`` macros and ``get_overload`` function replaced by correctly-named ``PYBIND11_OVERRIDE*`` and ``get_override``, fixing inconsistencies in the presence of a closing ``;`` in these macros. ``get_type_overload`` is deprecated. `#2325 `_ Packaging / building improvements: * The Python package was reworked to be more powerful and useful. `#2433 `_ * :ref:`build-setuptools` is easier thanks to a new ``pybind11.setup_helpers`` module, which provides utilities to use setuptools with pybind11. It can be used via PEP 518, ``setup_requires``, or by directly importing or copying ``setup_helpers.py`` into your project. * CMake configuration files are now included in the Python package. Use ``pybind11.get_cmake_dir()`` or ``python -m pybind11 --cmakedir`` to get the directory with the CMake configuration files, or include the site-packages location in your ``CMAKE_MODULE_PATH``. Or you can use the new ``pybind11[global]`` extra when you install ``pybind11``, which installs the CMake files and headers into your base environment in the standard location. * ``pybind11-config`` is another way to write ``python -m pybind11`` if you have your PATH set up. * Added external typing support to the helper module, code from ``import pybind11`` can now be type checked. `#2588 `_ * Minimum CMake required increased to 3.4. `#2338 `_ and `#2370 `_ * Full integration with CMake's C++ standard system and compile features replaces ``PYBIND11_CPP_STANDARD``. * Generated config file is now portable to different Python/compiler/CMake versions. * Virtual environments prioritized if ``PYTHON_EXECUTABLE`` is not set (``venv``, ``virtualenv``, and ``conda``) (similar to the new FindPython mode). * Other CMake features now natively supported, like ``CMAKE_INTERPROCEDURAL_OPTIMIZATION``, ``set(CMAKE_CXX_VISIBILITY_PRESET hidden)``. * ``CUDA`` as a language is now supported. * Helper functions ``pybind11_strip``, ``pybind11_extension``, ``pybind11_find_import`` added, see :doc:`cmake/index`. * Optional :ref:`find-python-mode` and :ref:`nopython-mode` with CMake. `#2370 `_ * Uninstall target added. `#2265 `_ and `#2346 `_ * ``pybind11_add_module()`` now accepts an optional ``OPT_SIZE`` flag that switches the binding target to size-based optimization if the global build type can not always be fixed to ``MinSizeRel`` (except in debug mode, where optimizations remain disabled). ``MinSizeRel`` or this flag reduces binary size quite substantially (~25% on some platforms). `#2463 `_ Smaller or developer focused features and fixes: * Moved ``mkdoc.py`` to a new repo, `pybind11-mkdoc`_. There are no longer submodules in the main repo. * ``py::memoryview`` segfault fix and update, with new ``py::memoryview::from_memory`` in Python 3, and documentation. `#2223 `_ * Fix for ``buffer_info`` on Python 2. `#2503 `_ * If ``__eq__`` defined but not ``__hash__``, ``__hash__`` is now set to ``None``. `#2291 `_ * ``py::ellipsis`` now also works on Python 2. `#2360 `_ * Pointer to ``std::tuple`` & ``std::pair`` supported in cast. `#2334 `_ * Small fixes in NumPy support. ``py::array`` now uses ``py::ssize_t`` as first argument type. `#2293 `_ * Added missing signature for ``py::array``. `#2363 `_ * ``unchecked_mutable_reference`` has access to operator ``()`` and ``[]`` when const. `#2514 `_ * ``py::vectorize`` is now supported on functions that return void. `#1969 `_ * ``py::capsule`` supports ``get_pointer`` and ``set_pointer``. `#1131 `_ * Fix crash when different instances share the same pointer of the same type. `#2252 `_ * Fix for ``py::len`` not clearing Python's error state when it fails and throws. `#2575 `_ * Bugfixes related to more extensive testing, new GitHub Actions CI. `#2321 `_ * Bug in timezone issue in Eastern hemisphere midnight fixed. `#2438 `_ * ``std::chrono::time_point`` now works when the resolution is not the same as the system. `#2481 `_ * Bug fixed where ``py::array_t`` could accept arrays that did not match the requested ordering. `#2484 `_ * Avoid a segfault on some compilers when types are removed in Python. `#2564 `_ * ``py::arg::none()`` is now also respected when passing keyword arguments. `#2611 `_ * PyPy fixes, PyPy 7.3.x now supported, including PyPy3. (Known issue with PyPy2 and Windows `#2596 `_). `#2146 `_ * CPython 3.9.0 workaround for undefined behavior (macOS segfault). `#2576 `_ * CPython 3.9 warning fixes. `#2253 `_ * Improved C++20 support, now tested in CI. `#2489 `_ `#2599 `_ * Improved but still incomplete debug Python interpreter support. `#2025 `_ * NVCC (CUDA 11) now supported and tested in CI. `#2461 `_ * NVIDIA PGI compilers now supported and tested in CI. `#2475 `_ * At least Intel 18 now explicitly required when compiling with Intel. `#2577 `_ * Extensive style checking in CI, with `pre-commit`_ support. Code modernization, checked by clang-tidy. * Expanded docs, including new main page, new installing section, and CMake helpers page, along with over a dozen new sections on existing pages. * In GitHub, new docs for contributing and new issue templates. .. _pre-commit: https://pre-commit.com .. _pybind11-mkdoc: https://github.com/pybind/pybind11-mkdoc v2.5.0 (Mar 31, 2020) ----------------------------------------------------- * Use C++17 fold expressions in type casters, if available. This can improve performance during overload resolution when functions have multiple arguments. `#2043 `_. * Changed include directory resolution in ``pybind11/__init__.py`` and installation in ``setup.py``. This fixes a number of open issues where pybind11 headers could not be found in certain environments. `#1995 `_. * C++20 ``char8_t`` and ``u8string`` support. `#2026 `_. * CMake: search for Python 3.9. `bb9c91 `_. * Fixes for MSYS-based build environments. `#2087 `_, `#2053 `_. * STL bindings for ``std::vector<...>::clear``. `#2074 `_. * Read-only flag for ``py::buffer``. `#1466 `_. * Exception handling during module initialization. `bf2b031 `_. * Support linking against a CPython debug build. `#2025 `_. * Fixed issues involving the availability and use of aligned ``new`` and ``delete``. `#1988 `_, `759221 `_. * Fixed a resource leak upon interpreter shutdown. `#2020 `_. * Fixed error handling in the boolean caster. `#1976 `_. v2.4.3 (Oct 15, 2019) ----------------------------------------------------- * Adapt pybind11 to a C API convention change in Python 3.8. `#1950 `_. v2.4.2 (Sep 21, 2019) ----------------------------------------------------- * Replaced usage of a C++14 only construct. `#1929 `_. * Made an ifdef future-proof for Python >= 4. `f3109d `_. v2.4.1 (Sep 20, 2019) ----------------------------------------------------- * Fixed a problem involving implicit conversion from enumerations to integers on Python 3.8. `#1780 `_. v2.4.0 (Sep 19, 2019) ----------------------------------------------------- * Try harder to keep pybind11-internal data structures separate when there are potential ABI incompatibilities. Fixes crashes that occurred when loading multiple pybind11 extensions that were e.g. compiled by GCC (libstdc++) and Clang (libc++). `#1588 `_ and `c9f5a `_. * Added support for ``__await__``, ``__aiter__``, and ``__anext__`` protocols. `#1842 `_. * ``pybind11_add_module()``: don't strip symbols when compiling in ``RelWithDebInfo`` mode. `#1980 `_. * ``enum_``: Reproduce Python behavior when comparing against invalid values (e.g. ``None``, strings, etc.). Add back support for ``__invert__()``. `#1912 `_, `#1907 `_. * List insertion operation for ``py::list``. Added ``.empty()`` to all collection types. Added ``py::set::contains()`` and ``py::dict::contains()``. `#1887 `_, `#1884 `_, `#1888 `_. * ``py::details::overload_cast_impl`` is available in C++11 mode, can be used like ``overload_cast`` with an additional set of parentheses. `#1581 `_. * Fixed ``get_include()`` on Conda. `#1877 `_. * ``stl_bind.h``: negative indexing support. `#1882 `_. * Minor CMake fix to add MinGW compatibility. `#1851 `_. * GIL-related fixes. `#1836 `_, `8b90b `_. * Other very minor/subtle fixes and improvements. `#1329 `_, `#1910 `_, `#1863 `_, `#1847 `_, `#1890 `_, `#1860 `_, `#1848 `_, `#1821 `_, `#1837 `_, `#1833 `_, `#1748 `_, `#1852 `_. v2.3.0 (June 11, 2019) ----------------------------------------------------- * Significantly reduced module binary size (10-20%) when compiled in C++11 mode with GCC/Clang, or in any mode with MSVC. Function signatures are now always precomputed at compile time (this was previously only available in C++14 mode for non-MSVC compilers). `#934 `_. * Add basic support for tag-based static polymorphism, where classes provide a method to returns the desired type of an instance. `#1326 `_. * Python type wrappers (``py::handle``, ``py::object``, etc.) now support map Python's number protocol onto C++ arithmetic operators such as ``operator+``, ``operator/=``, etc. `#1511 `_. * A number of improvements related to enumerations: 1. The ``enum_`` implementation was rewritten from scratch to reduce code bloat. Rather than instantiating a full implementation for each enumeration, most code is now contained in a generic base class. `#1511 `_. 2. The ``value()`` method of ``py::enum_`` now accepts an optional docstring that will be shown in the documentation of the associated enumeration. `#1160 `_. 3. check for already existing enum value and throw an error if present. `#1453 `_. * Support for over-aligned type allocation via C++17's aligned ``new`` statement. `#1582 `_. * Added ``py::ellipsis()`` method for slicing of multidimensional NumPy arrays `#1502 `_. * Numerous Improvements to the ``mkdoc.py`` script for extracting documentation from C++ header files. `#1788 `_. * ``pybind11_add_module()``: allow including Python as a ``SYSTEM`` include path. `#1416 `_. * ``pybind11/stl.h`` does not convert strings to ``vector`` anymore. `#1258 `_. * Mark static methods as such to fix auto-generated Sphinx documentation. `#1732 `_. * Re-throw forced unwind exceptions (e.g. during pthread termination). `#1208 `_. * Added ``__contains__`` method to the bindings of maps (``std::map``, ``std::unordered_map``). `#1767 `_. * Improvements to ``gil_scoped_acquire``. `#1211 `_. * Type caster support for ``std::deque``. `#1609 `_. * Support for ``std::unique_ptr`` holders, whose deleters differ between a base and derived class. `#1353 `_. * Construction of STL array/vector-like data structures from iterators. Added an ``extend()`` operation. `#1709 `_, * CMake build system improvements for projects that include non-C++ files (e.g. plain C, CUDA) in ``pybind11_add_module`` et al. `#1678 `_. * Fixed asynchronous invocation and deallocation of Python functions wrapped in ``std::function``. `#1595 `_. * Fixes regarding return value policy propagation in STL type casters. `#1603 `_. * Fixed scoped enum comparisons. `#1571 `_. * Fixed iostream redirection for code that releases the GIL. `#1368 `_, * A number of CI-related fixes. `#1757 `_, `#1744 `_, `#1670 `_. v2.2.4 (September 11, 2018) ----------------------------------------------------- * Use new Python 3.7 Thread Specific Storage (TSS) implementation if available. `#1454 `_, `#1517 `_. * Fixes for newer MSVC versions and C++17 mode. `#1347 `_, `#1462 `_. * Propagate return value policies to type-specific casters when casting STL containers. `#1455 `_. * Allow ostream-redirection of more than 1024 characters. `#1479 `_. * Set ``Py_DEBUG`` define when compiling against a debug Python build. `#1438 `_. * Untangle integer logic in number type caster to work for custom types that may only be castable to a restricted set of builtin types. `#1442 `_. * CMake build system: Remember Python version in cache file. `#1434 `_. * Fix for custom smart pointers: use ``std::addressof`` to obtain holder address instead of ``operator&``. `#1435 `_. * Properly report exceptions thrown during module initialization. `#1362 `_. * Fixed a segmentation fault when creating empty-shaped NumPy array. `#1371 `_. * The version of Intel C++ compiler must be >= 2017, and this is now checked by the header files. `#1363 `_. * A few minor typo fixes and improvements to the test suite, and patches that silence compiler warnings. * Vectors now support construction from generators, as well as ``extend()`` from a list or generator. `#1496 `_. v2.2.3 (April 29, 2018) ----------------------------------------------------- * The pybind11 header location detection was replaced by a new implementation that no longer depends on ``pip`` internals (the recently released ``pip`` 10 has restricted access to this API). `#1190 `_. * Small adjustment to an implementation detail to work around a compiler segmentation fault in Clang 3.3/3.4. `#1350 `_. * The minimal supported version of the Intel compiler was >= 17.0 since pybind11 v2.1. This check is now explicit, and a compile-time error is raised if the compiler meet the requirement. `#1363 `_. * Fixed an endianness-related fault in the test suite. `#1287 `_. v2.2.2 (February 7, 2018) ----------------------------------------------------- * Fixed a segfault when combining embedded interpreter shutdown/reinitialization with external loaded pybind11 modules. `#1092 `_. * Eigen support: fixed a bug where Nx1/1xN numpy inputs couldn't be passed as arguments to Eigen vectors (which for Eigen are simply compile-time fixed Nx1/1xN matrices). `#1106 `_. * Clarified to license by moving the licensing of contributions from ``LICENSE`` into ``CONTRIBUTING.md``: the licensing of contributions is not actually part of the software license as distributed. This isn't meant to be a substantial change in the licensing of the project, but addresses concerns that the clause made the license non-standard. `#1109 `_. * Fixed a regression introduced in 2.1 that broke binding functions with lvalue character literal arguments. `#1128 `_. * MSVC: fix for compilation failures under /permissive-, and added the flag to the appveyor test suite. `#1155 `_. * Fixed ``__qualname__`` generation, and in turn, fixes how class names (especially nested class names) are shown in generated docstrings. `#1171 `_. * Updated the FAQ with a suggested project citation reference. `#1189 `_. * Added fixes for deprecation warnings when compiled under C++17 with ``-Wdeprecated`` turned on, and add ``-Wdeprecated`` to the test suite compilation flags. `#1191 `_. * Fixed outdated PyPI URLs in ``setup.py``. `#1213 `_. * Fixed a refcount leak for arguments that end up in a ``py::args`` argument for functions with both fixed positional and ``py::args`` arguments. `#1216 `_. * Fixed a potential segfault resulting from possible premature destruction of ``py::args``/``py::kwargs`` arguments with overloaded functions. `#1223 `_. * Fixed ``del map[item]`` for a ``stl_bind.h`` bound stl map. `#1229 `_. * Fixed a regression from v2.1.x where the aggregate initialization could unintentionally end up at a constructor taking a templated ``std::initializer_list`` argument. `#1249 `_. * Fixed an issue where calling a function with a keep_alive policy on the same nurse/patient pair would cause the internal patient storage to needlessly grow (unboundedly, if the nurse is long-lived). `#1251 `_. * Various other minor fixes. v2.2.1 (September 14, 2017) ----------------------------------------------------- * Added ``py::module_::reload()`` member function for reloading a module. `#1040 `_. * Fixed a reference leak in the number converter. `#1078 `_. * Fixed compilation with Clang on host GCC < 5 (old libstdc++ which isn't fully C++11 compliant). `#1062 `_. * Fixed a regression where the automatic ``std::vector`` caster would fail to compile. The same fix also applies to any container which returns element proxies instead of references. `#1053 `_. * Fixed a regression where the ``py::keep_alive`` policy could not be applied to constructors. `#1065 `_. * Fixed a nullptr dereference when loading a ``py::module_local`` type that's only registered in an external module. `#1058 `_. * Fixed implicit conversion of accessors to types derived from ``py::object``. `#1076 `_. * The ``name`` in ``PYBIND11_MODULE(name, variable)`` can now be a macro. `#1082 `_. * Relaxed overly strict ``py::pickle()`` check for matching get and set types. `#1064 `_. * Conversion errors now try to be more informative when it's likely that a missing header is the cause (e.g. forgetting ````). `#1077 `_. v2.2.0 (August 31, 2017) ----------------------------------------------------- * Support for embedding the Python interpreter. See the :doc:`documentation page ` for a full overview of the new features. `#774 `_, `#889 `_, `#892 `_, `#920 `_. .. code-block:: cpp #include namespace py = pybind11; int main() { py::scoped_interpreter guard{}; // start the interpreter and keep it alive py::print("Hello, World!"); // use the Python API } * Support for inheriting from multiple C++ bases in Python. `#693 `_. .. code-block:: python from cpp_module import CppBase1, CppBase2 class PyDerived(CppBase1, CppBase2): def __init__(self): CppBase1.__init__(self) # C++ bases must be initialized explicitly CppBase2.__init__(self) * ``PYBIND11_MODULE`` is now the preferred way to create module entry points. ``PYBIND11_PLUGIN`` is deprecated. See :ref:`macros` for details. `#879 `_. .. code-block:: cpp // new PYBIND11_MODULE(example, m) { m.def("add", [](int a, int b) { return a + b; }); } // old PYBIND11_PLUGIN(example) { py::module m("example"); m.def("add", [](int a, int b) { return a + b; }); return m.ptr(); } * pybind11's headers and build system now more strictly enforce hidden symbol visibility for extension modules. This should be seamless for most users, but see the :doc:`upgrade` if you use a custom build system. `#995 `_. * Support for ``py::module_local`` types which allow multiple modules to export the same C++ types without conflicts. This is useful for opaque types like ``std::vector``. ``py::bind_vector`` and ``py::bind_map`` now default to ``py::module_local`` if their elements are builtins or local types. See :ref:`module_local` for details. `#949 `_, `#981 `_, `#995 `_, `#997 `_. * Custom constructors can now be added very easily using lambdas or factory functions which return a class instance by value, pointer or holder. This supersedes the old placement-new ``__init__`` technique. See :ref:`custom_constructors` for details. `#805 `_, `#1014 `_. .. code-block:: cpp struct Example { Example(std::string); }; py::class_(m, "Example") .def(py::init()) // existing constructor .def(py::init([](int n) { // custom constructor return std::make_unique(std::to_string(n)); })); * Similarly to custom constructors, pickling support functions are now bound using the ``py::pickle()`` adaptor which improves type safety. See the :doc:`upgrade` and :ref:`pickling` for details. `#1038 `_. * Builtin support for converting C++17 standard library types and general conversion improvements: 1. C++17 ``std::variant`` is supported right out of the box. C++11/14 equivalents (e.g. ``boost::variant``) can also be added with a simple user-defined specialization. See :ref:`cpp17_container_casters` for details. `#811 `_, `#845 `_, `#989 `_. 2. Out-of-the-box support for C++17 ``std::string_view``. `#906 `_. 3. Improved compatibility of the builtin ``optional`` converter. `#874 `_. 4. The ``bool`` converter now accepts ``numpy.bool_`` and types which define ``__bool__`` (Python 3.x) or ``__nonzero__`` (Python 2.7). `#925 `_. 5. C++-to-Python casters are now more efficient and move elements out of rvalue containers whenever possible. `#851 `_, `#936 `_, `#938 `_. 6. Fixed ``bytes`` to ``std::string/char*`` conversion on Python 3. `#817 `_. 7. Fixed lifetime of temporary C++ objects created in Python-to-C++ conversions. `#924 `_. * Scope guard call policy for RAII types, e.g. ``py::call_guard()``, ``py::call_guard()``. See :ref:`call_policies` for details. `#740 `_. * Utility for redirecting C++ streams to Python (e.g. ``std::cout`` -> ``sys.stdout``). Scope guard ``py::scoped_ostream_redirect`` in C++ and a context manager in Python. See :ref:`ostream_redirect`. `#1009 `_. * Improved handling of types and exceptions across module boundaries. `#915 `_, `#951 `_, `#995 `_. * Fixed destruction order of ``py::keep_alive`` nurse/patient objects in reference cycles. `#856 `_. * NumPy and buffer protocol related improvements: 1. Support for negative strides in Python buffer objects/numpy arrays. This required changing integers from unsigned to signed for the related C++ APIs. Note: If you have compiler warnings enabled, you may notice some new conversion warnings after upgrading. These can be resolved with ``static_cast``. `#782 `_. 2. Support ``std::complex`` and arrays inside ``PYBIND11_NUMPY_DTYPE``. `#831 `_, `#832 `_. 3. Support for constructing ``py::buffer_info`` and ``py::arrays`` using arbitrary containers or iterators instead of requiring a ``std::vector``. `#788 `_, `#822 `_, `#860 `_. 4. Explicitly check numpy version and require >= 1.7.0. `#819 `_. * Support for allowing/prohibiting ``None`` for specific arguments and improved ``None`` overload resolution order. See :ref:`none_arguments` for details. `#843 `_. `#859 `_. * Added ``py::exec()`` as a shortcut for ``py::eval()`` and support for C++11 raw string literals as input. See :ref:`eval`. `#766 `_, `#827 `_. * ``py::vectorize()`` ignores non-vectorizable arguments and supports member functions. `#762 `_. * Support for bound methods as callbacks (``pybind11/functional.h``). `#815 `_. * Allow aliasing pybind11 methods: ``cls.attr("foo") = cls.attr("bar")``. `#802 `_. * Don't allow mixed static/non-static overloads. `#804 `_. * Fixed overriding static properties in derived classes. `#784 `_. * Added support for write only properties. `#1144 `_. * Improved deduction of member functions of a derived class when its bases aren't registered with pybind11. `#855 `_. .. code-block:: cpp struct Base { int foo() { return 42; } } struct Derived : Base {} // Now works, but previously required also binding `Base` py::class_(m, "Derived") .def("foo", &Derived::foo); // function is actually from `Base` * The implementation of ``py::init<>`` now uses C++11 brace initialization syntax to construct instances, which permits binding implicit constructors of aggregate types. `#1015 `_. .. code-block:: cpp struct Aggregate { int a; std::string b; }; py::class_(m, "Aggregate") .def(py::init()); * Fixed issues with multiple inheritance with offset base/derived pointers. `#812 `_, `#866 `_, `#960 `_. * Fixed reference leak of type objects. `#1030 `_. * Improved support for the ``/std:c++14`` and ``/std:c++latest`` modes on MSVC 2017. `#841 `_, `#999 `_. * Fixed detection of private operator new on MSVC. `#893 `_, `#918 `_. * Intel C++ compiler compatibility fixes. `#937 `_. * Fixed implicit conversion of ``py::enum_`` to integer types on Python 2.7. `#821 `_. * Added ``py::hash`` to fetch the hash value of Python objects, and ``.def(hash(py::self))`` to provide the C++ ``std::hash`` as the Python ``__hash__`` method. `#1034 `_. * Fixed ``__truediv__`` on Python 2 and ``__itruediv__`` on Python 3. `#867 `_. * ``py::capsule`` objects now support the ``name`` attribute. This is useful for interfacing with ``scipy.LowLevelCallable``. `#902 `_. * Fixed ``py::make_iterator``'s ``__next__()`` for past-the-end calls. `#897 `_. * Added ``error_already_set::matches()`` for checking Python exceptions. `#772 `_. * Deprecated ``py::error_already_set::clear()``. It's no longer needed following a simplification of the ``py::error_already_set`` class. `#954 `_. * Deprecated ``py::handle::operator==()`` in favor of ``py::handle::is()`` `#825 `_. * Deprecated ``py::object::borrowed``/``py::object::stolen``. Use ``py::object::borrowed_t{}``/``py::object::stolen_t{}`` instead. `#771 `_. * Changed internal data structure versioning to avoid conflicts between modules compiled with different revisions of pybind11. `#1012 `_. * Additional compile-time and run-time error checking and more informative messages. `#786 `_, `#794 `_, `#803 `_. * Various minor improvements and fixes. `#764 `_, `#791 `_, `#795 `_, `#840 `_, `#844 `_, `#846 `_, `#849 `_, `#858 `_, `#862 `_, `#871 `_, `#872 `_, `#881 `_, `#888 `_, `#899 `_, `#928 `_, `#931 `_, `#944 `_, `#950 `_, `#952 `_, `#962 `_, `#965 `_, `#970 `_, `#978 `_, `#979 `_, `#986 `_, `#1020 `_, `#1027 `_, `#1037 `_. * Testing improvements. `#798 `_, `#882 `_, `#898 `_, `#900 `_, `#921 `_, `#923 `_, `#963 `_. v2.1.1 (April 7, 2017) ----------------------------------------------------- * Fixed minimum version requirement for MSVC 2015u3 `#773 `_. v2.1.0 (March 22, 2017) ----------------------------------------------------- * pybind11 now performs function overload resolution in two phases. The first phase only considers exact type matches, while the second allows for implicit conversions to take place. A special ``noconvert()`` syntax can be used to completely disable implicit conversions for specific arguments. `#643 `_, `#634 `_, `#650 `_. * Fixed a regression where static properties no longer worked with classes using multiple inheritance. The ``py::metaclass`` attribute is no longer necessary (and deprecated as of this release) when binding classes with static properties. `#679 `_, * Classes bound using ``pybind11`` can now use custom metaclasses. `#679 `_, * ``py::args`` and ``py::kwargs`` can now be mixed with other positional arguments when binding functions using pybind11. `#611 `_. * Improved support for C++11 unicode string and character types; added extensive documentation regarding pybind11's string conversion behavior. `#624 `_, `#636 `_, `#715 `_. * pybind11 can now avoid expensive copies when converting Eigen arrays to NumPy arrays (and vice versa). `#610 `_. * The "fast path" in ``py::vectorize`` now works for any full-size group of C or F-contiguous arrays. The non-fast path is also faster since it no longer performs copies of the input arguments (except when type conversions are necessary). `#610 `_. * Added fast, unchecked access to NumPy arrays via a proxy object. `#746 `_. * Transparent support for class-specific ``operator new`` and ``operator delete`` implementations. `#755 `_. * Slimmer and more efficient STL-compatible iterator interface for sequence types. `#662 `_. * Improved custom holder type support. `#607 `_. * ``nullptr`` to ``None`` conversion fixed in various builtin type casters. `#732 `_. * ``enum_`` now exposes its members via a special ``__members__`` attribute. `#666 `_. * ``std::vector`` bindings created using ``stl_bind.h`` can now optionally implement the buffer protocol. `#488 `_. * Automated C++ reference documentation using doxygen and breathe. `#598 `_. * Added minimum compiler version assertions. `#727 `_. * Improved compatibility with C++1z. `#677 `_. * Improved ``py::capsule`` API. Can be used to implement cleanup callbacks that are involved at module destruction time. `#752 `_. * Various minor improvements and fixes. `#595 `_, `#588 `_, `#589 `_, `#603 `_, `#619 `_, `#648 `_, `#695 `_, `#720 `_, `#723 `_, `#729 `_, `#724 `_, `#742 `_, `#753 `_. v2.0.1 (Jan 4, 2017) ----------------------------------------------------- * Fix pointer to reference error in type_caster on MSVC `#583 `_. * Fixed a segmentation in the test suite due to a typo `cd7eac `_. v2.0.0 (Jan 1, 2017) ----------------------------------------------------- * Fixed a reference counting regression affecting types with custom metaclasses (introduced in v2.0.0-rc1). `#571 `_. * Quenched a CMake policy warning. `#570 `_. v2.0.0-rc1 (Dec 23, 2016) ----------------------------------------------------- The pybind11 developers are excited to issue a release candidate of pybind11 with a subsequent v2.0.0 release planned in early January next year. An incredible amount of effort by went into pybind11 over the last ~5 months, leading to a release that is jam-packed with exciting new features and numerous usability improvements. The following list links PRs or individual commits whenever applicable. Happy Christmas! * Support for binding C++ class hierarchies that make use of multiple inheritance. `#410 `_. * PyPy support: pybind11 now supports nightly builds of PyPy and will interoperate with the future 5.7 release. No code changes are necessary, everything "just" works as usual. Note that we only target the Python 2.7 branch for now; support for 3.x will be added once its ``cpyext`` extension support catches up. A few minor features remain unsupported for the time being (notably dynamic attributes in custom types). `#527 `_. * Significant work on the documentation -- in particular, the monolithic ``advanced.rst`` file was restructured into a easier to read hierarchical organization. `#448 `_. * Many NumPy-related improvements: 1. Object-oriented API to access and modify NumPy ``ndarray`` instances, replicating much of the corresponding NumPy C API functionality. `#402 `_. 2. NumPy array ``dtype`` array descriptors are now first-class citizens and are exposed via a new class ``py::dtype``. 3. Structured dtypes can be registered using the ``PYBIND11_NUMPY_DTYPE()`` macro. Special ``array`` constructors accepting dtype objects were also added. One potential caveat involving this change: format descriptor strings should now be accessed via ``format_descriptor::format()`` (however, for compatibility purposes, the old syntax ``format_descriptor::value`` will still work for non-structured data types). `#308 `_. 4. Further improvements to support structured dtypes throughout the system. `#472 `_, `#474 `_, `#459 `_, `#453 `_, `#452 `_, and `#505 `_. 5. Fast access operators. `#497 `_. 6. Constructors for arrays whose storage is owned by another object. `#440 `_. 7. Added constructors for ``array`` and ``array_t`` explicitly accepting shape and strides; if strides are not provided, they are deduced assuming C-contiguity. Also added simplified constructors for 1-dimensional case. 8. Added buffer/NumPy support for ``char[N]`` and ``std::array`` types. 9. Added ``memoryview`` wrapper type which is constructible from ``buffer_info``. * Eigen: many additional conversions and support for non-contiguous arrays/slices. `#427 `_, `#315 `_, `#316 `_, `#312 `_, and `#267 `_ * Incompatible changes in ``class_<...>::class_()``: 1. Declarations of types that provide access via the buffer protocol must now include the ``py::buffer_protocol()`` annotation as an argument to the ``class_`` constructor. 2. Declarations of types that require a custom metaclass (i.e. all classes which include static properties via commands such as ``def_readwrite_static()``) must now include the ``py::metaclass()`` annotation as an argument to the ``class_`` constructor. These two changes were necessary to make type definitions in pybind11 future-proof, and to support PyPy via its cpyext mechanism. `#527 `_. 3. This version of pybind11 uses a redesigned mechanism for instantiating trampoline classes that are used to override virtual methods from within Python. This led to the following user-visible syntax change: instead of .. code-block:: cpp py::class_("MyClass") .alias() .... write .. code-block:: cpp py::class_("MyClass") .... Importantly, both the original and the trampoline class are now specified as an arguments (in arbitrary order) to the ``py::class_`` template, and the ``alias<..>()`` call is gone. The new scheme has zero overhead in cases when Python doesn't override any functions of the underlying C++ class. `rev. 86d825 `_. * Added ``eval`` and ``eval_file`` functions for evaluating expressions and statements from a string or file. `rev. 0d3fc3 `_. * pybind11 can now create types with a modifiable dictionary. `#437 `_ and `#444 `_. * Support for translation of arbitrary C++ exceptions to Python counterparts. `#296 `_ and `#273 `_. * Report full backtraces through mixed C++/Python code, better reporting for import errors, fixed GIL management in exception processing. `#537 `_, `#494 `_, `rev. e72d95 `_, and `rev. 099d6e `_. * Support for bit-level operations, comparisons, and serialization of C++ enumerations. `#503 `_, `#508 `_, `#380 `_, `#309 `_. `#311 `_. * The ``class_`` constructor now accepts its template arguments in any order. `#385 `_. * Attribute and item accessors now have a more complete interface which makes it possible to chain attributes as in ``obj.attr("a")[key].attr("b").attr("method")(1, 2, 3)``. `#425 `_. * Major redesign of the default and conversion constructors in ``pytypes.h``. `#464 `_. * Added built-in support for ``std::shared_ptr`` holder type. It is no longer necessary to to include a declaration of the form ``PYBIND11_DECLARE_HOLDER_TYPE(T, std::shared_ptr)`` (though continuing to do so won't cause an error). `#454 `_. * New ``py::overload_cast`` casting operator to select among multiple possible overloads of a function. An example: .. code-block:: cpp py::class_(m, "Pet") .def("set", py::overload_cast(&Pet::set), "Set the pet's age") .def("set", py::overload_cast(&Pet::set), "Set the pet's name"); This feature only works on C++14-capable compilers. `#541 `_. * C++ types are automatically cast to Python types, e.g. when assigning them as an attribute. For instance, the following is now legal: .. code-block:: cpp py::module m = /* ... */ m.attr("constant") = 123; (Previously, a ``py::cast`` call was necessary to avoid a compilation error.) `#551 `_. * Redesigned ``pytest``-based test suite. `#321 `_. * Instance tracking to detect reference leaks in test suite. `#324 `_ * pybind11 can now distinguish between multiple different instances that are located at the same memory address, but which have different types. `#329 `_. * Improved logic in ``move`` return value policy. `#510 `_, `#297 `_. * Generalized unpacking API to permit calling Python functions from C++ using notation such as ``foo(a1, a2, *args, "ka"_a=1, "kb"_a=2, **kwargs)``. `#372 `_. * ``py::print()`` function whose behavior matches that of the native Python ``print()`` function. `#372 `_. * Added ``py::dict`` keyword constructor:``auto d = dict("number"_a=42, "name"_a="World");``. `#372 `_. * Added ``py::str::format()`` method and ``_s`` literal: ``py::str s = "1 + 2 = {}"_s.format(3);``. `#372 `_. * Added ``py::repr()`` function which is equivalent to Python's builtin ``repr()``. `#333 `_. * Improved construction and destruction logic for holder types. It is now possible to reference instances with smart pointer holder types without constructing the holder if desired. The ``PYBIND11_DECLARE_HOLDER_TYPE`` macro now accepts an optional second parameter to indicate whether the holder type uses intrusive reference counting. `#533 `_ and `#561 `_. * Mapping a stateless C++ function to Python and back is now "for free" (i.e. no extra indirections or argument conversion overheads). `rev. 954b79 `_. * Bindings for ``std::valarray``. `#545 `_. * Improved support for C++17 capable compilers. `#562 `_. * Bindings for ``std::optional``. `#475 `_, `#476 `_, `#479 `_, `#499 `_, and `#501 `_. * ``stl_bind.h``: general improvements and support for ``std::map`` and ``std::unordered_map``. `#490 `_, `#282 `_, `#235 `_. * The ``std::tuple``, ``std::pair``, ``std::list``, and ``std::vector`` type casters now accept any Python sequence type as input. `rev. 107285 `_. * Improved CMake Python detection on multi-architecture Linux. `#532 `_. * Infrastructure to selectively disable or enable parts of the automatically generated docstrings. `#486 `_. * ``reference`` and ``reference_internal`` are now the default return value properties for static and non-static properties, respectively. `#473 `_. (the previous defaults were ``automatic``). `#473 `_. * Support for ``std::unique_ptr`` with non-default deleters or no deleter at all (``py::nodelete``). `#384 `_. * Deprecated ``handle::call()`` method. The new syntax to call Python functions is simply ``handle()``. It can also be invoked explicitly via ``handle::operator()``, where ``X`` is an optional return value policy. * Print more informative error messages when ``make_tuple()`` or ``cast()`` fail. `#262 `_. * Creation of holder types for classes deriving from ``std::enable_shared_from_this<>`` now also works for ``const`` values. `#260 `_. * ``make_iterator()`` improvements for better compatibility with various types (now uses prefix increment operator); it now also accepts iterators with different begin/end types as long as they are equality comparable. `#247 `_. * ``arg()`` now accepts a wider range of argument types for default values. `#244 `_. * Support ``keep_alive`` where the nurse object may be ``None``. `#341 `_. * Added constructors for ``str`` and ``bytes`` from zero-terminated char pointers, and from char pointers and length. Added constructors for ``str`` from ``bytes`` and for ``bytes`` from ``str``, which will perform UTF-8 decoding/encoding as required. * Many other improvements of library internals without user-visible changes 1.8.1 (July 12, 2016) ---------------------- * Fixed a rare but potentially very severe issue when the garbage collector ran during pybind11 type creation. 1.8.0 (June 14, 2016) ---------------------- * Redesigned CMake build system which exports a convenient ``pybind11_add_module`` function to parent projects. * ``std::vector<>`` type bindings analogous to Boost.Python's ``indexing_suite`` * Transparent conversion of sparse and dense Eigen matrices and vectors (``eigen.h``) * Added an ``ExtraFlags`` template argument to the NumPy ``array_t<>`` wrapper to disable an enforced cast that may lose precision, e.g. to create overloads for different precisions and complex vs real-valued matrices. * Prevent implicit conversion of floating point values to integral types in function arguments * Fixed incorrect default return value policy for functions returning a shared pointer * Don't allow registering a type via ``class_`` twice * Don't allow casting a ``None`` value into a C++ lvalue reference * Fixed a crash in ``enum_::operator==`` that was triggered by the ``help()`` command * Improved detection of whether or not custom C++ types can be copy/move-constructed * Extended ``str`` type to also work with ``bytes`` instances * Added a ``"name"_a`` user defined string literal that is equivalent to ``py::arg("name")``. * When specifying function arguments via ``py::arg``, the test that verifies the number of arguments now runs at compile time. * Added ``[[noreturn]]`` attribute to ``pybind11_fail()`` to quench some compiler warnings * List function arguments in exception text when the dispatch code cannot find a matching overload * Added ``PYBIND11_OVERLOAD_NAME`` and ``PYBIND11_OVERLOAD_PURE_NAME`` macros which can be used to override virtual methods whose name differs in C++ and Python (e.g. ``__call__`` and ``operator()``) * Various minor ``iterator`` and ``make_iterator()`` improvements * Transparently support ``__bool__`` on Python 2.x and Python 3.x * Fixed issue with destructor of unpickled object not being called * Minor CMake build system improvements on Windows * New ``pybind11::args`` and ``pybind11::kwargs`` types to create functions which take an arbitrary number of arguments and keyword arguments * New syntax to call a Python function from C++ using ``*args`` and ``*kwargs`` * The functions ``def_property_*`` now correctly process docstring arguments (these formerly caused a segmentation fault) * Many ``mkdoc.py`` improvements (enumerations, template arguments, ``DOC()`` macro accepts more arguments) * Cygwin support * Documentation improvements (pickling support, ``keep_alive``, macro usage) 1.7 (April 30, 2016) ---------------------- * Added a new ``move`` return value policy that triggers C++11 move semantics. The automatic return value policy falls back to this case whenever a rvalue reference is encountered * Significantly more general GIL state routines that are used instead of Python's troublesome ``PyGILState_Ensure`` and ``PyGILState_Release`` API * Redesign of opaque types that drastically simplifies their usage * Extended ability to pass values of type ``[const] void *`` * ``keep_alive`` fix: don't fail when there is no patient * ``functional.h``: acquire the GIL before calling a Python function * Added Python RAII type wrappers ``none`` and ``iterable`` * Added ``*args`` and ``*kwargs`` pass-through parameters to ``pybind11.get_include()`` function * Iterator improvements and fixes * Documentation on return value policies and opaque types improved 1.6 (April 30, 2016) ---------------------- * Skipped due to upload to PyPI gone wrong and inability to recover (https://github.com/pypa/packaging-problems/issues/74) 1.5 (April 21, 2016) ---------------------- * For polymorphic types, use RTTI to try to return the closest type registered with pybind11 * Pickling support for serializing and unserializing C++ instances to a byte stream in Python * Added a convenience routine ``make_iterator()`` which turns a range indicated by a pair of C++ iterators into a iterable Python object * Added ``len()`` and a variadic ``make_tuple()`` function * Addressed a rare issue that could confuse the current virtual function dispatcher and another that could lead to crashes in multi-threaded applications * Added a ``get_include()`` function to the Python module that returns the path of the directory containing the installed pybind11 header files * Documentation improvements: import issues, symbol visibility, pickling, limitations * Added casting support for ``std::reference_wrapper<>`` 1.4 (April 7, 2016) -------------------------- * Transparent type conversion for ``std::wstring`` and ``wchar_t`` * Allow passing ``nullptr``-valued strings * Transparent passing of ``void *`` pointers using capsules * Transparent support for returning values wrapped in ``std::unique_ptr<>`` * Improved docstring generation for compatibility with Sphinx * Nicer debug error message when default parameter construction fails * Support for "opaque" types that bypass the transparent conversion layer for STL containers * Redesigned type casting interface to avoid ambiguities that could occasionally cause compiler errors * Redesigned property implementation; fixes crashes due to an unfortunate default return value policy * Anaconda package generation support 1.3 (March 8, 2016) -------------------------- * Added support for the Intel C++ compiler (v15+) * Added support for the STL unordered set/map data structures * Added support for the STL linked list data structure * NumPy-style broadcasting support in ``pybind11::vectorize`` * pybind11 now displays more verbose error messages when ``arg::operator=()`` fails * pybind11 internal data structures now live in a version-dependent namespace to avoid ABI issues * Many, many bugfixes involving corner cases and advanced usage 1.2 (February 7, 2016) -------------------------- * Optional: efficient generation of function signatures at compile time using C++14 * Switched to a simpler and more general way of dealing with function default arguments. Unused keyword arguments in function calls are now detected and cause errors as expected * New ``keep_alive`` call policy analogous to Boost.Python's ``with_custodian_and_ward`` * New ``pybind11::base<>`` attribute to indicate a subclass relationship * Improved interface for RAII type wrappers in ``pytypes.h`` * Use RAII type wrappers consistently within pybind11 itself. This fixes various potential refcount leaks when exceptions occur * Added new ``bytes`` RAII type wrapper (maps to ``string`` in Python 2.7) * Made handle and related RAII classes const correct, using them more consistently everywhere now * Got rid of the ugly ``__pybind11__`` attributes on the Python side---they are now stored in a C++ hash table that is not visible in Python * Fixed refcount leaks involving NumPy arrays and bound functions * Vastly improved handling of shared/smart pointers * Removed an unnecessary copy operation in ``pybind11::vectorize`` * Fixed naming clashes when both pybind11 and NumPy headers are included * Added conversions for additional exception types * Documentation improvements (using multiple extension modules, smart pointers, other minor clarifications) * unified infrastructure for parsing variadic arguments in ``class_`` and cpp_function * Fixed license text (was: ZLIB, should have been: 3-clause BSD) * Python 3.2 compatibility * Fixed remaining issues when accessing types in another plugin module * Added enum comparison and casting methods * Improved SFINAE-based detection of whether types are copy-constructible * Eliminated many warnings about unused variables and the use of ``offsetof()`` * Support for ``std::array<>`` conversions 1.1 (December 7, 2015) -------------------------- * Documentation improvements (GIL, wrapping functions, casting, fixed many typos) * Generalized conversion of integer types * Improved support for casting function objects * Improved support for ``std::shared_ptr<>`` conversions * Initial support for ``std::set<>`` conversions * Fixed type resolution issue for types defined in a separate plugin module * CMake build system improvements * Factored out generic functionality to non-templated code (smaller code size) * Added a code size / compile time benchmark vs Boost.Python * Added an appveyor CI script 1.0 (October 15, 2015) ------------------------ * Initial release pybind11-2.13.6/docs/classes.rst000066400000000000000000000413021467115402600163570ustar00rootroot00000000000000.. _classes: Object-oriented code #################### Creating bindings for a custom type =================================== Let's now look at a more complex example where we'll create bindings for a custom C++ data structure named ``Pet``. Its definition is given below: .. code-block:: cpp struct Pet { Pet(const std::string &name) : name(name) { } void setName(const std::string &name_) { name = name_; } const std::string &getName() const { return name; } std::string name; }; The binding code for ``Pet`` looks as follows: .. code-block:: cpp #include namespace py = pybind11; PYBIND11_MODULE(example, m) { py::class_(m, "Pet") .def(py::init()) .def("setName", &Pet::setName) .def("getName", &Pet::getName); } :class:`class_` creates bindings for a C++ *class* or *struct*-style data structure. :func:`init` is a convenience function that takes the types of a constructor's parameters as template arguments and wraps the corresponding constructor (see the :ref:`custom_constructors` section for details). An interactive Python session demonstrating this example is shown below: .. code-block:: pycon % python >>> import example >>> p = example.Pet("Molly") >>> print(p) >>> p.getName() 'Molly' >>> p.setName("Charly") >>> p.getName() 'Charly' .. seealso:: Static member functions can be bound in the same way using :func:`class_::def_static`. .. note:: Binding C++ types in unnamed namespaces (also known as anonymous namespaces) works reliably on many platforms, but not all. The `XFAIL_CONDITION` in tests/test_unnamed_namespace_a.py encodes the currently known conditions. For background see `#4319 `_. If portability is a concern, it is therefore not recommended to bind C++ types in unnamed namespaces. It will be safest to manually pick unique namespace names. Keyword and default arguments ============================= It is possible to specify keyword and default arguments using the syntax discussed in the previous chapter. Refer to the sections :ref:`keyword_args` and :ref:`default_args` for details. Binding lambda functions ======================== Note how ``print(p)`` produced a rather useless summary of our data structure in the example above: .. code-block:: pycon >>> print(p) To address this, we could bind a utility function that returns a human-readable summary to the special method slot named ``__repr__``. Unfortunately, there is no suitable functionality in the ``Pet`` data structure, and it would be nice if we did not have to change it. This can easily be accomplished by binding a Lambda function instead: .. code-block:: cpp py::class_(m, "Pet") .def(py::init()) .def("setName", &Pet::setName) .def("getName", &Pet::getName) .def("__repr__", [](const Pet &a) { return ""; } ); Both stateless [#f1]_ and stateful lambda closures are supported by pybind11. With the above change, the same Python code now produces the following output: .. code-block:: pycon >>> print(p) .. [#f1] Stateless closures are those with an empty pair of brackets ``[]`` as the capture object. .. _properties: Instance and static fields ========================== We can also directly expose the ``name`` field using the :func:`class_::def_readwrite` method. A similar :func:`class_::def_readonly` method also exists for ``const`` fields. .. code-block:: cpp py::class_(m, "Pet") .def(py::init()) .def_readwrite("name", &Pet::name) // ... remainder ... This makes it possible to write .. code-block:: pycon >>> p = example.Pet("Molly") >>> p.name 'Molly' >>> p.name = "Charly" >>> p.name 'Charly' Now suppose that ``Pet::name`` was a private internal variable that can only be accessed via setters and getters. .. code-block:: cpp class Pet { public: Pet(const std::string &name) : name(name) { } void setName(const std::string &name_) { name = name_; } const std::string &getName() const { return name; } private: std::string name; }; In this case, the method :func:`class_::def_property` (:func:`class_::def_property_readonly` for read-only data) can be used to provide a field-like interface within Python that will transparently call the setter and getter functions: .. code-block:: cpp py::class_(m, "Pet") .def(py::init()) .def_property("name", &Pet::getName, &Pet::setName) // ... remainder ... Write only properties can be defined by passing ``nullptr`` as the input for the read function. .. seealso:: Similar functions :func:`class_::def_readwrite_static`, :func:`class_::def_readonly_static` :func:`class_::def_property_static`, and :func:`class_::def_property_readonly_static` are provided for binding static variables and properties. Please also see the section on :ref:`static_properties` in the advanced part of the documentation. Dynamic attributes ================== Native Python classes can pick up new attributes dynamically: .. code-block:: pycon >>> class Pet: ... name = "Molly" ... >>> p = Pet() >>> p.name = "Charly" # overwrite existing >>> p.age = 2 # dynamically add a new attribute By default, classes exported from C++ do not support this and the only writable attributes are the ones explicitly defined using :func:`class_::def_readwrite` or :func:`class_::def_property`. .. code-block:: cpp py::class_(m, "Pet") .def(py::init<>()) .def_readwrite("name", &Pet::name); Trying to set any other attribute results in an error: .. code-block:: pycon >>> p = example.Pet() >>> p.name = "Charly" # OK, attribute defined in C++ >>> p.age = 2 # fail AttributeError: 'Pet' object has no attribute 'age' To enable dynamic attributes for C++ classes, the :class:`py::dynamic_attr` tag must be added to the :class:`py::class_` constructor: .. code-block:: cpp py::class_(m, "Pet", py::dynamic_attr()) .def(py::init<>()) .def_readwrite("name", &Pet::name); Now everything works as expected: .. code-block:: pycon >>> p = example.Pet() >>> p.name = "Charly" # OK, overwrite value in C++ >>> p.age = 2 # OK, dynamically add a new attribute >>> p.__dict__ # just like a native Python class {'age': 2} Note that there is a small runtime cost for a class with dynamic attributes. Not only because of the addition of a ``__dict__``, but also because of more expensive garbage collection tracking which must be activated to resolve possible circular references. Native Python classes incur this same cost by default, so this is not anything to worry about. By default, pybind11 classes are more efficient than native Python classes. Enabling dynamic attributes just brings them on par. .. _inheritance: Inheritance and automatic downcasting ===================================== Suppose now that the example consists of two data structures with an inheritance relationship: .. code-block:: cpp struct Pet { Pet(const std::string &name) : name(name) { } std::string name; }; struct Dog : Pet { Dog(const std::string &name) : Pet(name) { } std::string bark() const { return "woof!"; } }; There are two different ways of indicating a hierarchical relationship to pybind11: the first specifies the C++ base class as an extra template parameter of the :class:`class_`: .. code-block:: cpp py::class_(m, "Pet") .def(py::init()) .def_readwrite("name", &Pet::name); // Method 1: template parameter: py::class_(m, "Dog") .def(py::init()) .def("bark", &Dog::bark); Alternatively, we can also assign a name to the previously bound ``Pet`` :class:`class_` object and reference it when binding the ``Dog`` class: .. code-block:: cpp py::class_ pet(m, "Pet"); pet.def(py::init()) .def_readwrite("name", &Pet::name); // Method 2: pass parent class_ object: py::class_(m, "Dog", pet /* <- specify Python parent type */) .def(py::init()) .def("bark", &Dog::bark); Functionality-wise, both approaches are equivalent. Afterwards, instances will expose fields and methods of both types: .. code-block:: pycon >>> p = example.Dog("Molly") >>> p.name 'Molly' >>> p.bark() 'woof!' The C++ classes defined above are regular non-polymorphic types with an inheritance relationship. This is reflected in Python: .. code-block:: cpp // Return a base pointer to a derived instance m.def("pet_store", []() { return std::unique_ptr(new Dog("Molly")); }); .. code-block:: pycon >>> p = example.pet_store() >>> type(p) # `Dog` instance behind `Pet` pointer Pet # no pointer downcasting for regular non-polymorphic types >>> p.bark() AttributeError: 'Pet' object has no attribute 'bark' The function returned a ``Dog`` instance, but because it's a non-polymorphic type behind a base pointer, Python only sees a ``Pet``. In C++, a type is only considered polymorphic if it has at least one virtual function and pybind11 will automatically recognize this: .. code-block:: cpp struct PolymorphicPet { virtual ~PolymorphicPet() = default; }; struct PolymorphicDog : PolymorphicPet { std::string bark() const { return "woof!"; } }; // Same binding code py::class_(m, "PolymorphicPet"); py::class_(m, "PolymorphicDog") .def(py::init<>()) .def("bark", &PolymorphicDog::bark); // Again, return a base pointer to a derived instance m.def("pet_store2", []() { return std::unique_ptr(new PolymorphicDog); }); .. code-block:: pycon >>> p = example.pet_store2() >>> type(p) PolymorphicDog # automatically downcast >>> p.bark() 'woof!' Given a pointer to a polymorphic base, pybind11 performs automatic downcasting to the actual derived type. Note that this goes beyond the usual situation in C++: we don't just get access to the virtual functions of the base, we get the concrete derived type including functions and attributes that the base type may not even be aware of. .. seealso:: For more information about polymorphic behavior see :ref:`overriding_virtuals`. Overloaded methods ================== Sometimes there are several overloaded C++ methods with the same name taking different kinds of input arguments: .. code-block:: cpp struct Pet { Pet(const std::string &name, int age) : name(name), age(age) { } void set(int age_) { age = age_; } void set(const std::string &name_) { name = name_; } std::string name; int age; }; Attempting to bind ``Pet::set`` will cause an error since the compiler does not know which method the user intended to select. We can disambiguate by casting them to function pointers. Binding multiple functions to the same Python name automatically creates a chain of function overloads that will be tried in sequence. .. code-block:: cpp py::class_(m, "Pet") .def(py::init()) .def("set", static_cast(&Pet::set), "Set the pet's age") .def("set", static_cast(&Pet::set), "Set the pet's name"); The overload signatures are also visible in the method's docstring: .. code-block:: pycon >>> help(example.Pet) class Pet(__builtin__.object) | Methods defined here: | | __init__(...) | Signature : (Pet, str, int) -> NoneType | | set(...) | 1. Signature : (Pet, int) -> NoneType | | Set the pet's age | | 2. Signature : (Pet, str) -> NoneType | | Set the pet's name If you have a C++14 compatible compiler [#cpp14]_, you can use an alternative syntax to cast the overloaded function: .. code-block:: cpp py::class_(m, "Pet") .def("set", py::overload_cast(&Pet::set), "Set the pet's age") .def("set", py::overload_cast(&Pet::set), "Set the pet's name"); Here, ``py::overload_cast`` only requires the parameter types to be specified. The return type and class are deduced. This avoids the additional noise of ``void (Pet::*)()`` as seen in the raw cast. If a function is overloaded based on constness, the ``py::const_`` tag should be used: .. code-block:: cpp struct Widget { int foo(int x, float y); int foo(int x, float y) const; }; py::class_(m, "Widget") .def("foo_mutable", py::overload_cast(&Widget::foo)) .def("foo_const", py::overload_cast(&Widget::foo, py::const_)); If you prefer the ``py::overload_cast`` syntax but have a C++11 compatible compiler only, you can use ``py::detail::overload_cast_impl`` with an additional set of parentheses: .. code-block:: cpp template using overload_cast_ = pybind11::detail::overload_cast_impl; py::class_(m, "Pet") .def("set", overload_cast_()(&Pet::set), "Set the pet's age") .def("set", overload_cast_()(&Pet::set), "Set the pet's name"); .. [#cpp14] A compiler which supports the ``-std=c++14`` flag. .. note:: To define multiple overloaded constructors, simply declare one after the other using the ``.def(py::init<...>())`` syntax. The existing machinery for specifying keyword and default arguments also works. Enumerations and internal types =============================== Let's now suppose that the example class contains internal types like enumerations, e.g.: .. code-block:: cpp struct Pet { enum Kind { Dog = 0, Cat }; struct Attributes { float age = 0; }; Pet(const std::string &name, Kind type) : name(name), type(type) { } std::string name; Kind type; Attributes attr; }; The binding code for this example looks as follows: .. code-block:: cpp py::class_ pet(m, "Pet"); pet.def(py::init()) .def_readwrite("name", &Pet::name) .def_readwrite("type", &Pet::type) .def_readwrite("attr", &Pet::attr); py::enum_(pet, "Kind") .value("Dog", Pet::Kind::Dog) .value("Cat", Pet::Kind::Cat) .export_values(); py::class_(pet, "Attributes") .def(py::init<>()) .def_readwrite("age", &Pet::Attributes::age); To ensure that the nested types ``Kind`` and ``Attributes`` are created within the scope of ``Pet``, the ``pet`` :class:`class_` instance must be supplied to the :class:`enum_` and :class:`class_` constructor. The :func:`enum_::export_values` function exports the enum entries into the parent scope, which should be skipped for newer C++11-style strongly typed enums. .. code-block:: pycon >>> p = Pet("Lucy", Pet.Cat) >>> p.type Kind.Cat >>> int(p.type) 1L The entries defined by the enumeration type are exposed in the ``__members__`` property: .. code-block:: pycon >>> Pet.Kind.__members__ {'Dog': Kind.Dog, 'Cat': Kind.Cat} The ``name`` property returns the name of the enum value as a unicode string. .. note:: It is also possible to use ``str(enum)``, however these accomplish different goals. The following shows how these two approaches differ. .. code-block:: pycon >>> p = Pet("Lucy", Pet.Cat) >>> pet_type = p.type >>> pet_type Pet.Cat >>> str(pet_type) 'Pet.Cat' >>> pet_type.name 'Cat' .. note:: When the special tag ``py::arithmetic()`` is specified to the ``enum_`` constructor, pybind11 creates an enumeration that also supports rudimentary arithmetic and bit-level operations like comparisons, and, or, xor, negation, etc. .. code-block:: cpp py::enum_(pet, "Kind", py::arithmetic()) ... By default, these are omitted to conserve space. .. warning:: Contrary to Python customs, enum values from the wrappers should not be compared using ``is``, but with ``==`` (see `#1177 `_ for background). pybind11-2.13.6/docs/cmake/000077500000000000000000000000001467115402600152505ustar00rootroot00000000000000pybind11-2.13.6/docs/cmake/index.rst000066400000000000000000000004211467115402600171060ustar00rootroot00000000000000CMake helpers ------------- Pybind11 can be used with ``add_subdirectory(extern/pybind11)``, or from an install with ``find_package(pybind11 CONFIG)``. The interface provided in either case is functionally identical. .. cmake-module:: ../../tools/pybind11Config.cmake.in pybind11-2.13.6/docs/compiling.rst000066400000000000000000000674461467115402600167240ustar00rootroot00000000000000.. _compiling: Build systems ############# For an overview of Python packaging including compiled packaging with a pybind11 example, along with a cookiecutter that includes several pybind11 options, see the `Scientific Python Development Guide`_. .. _Scientific Python Development Guide: https://learn.scientific-python.org/development/guides/packaging-compiled/ .. scikit-build-core: Modules with CMake ================== A Python extension module can be created with just a few lines of code: .. code-block:: cmake cmake_minimum_required(VERSION 3.15...3.29) project(example LANGUAGES CXX) set(PYBIND11_FINDPYTHON ON) find_package(pybind11 CONFIG REQUIRED) pybind11_add_module(example example.cpp) install(TARGETS example DESTINATION .) (You use the ``add_subdirectory`` instead, see the example in :ref:`cmake`.) In this example, the code is located in a file named :file:`example.cpp`. Either method will import the pybind11 project which provides the ``pybind11_add_module`` function. It will take care of all the details needed to build a Python extension module on any platform. To build with pip, build, cibuildwheel, uv, or other Python tools, you can add a ``pyproject.toml`` file like this: .. code-block:: toml [build-system] requires = ["scikit-build-core", "pybind11"] build-backend = "scikit_build_core.build" [project] name = "example" version = "0.1.0" You don't need setuptools files like ``MANIFEST.in``, ``setup.py``, or ``setup.cfg``, as this is not setuptools. See `scikit-build-core`_ for details. For projects you plan to upload to PyPI, be sure to fill out the ``[project]`` table with other important metadata as well (see `Writing pyproject.toml`_). A working sample project can be found in the [scikit_build_example]_ repository. An older and harder-to-maintain method is in [cmake_example]_. More details about our cmake support can be found below in :ref:`cmake`. .. _scikit-build-core: https://scikit-build-core.readthedocs.io .. [scikit_build_example] https://github.com/pybind/scikit_build_example .. [cmake_example] https://github.com/pybind/cmake_example .. _modules-meson-python: Modules with meson-python ========================= You can also build a package with `Meson`_ using `meson-python`_, if you prefer that. Your ``meson.build`` file would look something like this: .. _meson-example: .. code-block:: meson project( 'example', 'cpp', version: '0.1.0', default_options: [ 'cpp_std=c++11', ], ) py = import('python').find_installation(pure: false) pybind11_dep = dependency('pybind11') py.extension_module('example', 'example.cpp', install: true, dependencies : [pybind11_dep], ) And you would need a ``pyproject.toml`` file like this: .. code-block:: toml [build-system] requires = ["meson-python", "pybind11"] build-backend = "mesonpy" Meson-python *requires* your project to be in git (or mercurial) as it uses it for the SDist creation. For projects you plan to upload to PyPI, be sure to fill out the ``[project]`` table as well (see `Writing pyproject.toml`_). .. _Writing pyproject.toml: https://packaging.python.org/en/latest/guides/writing-pyproject-toml .. _meson: https://mesonbuild.com .. _meson-python: https://meson-python.readthedocs.io/en/latest .. _build-setuptools: Modules with setuptools ======================= For projects on PyPI, a historically popular option is setuptools. Sylvain Corlay has kindly provided an example project which shows how to set up everything, including automatic generation of documentation using Sphinx. Please refer to the [python_example]_ repository. .. [python_example] https://github.com/pybind/python_example A helper file is provided with pybind11 that can simplify usage with setuptools. To use pybind11 inside your ``setup.py``, you have to have some system to ensure that ``pybind11`` is installed when you build your package. There are four possible ways to do this, and pybind11 supports all four: You can ask all users to install pybind11 beforehand (bad), you can use :ref:`setup_helpers-pep518` (good), ``setup_requires=`` (discouraged), or you can :ref:`setup_helpers-copy-manually` (works but you have to manually sync your copy to get updates). Third party packagers like conda-forge generally strongly prefer the ``pyproject.toml`` method, as it gives them control over the ``pybind11`` version, and they may apply patches, etc. An example of a ``setup.py`` using pybind11's helpers: .. code-block:: python from glob import glob from setuptools import setup from pybind11.setup_helpers import Pybind11Extension ext_modules = [ Pybind11Extension( "python_example", sorted(glob("src/*.cpp")), # Sort source files for reproducibility ), ] setup(..., ext_modules=ext_modules) If you want to do an automatic search for the highest supported C++ standard, that is supported via a ``build_ext`` command override; it will only affect ``Pybind11Extensions``: .. code-block:: python from glob import glob from setuptools import setup from pybind11.setup_helpers import Pybind11Extension, build_ext ext_modules = [ Pybind11Extension( "python_example", sorted(glob("src/*.cpp")), ), ] setup(..., cmdclass={"build_ext": build_ext}, ext_modules=ext_modules) If you have single-file extension modules that are directly stored in the Python source tree (``foo.cpp`` in the same directory as where a ``foo.py`` would be located), you can also generate ``Pybind11Extensions`` using ``setup_helpers.intree_extensions``: ``intree_extensions(["path/to/foo.cpp", ...])`` returns a list of ``Pybind11Extensions`` which can be passed to ``ext_modules``, possibly after further customizing their attributes (``libraries``, ``include_dirs``, etc.). By doing so, a ``foo.*.so`` extension module will be generated and made available upon installation. ``intree_extension`` will automatically detect if you are using a ``src``-style layout (as long as no namespace packages are involved), but you can also explicitly pass ``package_dir`` to it (as in ``setuptools.setup``). Since pybind11 does not require NumPy when building, a light-weight replacement for NumPy's parallel compilation distutils tool is included. Use it like this: .. code-block:: python from pybind11.setup_helpers import ParallelCompile # Optional multithreaded build ParallelCompile("NPY_NUM_BUILD_JOBS").install() setup(...) The argument is the name of an environment variable to control the number of threads, such as ``NPY_NUM_BUILD_JOBS`` (as used by NumPy), though you can set something different if you want; ``CMAKE_BUILD_PARALLEL_LEVEL`` is another choice a user might expect. You can also pass ``default=N`` to set the default number of threads (0 will take the number of threads available) and ``max=N``, the maximum number of threads; if you have a large extension you may want set this to a memory dependent number. If you are developing rapidly and have a lot of C++ files, you may want to avoid rebuilding files that have not changed. For simple cases were you are using ``pip install -e .`` and do not have local headers, you can skip the rebuild if an object file is newer than its source (headers are not checked!) with the following: .. code-block:: python from pybind11.setup_helpers import ParallelCompile, naive_recompile ParallelCompile("NPY_NUM_BUILD_JOBS", needs_recompile=naive_recompile).install() If you have a more complex build, you can implement a smarter function and pass it to ``needs_recompile``, or you can use [Ccache]_ instead. ``CXX="cache g++" pip install -e .`` would be the way to use it with GCC, for example. Unlike the simple solution, this even works even when not compiling in editable mode, but it does require Ccache to be installed. Keep in mind that Pip will not even attempt to rebuild if it thinks it has already built a copy of your code, which it deduces from the version number. One way to avoid this is to use [setuptools_scm]_, which will generate a version number that includes the number of commits since your last tag and a hash for a dirty directory. Another way to force a rebuild is purge your cache or use Pip's ``--no-cache-dir`` option. You also need a ``MANIFEST.in`` file to include all relevant files so that you can make an SDist. If you use `pypa-build`_, that will build an SDist then a wheel from that SDist by default, so you can look inside those files (wheels are just zip files with a ``.whl`` extension) to make sure you aren't missing files. `check-manifest`_ (setuptools specific) or `check-sdist`_ (general) are CLI tools that can compare the SDist contents with your source control. .. [Ccache] https://ccache.dev .. [setuptools_scm] https://github.com/pypa/setuptools_scm .. _setup_helpers-pep518: Build requirements ------------------ With a ``pyproject.toml`` file, you can ensure that ``pybind11`` is available during the compilation of your project. When this file exists, Pip will make a new virtual environment, download just the packages listed here in ``requires=``, and build a wheel (binary Python package). It will then throw away the environment, and install your wheel. Your ``pyproject.toml`` file will likely look something like this: .. code-block:: toml [build-system] requires = ["setuptools", "pybind11"] build-backend = "setuptools.build_meta" .. _PEP 517: https://www.python.org/dev/peps/pep-0517/ .. _cibuildwheel: https://cibuildwheel.pypa.io .. _pypa-build: https://build.pypa.io/en/latest/ .. _check-manifest: https://pypi.io/project/check-manifest .. _check-sdist: https://pypi.io/project/check-sdist .. _setup_helpers-copy-manually: Copy manually ------------- You can also copy ``setup_helpers.py`` directly to your project; it was designed to be usable standalone, like the old example ``setup.py``. You can set ``include_pybind11=False`` to skip including the pybind11 package headers, so you can use it with git submodules and a specific git version. If you use this, you will need to import from a local file in ``setup.py`` and ensure the helper file is part of your MANIFEST. Closely related, if you include pybind11 as a subproject, you can run the ``setup_helpers.py`` inplace. If loaded correctly, this should even pick up the correct include for pybind11, though you can turn it off as shown above if you want to input it manually. Suggested usage if you have pybind11 as a submodule in ``extern/pybind11``: .. code-block:: python DIR = os.path.abspath(os.path.dirname(__file__)) sys.path.append(os.path.join(DIR, "extern", "pybind11")) from pybind11.setup_helpers import Pybind11Extension # noqa: E402 del sys.path[-1] .. versionchanged:: 2.6 Added ``setup_helpers`` file. Building with cppimport ======================== [cppimport]_ is a small Python import hook that determines whether there is a C++ source file whose name matches the requested module. If there is, the file is compiled as a Python extension using pybind11 and placed in the same folder as the C++ source file. Python is then able to find the module and load it. .. [cppimport] https://github.com/tbenthompson/cppimport .. _cmake: Building with CMake =================== For C++ codebases that have an existing CMake-based build system, a Python extension module can be created with just a few lines of code, as seen above in the module section. Pybind11 currently supports a lower minimum if you don't use the modern FindPython, though be aware that CMake 3.27 removed the old mechanism, so pybind11 will automatically switch if the old mechanism is not available. Please opt into the new mechanism if at all possible. Our default may change in future versions. This is the minimum required: .. versionchanged:: 2.6 CMake 3.4+ is required. .. versionchanged:: 2.11 CMake 3.5+ is required. Further information can be found at :doc:`cmake/index`. pybind11_add_module ------------------- To ease the creation of Python extension modules, pybind11 provides a CMake function with the following signature: .. code-block:: cmake pybind11_add_module( [MODULE | SHARED] [EXCLUDE_FROM_ALL] [NO_EXTRAS] [THIN_LTO] [OPT_SIZE] source1 [source2 ...]) This function behaves very much like CMake's builtin ``add_library`` (in fact, it's a wrapper function around that command). It will add a library target called ```` to be built from the listed source files. In addition, it will take care of all the Python-specific compiler and linker flags as well as the OS- and Python-version-specific file extension. The produced target ```` can be further manipulated with regular CMake commands. ``MODULE`` or ``SHARED`` may be given to specify the type of library. If no type is given, ``MODULE`` is used by default which ensures the creation of a Python-exclusive module. Specifying ``SHARED`` will create a more traditional dynamic library which can also be linked from elsewhere. ``EXCLUDE_FROM_ALL`` removes this target from the default build (see CMake docs for details). Since pybind11 is a template library, ``pybind11_add_module`` adds compiler flags to ensure high quality code generation without bloat arising from long symbol names and duplication of code in different translation units. It sets default visibility to *hidden*, which is required for some pybind11 features and functionality when attempting to load multiple pybind11 modules compiled under different pybind11 versions. It also adds additional flags enabling LTO (Link Time Optimization) and strip unneeded symbols. See the :ref:`FAQ entry ` for a more detailed explanation. These latter optimizations are never applied in ``Debug`` mode. If ``NO_EXTRAS`` is given, they will always be disabled, even in ``Release`` mode. However, this will result in code bloat and is generally not recommended. As stated above, LTO is enabled by default. Some newer compilers also support different flavors of LTO such as `ThinLTO`_. Setting ``THIN_LTO`` will cause the function to prefer this flavor if available. The function falls back to regular LTO if ``-flto=thin`` is not available. If ``CMAKE_INTERPROCEDURAL_OPTIMIZATION`` is set (either ``ON`` or ``OFF``), then that will be respected instead of the built-in flag search. .. note:: If you want to set the property form on targets or the ``CMAKE_INTERPROCEDURAL_OPTIMIZATION_`` versions of this, you should still use ``set(CMAKE_INTERPROCEDURAL_OPTIMIZATION OFF)`` (otherwise a no-op) to disable pybind11's ipo flags. The ``OPT_SIZE`` flag enables size-based optimization equivalent to the standard ``/Os`` or ``-Os`` compiler flags and the ``MinSizeRel`` build type, which avoid optimizations that can substantially increase the size of the resulting binary. This flag is particularly useful in projects that are split into performance-critical parts and associated bindings. In this case, we can compile the project in release mode (and hence, optimize performance globally), and specify ``OPT_SIZE`` for the binding target, where size might be the main concern as performance is often less critical here. A ~25% size reduction has been observed in practice. This flag only changes the optimization behavior at a per-target level and takes precedence over the global CMake build type (``Release``, ``RelWithDebInfo``) except for ``Debug`` builds, where optimizations remain disabled. .. _ThinLTO: http://clang.llvm.org/docs/ThinLTO.html Configuration variables ----------------------- By default, pybind11 will compile modules with the compiler default or the minimum standard required by pybind11, whichever is higher. You can set the standard explicitly with `CMAKE_CXX_STANDARD `_: .. code-block:: cmake set(CMAKE_CXX_STANDARD 14 CACHE STRING "C++ version selection") # or 11, 14, 17, 20 set(CMAKE_CXX_STANDARD_REQUIRED ON) # optional, ensure standard is supported set(CMAKE_CXX_EXTENSIONS OFF) # optional, keep compiler extensions off The variables can also be set when calling CMake from the command line using the ``-D=`` flag. You can also manually set ``CXX_STANDARD`` on a target or use ``target_compile_features`` on your targets - anything that CMake supports. Classic Python support: The target Python version can be selected by setting ``PYBIND11_PYTHON_VERSION`` or an exact Python installation can be specified with ``PYTHON_EXECUTABLE``. For example: .. code-block:: bash cmake -DPYBIND11_PYTHON_VERSION=3.7 .. # Another method: cmake -DPYTHON_EXECUTABLE=/path/to/python .. # This often is a good way to get the current Python, works in environments: cmake -DPYTHON_EXECUTABLE=$(python3 -c "import sys; print(sys.executable)") .. find_package vs. add_subdirectory --------------------------------- For CMake-based projects that don't include the pybind11 repository internally, an external installation can be detected through ``find_package(pybind11)``. See the `Config file`_ docstring for details of relevant CMake variables. .. code-block:: cmake cmake_minimum_required(VERSION 3.4...3.18) project(example LANGUAGES CXX) find_package(pybind11 REQUIRED) pybind11_add_module(example example.cpp) Note that ``find_package(pybind11)`` will only work correctly if pybind11 has been correctly installed on the system, e. g. after downloading or cloning the pybind11 repository : .. code-block:: bash # Classic CMake cd pybind11 mkdir build cd build cmake .. make install # CMake 3.15+ cd pybind11 cmake -S . -B build cmake --build build -j 2 # Build on 2 cores cmake --install build Once detected, the aforementioned ``pybind11_add_module`` can be employed as before. The function usage and configuration variables are identical no matter if pybind11 is added as a subdirectory or found as an installed package. You can refer to the same [cmake_example]_ repository for a full sample project -- just swap out ``add_subdirectory`` for ``find_package``. .. _Config file: https://github.com/pybind/pybind11/blob/master/tools/pybind11Config.cmake.in .. _find-python-mode: FindPython mode --------------- CMake 3.12+ (3.15+ recommended, 3.18.2+ ideal) added a new module called FindPython that had a highly improved search algorithm and modern targets and tools. If you use FindPython, pybind11 will detect this and use the existing targets instead: .. code-block:: cmake cmake_minimum_required(VERSION 3.15...3.22) project(example LANGUAGES CXX) find_package(Python 3.7 COMPONENTS Interpreter Development REQUIRED) find_package(pybind11 CONFIG REQUIRED) # or add_subdirectory(pybind11) pybind11_add_module(example example.cpp) You can also use the targets (as listed below) with FindPython. If you define ``PYBIND11_FINDPYTHON``, pybind11 will perform the FindPython step for you (mostly useful when building pybind11's own tests, or as a way to change search algorithms from the CMake invocation, with ``-DPYBIND11_FINDPYTHON=ON``. .. warning:: If you use FindPython to multi-target Python versions, use the individual targets listed below, and avoid targets that directly include Python parts. There are `many ways to hint or force a discovery of a specific Python installation `_), setting ``Python_ROOT_DIR`` may be the most common one (though with virtualenv/venv support, and Conda support, this tends to find the correct Python version more often than the old system did). .. warning:: When the Python libraries (i.e. ``libpythonXX.a`` and ``libpythonXX.so`` on Unix) are not available, as is the case on a manylinux image, the ``Development`` component will not be resolved by ``FindPython``. When not using the embedding functionality, CMake 3.18+ allows you to specify ``Development.Module`` instead of ``Development`` to resolve this issue. .. versionadded:: 2.6 Advanced: interface library targets ----------------------------------- Pybind11 supports modern CMake usage patterns with a set of interface targets, available in all modes. The targets provided are: ``pybind11::headers`` Just the pybind11 headers and minimum compile requirements ``pybind11::pybind11`` Python headers + ``pybind11::headers`` ``pybind11::python_link_helper`` Just the "linking" part of pybind11:module ``pybind11::module`` Everything for extension modules - ``pybind11::pybind11`` + ``Python::Module`` (FindPython CMake 3.15+) or ``pybind11::python_link_helper`` ``pybind11::embed`` Everything for embedding the Python interpreter - ``pybind11::pybind11`` + ``Python::Python`` (FindPython) or Python libs ``pybind11::lto`` / ``pybind11::thin_lto`` An alternative to `INTERPROCEDURAL_OPTIMIZATION` for adding link-time optimization. ``pybind11::windows_extras`` ``/bigobj`` and ``/mp`` for MSVC. ``pybind11::opt_size`` ``/Os`` for MSVC, ``-Os`` for other compilers. Does nothing for debug builds. Two helper functions are also provided: ``pybind11_strip(target)`` Strips a target (uses ``CMAKE_STRIP`` after the target is built) ``pybind11_extension(target)`` Sets the correct extension (with SOABI) for a target. You can use these targets to build complex applications. For example, the ``add_python_module`` function is identical to: .. code-block:: cmake cmake_minimum_required(VERSION 3.5...3.29) project(example LANGUAGES CXX) find_package(pybind11 REQUIRED) # or add_subdirectory(pybind11) add_library(example MODULE main.cpp) target_link_libraries(example PRIVATE pybind11::module pybind11::lto pybind11::windows_extras) pybind11_extension(example) if(NOT MSVC AND NOT ${CMAKE_BUILD_TYPE} MATCHES Debug|RelWithDebInfo) # Strip unnecessary sections of the binary on Linux/macOS pybind11_strip(example) endif() set_target_properties(example PROPERTIES CXX_VISIBILITY_PRESET "hidden" CUDA_VISIBILITY_PRESET "hidden") Instead of setting properties, you can set ``CMAKE_*`` variables to initialize these correctly. .. warning:: Since pybind11 is a metatemplate library, it is crucial that certain compiler flags are provided to ensure high quality code generation. In contrast to the ``pybind11_add_module()`` command, the CMake interface provides a *composable* set of targets to ensure that you retain flexibility. It can be especially important to provide or set these properties; the :ref:`FAQ ` contains an explanation on why these are needed. .. versionadded:: 2.6 .. _nopython-mode: Advanced: NOPYTHON mode ----------------------- If you want complete control, you can set ``PYBIND11_NOPYTHON`` to completely disable Python integration (this also happens if you run ``FindPython2`` and ``FindPython3`` without running ``FindPython``). This gives you complete freedom to integrate into an existing system (like `Scikit-Build's `_ ``PythonExtensions``). ``pybind11_add_module`` and ``pybind11_extension`` will be unavailable, and the targets will be missing any Python specific behavior. .. versionadded:: 2.6 Embedding the Python interpreter -------------------------------- In addition to extension modules, pybind11 also supports embedding Python into a C++ executable or library. In CMake, simply link with the ``pybind11::embed`` target. It provides everything needed to get the interpreter running. The Python headers and libraries are attached to the target. Unlike ``pybind11::module``, there is no need to manually set any additional properties here. For more information about usage in C++, see :doc:`/advanced/embedding`. .. code-block:: cmake cmake_minimum_required(VERSION 3.5...3.29) project(example LANGUAGES CXX) find_package(pybind11 REQUIRED) # or add_subdirectory(pybind11) add_executable(example main.cpp) target_link_libraries(example PRIVATE pybind11::embed) .. _building_manually: Building manually ================= pybind11 is a header-only library, hence it is not necessary to link against any special libraries and there are no intermediate (magic) translation steps. On Linux, you can compile an example such as the one given in :ref:`simple_example` using the following command: .. code-block:: bash $ c++ -O3 -Wall -shared -std=c++11 -fPIC $(python3 -m pybind11 --includes) example.cpp -o example$(python3-config --extension-suffix) The ``python3 -m pybind11 --includes`` command fetches the include paths for both pybind11 and Python headers. This assumes that pybind11 has been installed using ``pip`` or ``conda``. If it hasn't, you can also manually specify ``-I /include`` together with the Python includes path ``python3-config --includes``. On macOS: the build command is almost the same but it also requires passing the ``-undefined dynamic_lookup`` flag so as to ignore missing symbols when building the module: .. code-block:: bash $ c++ -O3 -Wall -shared -std=c++11 -undefined dynamic_lookup $(python3 -m pybind11 --includes) example.cpp -o example$(python3-config --extension-suffix) In general, it is advisable to include several additional build parameters that can considerably reduce the size of the created binary. Refer to section :ref:`cmake` for a detailed example of a suitable cross-platform CMake-based build system that works on all platforms including Windows. .. note:: On Linux and macOS, it's better to (intentionally) not link against ``libpython``. The symbols will be resolved when the extension library is loaded into a Python binary. This is preferable because you might have several different installations of a given Python version (e.g. the system-provided Python, and one that ships with a piece of commercial software). In this way, the plugin will work with both versions, instead of possibly importing a second Python library into a process that already contains one (which will lead to a segfault). Building with Bazel =================== You can build with the Bazel build system using the `pybind11_bazel `_ repository. Building with Meson =================== You can use Meson, which has support for ``pybind11`` as a dependency (internally relying on our ``pkg-config`` support). See the :ref:`module example above `. Generating binding code automatically ===================================== The ``Binder`` project is a tool for automatic generation of pybind11 binding code by introspecting existing C++ codebases using LLVM/Clang. See the [binder]_ documentation for details. .. [binder] http://cppbinder.readthedocs.io/en/latest/about.html [AutoWIG]_ is a Python library that wraps automatically compiled libraries into high-level languages. It parses C++ code using LLVM/Clang technologies and generates the wrappers using the Mako templating engine. The approach is automatic, extensible, and applies to very complex C++ libraries, composed of thousands of classes or incorporating modern meta-programming constructs. .. [AutoWIG] https://github.com/StatisKit/AutoWIG [robotpy-build]_ is a is a pure python, cross platform build tool that aims to simplify creation of python wheels for pybind11 projects, and provide cross-project dependency management. Additionally, it is able to autogenerate customizable pybind11-based wrappers by parsing C++ header files. .. [robotpy-build] https://robotpy-build.readthedocs.io [litgen]_ is an automatic python bindings generator with a focus on generating documented and discoverable bindings: bindings will nicely reproduce the documentation found in headers. It is based on srcML (srcml.org), a highly scalable, multi-language parsing tool with a developer centric approach. The API that you want to expose to python must be C++14 compatible (but your implementation can use more modern constructs). .. [litgen] https://pthom.github.io/litgen pybind11-2.13.6/docs/conf.py000066400000000000000000000265311467115402600154760ustar00rootroot00000000000000#!/usr/bin/env python3 # # pybind11 documentation build configuration file, created by # sphinx-quickstart on Sun Oct 11 19:23:48 2015. # # 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. from __future__ import annotations import os import re import subprocess import sys from pathlib import Path DIR = Path(__file__).parent.resolve() # 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 = [ "breathe", "sphinx_copybutton", "sphinxcontrib.rsvgconverter", "sphinxcontrib.moderncmakedomain", ] breathe_projects = {"pybind11": ".build/doxygenxml/"} breathe_default_project = "pybind11" breathe_domain_by_extension = {"h": "cpp"} # Add any paths that contain templates here, relative to this directory. templates_path = [".templates"] # The suffix(es) of source filenames. # You can specify multiple suffix as a list of string: # source_suffix = ['.rst', '.md'] source_suffix = ".rst" # The encoding of source files. # source_encoding = 'utf-8-sig' # The master toctree document. master_doc = "index" # General information about the project. project = "pybind11" copyright = "2017, Wenzel Jakob" author = "Wenzel Jakob" # 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. # Read the listed version with open("../pybind11/_version.py") as f: code = compile(f.read(), "../pybind11/_version.py", "exec") loc = {} exec(code, loc) # The full version, including alpha/beta/rc tags. version = loc["__version__"] # The language for content autogenerated by Sphinx. Refer to documentation # for a list of supported languages. # # This is also used if you do content translation via gettext catalogs. # Usually you set "language" from the command line for these cases. language = "en" # 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", "release.rst"] # The reST default role (used for this markup: `text`) to use for all # documents. default_role = "any" # 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 = 'monokai' # 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 # If true, `todo` and `todoList` produce output, else they produce nothing. todo_include_todos = 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 = "furo" # 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 = [] # 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"] html_css_files = [ "css/custom.css", ] # 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 # Language to be used for generating the HTML full-text search index. # Sphinx supports the following languages: # 'da', 'de', 'en', 'es', 'fi', 'fr', 'h', 'it', 'ja' # 'nl', 'no', 'pt', 'ro', 'r', 'sv', 'tr' # html_search_language = 'en' # A dictionary with options for the search language support, empty by default. # Now only 'ja' uses this config value # html_search_options = {'type': 'default'} # The name of a javascript file (relative to the configuration directory) that # implements a search results scorer. If empty, the default will be used. # html_search_scorer = 'scorer.js' # Output file base name for HTML help builder. htmlhelp_basename = "pybind11doc" # -- Options for LaTeX output --------------------------------------------- latex_engine = "pdflatex" 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. # remove blank pages (between the title page and the TOC, etc.) "classoptions": ",openany,oneside", "preamble": r""" \usepackage{fontawesome} \usepackage{textgreek} \DeclareUnicodeCharacter{00A0}{} \DeclareUnicodeCharacter{2194}{\faArrowsH} \DeclareUnicodeCharacter{1F382}{\faBirthdayCake} \DeclareUnicodeCharacter{1F355}{\faAdjust} \DeclareUnicodeCharacter{0301}{'} \DeclareUnicodeCharacter{03C0}{\textpi} """, # Latex figure (float) alignment # 'figure_align': 'htbp', } # 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 = [ (master_doc, "pybind11.tex", "pybind11 Documentation", "Wenzel Jakob", "manual"), ] # The name of an image file (relative to this directory) to place at the top of # the title page. # latex_logo = 'pybind11-logo.png' # 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 = [(master_doc, "pybind11", "pybind11 Documentation", [author], 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 = [ ( master_doc, "pybind11", "pybind11 Documentation", author, "pybind11", "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 primary_domain = "cpp" highlight_language = "cpp" def generate_doxygen_xml(app): build_dir = os.path.join(app.confdir, ".build") if not os.path.exists(build_dir): os.mkdir(build_dir) try: subprocess.call(["doxygen", "--version"]) retcode = subprocess.call(["doxygen"], cwd=app.confdir) if retcode < 0: sys.stderr.write(f"doxygen error code: {-retcode}\n") except OSError as e: sys.stderr.write(f"doxygen execution failed: {e}\n") def prepare(app): with open(DIR.parent / "README.rst") as f: contents = f.read() if app.builder.name == "latex": # Remove badges and stuff from start contents = contents[contents.find(r".. start") :] # Filter out section titles for index.rst for LaTeX contents = re.sub(r"^(.*)\n[-~]{3,}$", r"**\1**", contents, flags=re.MULTILINE) with open(DIR / "readme.rst", "w") as f: f.write(contents) def clean_up(app, exception): # noqa: ARG001 (DIR / "readme.rst").unlink() def setup(app): # Add hook for building doxygen xml when needed app.connect("builder-inited", generate_doxygen_xml) # Copy the readme in app.connect("builder-inited", prepare) # Clean up the generated readme app.connect("build-finished", clean_up) pybind11-2.13.6/docs/faq.rst000066400000000000000000000351361467115402600155010ustar00rootroot00000000000000Frequently asked questions ########################## "ImportError: dynamic module does not define init function" =========================================================== 1. Make sure that the name specified in PYBIND11_MODULE is identical to the filename of the extension library (without suffixes such as ``.so``). 2. If the above did not fix the issue, you are likely using an incompatible version of Python that does not match what you compiled with. "Symbol not found: ``__Py_ZeroStruct`` / ``_PyInstanceMethod_Type``" ======================================================================== See the first answer. "SystemError: dynamic module not initialized properly" ====================================================== See the first answer. The Python interpreter immediately crashes when importing my module =================================================================== See the first answer. .. _faq_reference_arguments: Limitations involving reference arguments ========================================= In C++, it's fairly common to pass arguments using mutable references or mutable pointers, which allows both read and write access to the value supplied by the caller. This is sometimes done for efficiency reasons, or to realize functions that have multiple return values. Here are two very basic examples: .. code-block:: cpp void increment(int &i) { i++; } void increment_ptr(int *i) { (*i)++; } In Python, all arguments are passed by reference, so there is no general issue in binding such code from Python. However, certain basic Python types (like ``str``, ``int``, ``bool``, ``float``, etc.) are **immutable**. This means that the following attempt to port the function to Python doesn't have the same effect on the value provided by the caller -- in fact, it does nothing at all. .. code-block:: python def increment(i): i += 1 # nope.. pybind11 is also affected by such language-level conventions, which means that binding ``increment`` or ``increment_ptr`` will also create Python functions that don't modify their arguments. Although inconvenient, one workaround is to encapsulate the immutable types in a custom type that does allow modifications. An other alternative involves binding a small wrapper lambda function that returns a tuple with all output arguments (see the remainder of the documentation for examples on binding lambda functions). An example: .. code-block:: cpp int foo(int &i) { i++; return 123; } and the binding code .. code-block:: cpp m.def("foo", [](int i) { int rv = foo(i); return std::make_tuple(rv, i); }); How can I reduce the build time? ================================ It's good practice to split binding code over multiple files, as in the following example: :file:`example.cpp`: .. code-block:: cpp void init_ex1(py::module_ &); void init_ex2(py::module_ &); /* ... */ PYBIND11_MODULE(example, m) { init_ex1(m); init_ex2(m); /* ... */ } :file:`ex1.cpp`: .. code-block:: cpp void init_ex1(py::module_ &m) { m.def("add", [](int a, int b) { return a + b; }); } :file:`ex2.cpp`: .. code-block:: cpp void init_ex2(py::module_ &m) { m.def("sub", [](int a, int b) { return a - b; }); } :command:`python`: .. code-block:: pycon >>> import example >>> example.add(1, 2) 3 >>> example.sub(1, 1) 0 As shown above, the various ``init_ex`` functions should be contained in separate files that can be compiled independently from one another, and then linked together into the same final shared object. Following this approach will: 1. reduce memory requirements per compilation unit. 2. enable parallel builds (if desired). 3. allow for faster incremental builds. For instance, when a single class definition is changed, only a subset of the binding code will generally need to be recompiled. "recursive template instantiation exceeded maximum depth of 256" ================================================================ If you receive an error about excessive recursive template evaluation, try specifying a larger value, e.g. ``-ftemplate-depth=1024`` on GCC/Clang. The culprit is generally the generation of function signatures at compile time using C++14 template metaprogramming. .. _`faq:hidden_visibility`: "'SomeClass' declared with greater visibility than the type of its field 'SomeClass::member' [-Wattributes]" ============================================================================================================ This error typically indicates that you are compiling without the required ``-fvisibility`` flag. pybind11 code internally forces hidden visibility on all internal code, but if non-hidden (and thus *exported*) code attempts to include a pybind type (for example, ``py::object`` or ``py::list``) you can run into this warning. To avoid it, make sure you are specifying ``-fvisibility=hidden`` when compiling pybind code. As to why ``-fvisibility=hidden`` is necessary, because pybind modules could have been compiled under different versions of pybind itself, it is also important that the symbols defined in one module do not clash with the potentially-incompatible symbols defined in another. While Python extension modules are usually loaded with localized symbols (under POSIX systems typically using ``dlopen`` with the ``RTLD_LOCAL`` flag), this Python default can be changed, but even if it isn't it is not always enough to guarantee complete independence of the symbols involved when not using ``-fvisibility=hidden``. Additionally, ``-fvisibility=hidden`` can deliver considerably binary size savings. (See the following section for more details.) .. _`faq:symhidden`: How can I create smaller binaries? ================================== To do its job, pybind11 extensively relies on a programming technique known as *template metaprogramming*, which is a way of performing computation at compile time using type information. Template metaprogramming usually instantiates code involving significant numbers of deeply nested types that are either completely removed or reduced to just a few instructions during the compiler's optimization phase. However, due to the nested nature of these types, the resulting symbol names in the compiled extension library can be extremely long. For instance, the included test suite contains the following symbol: .. only:: html .. code-block:: none _​_​Z​N​8​p​y​b​i​n​d​1​1​1​2​c​p​p​_​f​u​n​c​t​i​o​n​C​1​I​v​8​E​x​a​m​p​l​e​2​J​R​N​S​t​3​_​_​1​6​v​e​c​t​o​r​I​N​S​3​_​1​2​b​a​s​i​c​_​s​t​r​i​n​g​I​w​N​S​3​_​1​1​c​h​a​r​_​t​r​a​i​t​s​I​w​E​E​N​S​3​_​9​a​l​l​o​c​a​t​o​r​I​w​E​E​E​E​N​S​8​_​I​S​A​_​E​E​E​E​E​J​N​S​_​4​n​a​m​e​E​N​S​_​7​s​i​b​l​i​n​g​E​N​S​_​9​i​s​_​m​e​t​h​o​d​E​A​2​8​_​c​E​E​E​M​T​0​_​F​T​_​D​p​T​1​_​E​D​p​R​K​T​2​_ .. only:: not html .. code-block:: cpp __ZN8pybind1112cpp_functionC1Iv8Example2JRNSt3__16vectorINS3_12basic_stringIwNS3_11char_traitsIwEENS3_9allocatorIwEEEENS8_ISA_EEEEEJNS_4nameENS_7siblingENS_9is_methodEA28_cEEEMT0_FT_DpT1_EDpRKT2_ which is the mangled form of the following function type: .. code-block:: cpp pybind11::cpp_function::cpp_function, std::__1::allocator >, std::__1::allocator, std::__1::allocator > > >&, pybind11::name, pybind11::sibling, pybind11::is_method, char [28]>(void (Example2::*)(std::__1::vector, std::__1::allocator >, std::__1::allocator, std::__1::allocator > > >&), pybind11::name const&, pybind11::sibling const&, pybind11::is_method const&, char const (&) [28]) The memory needed to store just the mangled name of this function (196 bytes) is larger than the actual piece of code (111 bytes) it represents! On the other hand, it's silly to even give this function a name -- after all, it's just a tiny cog in a bigger piece of machinery that is not exposed to the outside world. So we'll generally only want to export symbols for those functions which are actually called from the outside. This can be achieved by specifying the parameter ``-fvisibility=hidden`` to GCC and Clang, which sets the default symbol visibility to *hidden*, which has a tremendous impact on the final binary size of the resulting extension library. (On Visual Studio, symbols are already hidden by default, so nothing needs to be done there.) In addition to decreasing binary size, ``-fvisibility=hidden`` also avoids potential serious issues when loading multiple modules and is required for proper pybind operation. See the previous FAQ entry for more details. How can I properly handle Ctrl-C in long-running functions? =========================================================== Ctrl-C is received by the Python interpreter, and holds it until the GIL is released, so a long-running function won't be interrupted. To interrupt from inside your function, you can use the ``PyErr_CheckSignals()`` function, that will tell if a signal has been raised on the Python side. This function merely checks a flag, so its impact is negligible. When a signal has been received, you must either explicitly interrupt execution by throwing ``py::error_already_set`` (which will propagate the existing ``KeyboardInterrupt``), or clear the error (which you usually will not want): .. code-block:: cpp PYBIND11_MODULE(example, m) { m.def("long running_func", []() { for (;;) { if (PyErr_CheckSignals() != 0) throw py::error_already_set(); // Long running iteration } }); } What is a highly conclusive and simple way to find memory leaks (e.g. in pybind11 bindings)? ============================================================================================ Use ``while True`` & ``top`` (Linux, macOS). For example, locally change tests/test_type_caster_pyobject_ptr.py like this: .. code-block:: diff def test_return_list_pyobject_ptr_reference(): + while True: vec_obj = m.return_list_pyobject_ptr_reference(ValueHolder) assert [e.value for e in vec_obj] == [93, 186] # Commenting out the next `assert` will leak the Python references. # An easy way to see evidence of the leaks: # Insert `while True:` as the first line of this function and monitor the # process RES (Resident Memory Size) with the Unix top command. - assert m.dec_ref_each_pyobject_ptr(vec_obj) == 2 + # assert m.dec_ref_each_pyobject_ptr(vec_obj) == 2 Then run the test as you would normally do, which will go into the infinite loop. **In another shell, but on the same machine** run: .. code-block:: bash top This will show: .. code-block:: PID USER PR NI VIRT RES SHR S %CPU %MEM TIME+ COMMAND 1266095 rwgk 20 0 5207496 611372 45696 R 100.0 0.3 0:08.01 test_type_caste Look for the number under ``RES`` there. You'll see it going up very quickly. **Don't forget to Ctrl-C the test command** before your machine becomes unresponsive due to swapping. This method only takes a couple minutes of effort and is very conclusive. What you want to see is that the ``RES`` number is stable after a couple seconds. CMake doesn't detect the right Python version ============================================= The CMake-based build system will try to automatically detect the installed version of Python and link against that. When this fails, or when there are multiple versions of Python and it finds the wrong one, delete ``CMakeCache.txt`` and then add ``-DPYTHON_EXECUTABLE=$(which python)`` to your CMake configure line. (Replace ``$(which python)`` with a path to python if your prefer.) You can alternatively try ``-DPYBIND11_FINDPYTHON=ON``, which will activate the new CMake FindPython support instead of pybind11's custom search. Requires CMake 3.12+, and 3.15+ or 3.18.2+ are even better. You can set this in your ``CMakeLists.txt`` before adding or finding pybind11, as well. Inconsistent detection of Python version in CMake and pybind11 ============================================================== The functions ``find_package(PythonInterp)`` and ``find_package(PythonLibs)`` provided by CMake for Python version detection are modified by pybind11 due to unreliability and limitations that make them unsuitable for pybind11's needs. Instead pybind11 provides its own, more reliable Python detection CMake code. Conflicts can arise, however, when using pybind11 in a project that *also* uses the CMake Python detection in a system with several Python versions installed. This difference may cause inconsistencies and errors if *both* mechanisms are used in the same project. There are three possible solutions: 1. Avoid using ``find_package(PythonInterp)`` and ``find_package(PythonLibs)`` from CMake and rely on pybind11 in detecting Python version. If this is not possible, the CMake machinery should be called *before* including pybind11. 2. Set ``PYBIND11_FINDPYTHON`` to ``True`` or use ``find_package(Python COMPONENTS Interpreter Development)`` on modern CMake (3.12+, 3.15+ better, 3.18.2+ best). Pybind11 in these cases uses the new CMake FindPython instead of the old, deprecated search tools, and these modules are much better at finding the correct Python. If FindPythonLibs/Interp are not available (CMake 3.27+), then this will be ignored and FindPython will be used. 3. Set ``PYBIND11_NOPYTHON`` to ``TRUE``. Pybind11 will not search for Python. However, you will have to use the target-based system, and do more setup yourself, because it does not know about or include things that depend on Python, like ``pybind11_add_module``. This might be ideal for integrating into an existing system, like scikit-build's Python helpers. How to cite this project? ========================= We suggest the following BibTeX template to cite pybind11 in scientific discourse: .. code-block:: bash @misc{pybind11, author = {Wenzel Jakob and Jason Rhinelander and Dean Moldovan}, year = {2017}, note = {https://github.com/pybind/pybind11}, title = {pybind11 -- Seamless operability between C++11 and Python} } pybind11-2.13.6/docs/index.rst000066400000000000000000000011451467115402600160320ustar00rootroot00000000000000.. only:: latex Intro ===== .. include:: readme.rst .. only:: not latex Contents: .. toctree:: :maxdepth: 1 changelog upgrade .. toctree:: :caption: The Basics :maxdepth: 2 installing basics classes compiling .. toctree:: :caption: Advanced Topics :maxdepth: 2 advanced/functions advanced/classes advanced/exceptions advanced/smart_ptrs advanced/cast/index advanced/pycpp/index advanced/embedding advanced/misc .. toctree:: :caption: Extra Information :maxdepth: 1 faq benchmark limitations reference cmake/index pybind11-2.13.6/docs/installing.rst000066400000000000000000000063151467115402600170730ustar00rootroot00000000000000.. _installing: Installing the library ###################### There are several ways to get the pybind11 source, which lives at `pybind/pybind11 on GitHub `_. The pybind11 developers recommend one of the first three ways listed here, submodule, PyPI, or conda-forge, for obtaining pybind11. .. _include_as_a_submodule: Include as a submodule ====================== When you are working on a project in Git, you can use the pybind11 repository as a submodule. From your git repository, use: .. code-block:: bash git submodule add -b stable ../../pybind/pybind11 extern/pybind11 git submodule update --init This assumes you are placing your dependencies in ``extern/``, and that you are using GitHub; if you are not using GitHub, use the full https or ssh URL instead of the relative URL ``../../pybind/pybind11`` above. Some other servers also require the ``.git`` extension (GitHub does not). From here, you can now include ``extern/pybind11/include``, or you can use the various integration tools (see :ref:`compiling`) pybind11 provides directly from the local folder. Include with PyPI ================= You can download the sources and CMake files as a Python package from PyPI using Pip. Just use: .. code-block:: bash pip install pybind11 This will provide pybind11 in a standard Python package format. If you want pybind11 available directly in your environment root, you can use: .. code-block:: bash pip install "pybind11[global]" This is not recommended if you are installing with your system Python, as it will add files to ``/usr/local/include/pybind11`` and ``/usr/local/share/cmake/pybind11``, so unless that is what you want, it is recommended only for use in virtual environments or your ``pyproject.toml`` file (see :ref:`compiling`). Include with conda-forge ======================== You can use pybind11 with conda packaging via `conda-forge `_: .. code-block:: bash conda install -c conda-forge pybind11 Include with vcpkg ================== You can download and install pybind11 using the Microsoft `vcpkg `_ dependency manager: .. code-block:: bash git clone https://github.com/Microsoft/vcpkg.git cd vcpkg ./bootstrap-vcpkg.sh ./vcpkg integrate install vcpkg install pybind11 The pybind11 port in vcpkg is kept up to date by Microsoft team members and community contributors. If the version is out of date, please `create an issue or pull request `_ on the vcpkg repository. Global install with brew ======================== The brew package manager (Homebrew on macOS, or Linuxbrew on Linux) has a `pybind11 package `_. To install: .. code-block:: bash brew install pybind11 .. We should list Conan, and possibly a few other C++ package managers (hunter, .. perhaps). Conan has a very clean CMake integration that would be good to show. Other options ============= Other locations you can find pybind11 are `listed here `_; these are maintained by various packagers and the community. pybind11-2.13.6/docs/limitations.rst000066400000000000000000000054541467115402600172660ustar00rootroot00000000000000Limitations ########### Design choices ^^^^^^^^^^^^^^ pybind11 strives to be a general solution to binding generation, but it also has certain limitations: - pybind11 casts away ``const``-ness in function arguments and return values. This is in line with the Python language, which has no concept of ``const`` values. This means that some additional care is needed to avoid bugs that would be caught by the type checker in a traditional C++ program. - The NumPy interface ``pybind11::array`` greatly simplifies accessing numerical data from C++ (and vice versa), but it's not a full-blown array class like ``Eigen::Array`` or ``boost.multi_array``. ``Eigen`` objects are directly supported, however, with ``pybind11/eigen.h``. Large but useful features could be implemented in pybind11 but would lead to a significant increase in complexity. Pybind11 strives to be simple and compact. Users who require large new features are encouraged to write an extension to pybind11; see `pybind11_json `_ for an example. Known bugs ^^^^^^^^^^ These are issues that hopefully will one day be fixed, but currently are unsolved. If you know how to help with one of these issues, contributions are welcome! - Intel 20.2 is currently having an issue with the test suite. `#2573 `_ - Debug mode Python does not support 1-5 tests in the test suite currently. `#2422 `_ - PyPy3 7.3.1 and 7.3.2 have issues with several tests on 32-bit Windows. Known limitations ^^^^^^^^^^^^^^^^^ These are issues that are probably solvable, but have not been fixed yet. A clean, well written patch would likely be accepted to solve them. - Type casters are not kept alive recursively. `#2527 `_ One consequence is that containers of ``char *`` are currently not supported. `#2245 `_ Python 3.9.0 warning ^^^^^^^^^^^^^^^^^^^^ Combining older versions of pybind11 (< 2.6.0) with Python on exactly 3.9.0 will trigger undefined behavior that typically manifests as crashes during interpreter shutdown (but could also destroy your data. **You have been warned**). This issue was `fixed in Python `_. As a mitigation for this bug, pybind11 2.6.0 or newer includes a workaround specifically when Python 3.9.0 is detected at runtime, leaking about 50 bytes of memory when a callback function is garbage collected. For reference, the pybind11 test suite has about 2,000 such callbacks, but only 49 are garbage collected before the end-of-process. 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Please refer to the previous sections and the pybind11 header files for the nitty gritty details. Reference ######### .. _macros: Macros ====== .. doxygendefine:: PYBIND11_MODULE .. _core_types: Convenience classes for arbitrary Python types ============================================== Common member functions ----------------------- .. doxygenclass:: object_api :members: Without reference counting -------------------------- .. doxygenclass:: handle :members: With reference counting ----------------------- .. doxygenclass:: object :members: .. doxygenfunction:: reinterpret_borrow .. doxygenfunction:: reinterpret_steal Convenience classes for specific Python types ============================================= .. doxygenclass:: module_ :members: .. doxygengroup:: pytypes :members: Convenience functions converting to Python types ================================================ .. doxygenfunction:: make_tuple(Args&&...) .. doxygenfunction:: make_iterator(Iterator, Sentinel, Extra &&...) .. doxygenfunction:: make_iterator(Type &, Extra&&...) .. doxygenfunction:: make_key_iterator(Iterator, Sentinel, Extra &&...) .. doxygenfunction:: make_key_iterator(Type &, Extra&&...) .. doxygenfunction:: make_value_iterator(Iterator, Sentinel, Extra &&...) .. doxygenfunction:: make_value_iterator(Type &, Extra&&...) .. _extras: Passing extra arguments to ``def`` or ``class_`` ================================================ .. doxygengroup:: annotations :members: Embedding the interpreter ========================= .. doxygendefine:: PYBIND11_EMBEDDED_MODULE .. doxygenfunction:: initialize_interpreter .. doxygenfunction:: finalize_interpreter .. doxygenclass:: scoped_interpreter Redirecting C++ streams ======================= .. doxygenclass:: scoped_ostream_redirect .. doxygenclass:: scoped_estream_redirect .. doxygenfunction:: add_ostream_redirect Python built-in functions ========================= .. doxygengroup:: python_builtins :members: Inheritance =========== See :doc:`/classes` and :doc:`/advanced/classes` for more detail. .. doxygendefine:: PYBIND11_OVERRIDE .. doxygendefine:: PYBIND11_OVERRIDE_PURE .. doxygendefine:: PYBIND11_OVERRIDE_NAME .. doxygendefine:: PYBIND11_OVERRIDE_PURE_NAME .. doxygenfunction:: get_override Exceptions ========== .. doxygenclass:: error_already_set :members: .. doxygenclass:: builtin_exception :members: Literals ======== .. doxygennamespace:: literals pybind11-2.13.6/docs/release.rst000066400000000000000000000115241467115402600163450ustar00rootroot00000000000000On version numbers ^^^^^^^^^^^^^^^^^^ The two version numbers (C++ and Python) must match when combined (checked when you build the PyPI package), and must be a valid `PEP 440 `_ version when combined. For example: .. code-block:: C++ #define PYBIND11_VERSION_MAJOR X #define PYBIND11_VERSION_MINOR Y #define PYBIND11_VERSION_PATCH Z.dev1 For beta, ``PYBIND11_VERSION_PATCH`` should be ``Z.b1``. RC's can be ``Z.rc1``. Always include the dot (even though PEP 440 allows it to be dropped). For a final release, this must be a simple integer. There is also ``PYBIND11_VERSION_HEX`` just below that needs to be updated. To release a new version of pybind11: ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ If you don't have nox, you should either use ``pipx run nox`` instead, or use ``pipx install nox`` or ``brew install nox`` (Unix). - Update the version number - Update ``PYBIND11_VERSION_MAJOR`` etc. in ``include/pybind11/detail/common.h``. PATCH should be a simple integer. - Update ``PYBIND11_VERSION_HEX`` just below as well. - Update ``pybind11/_version.py`` (match above). - Run ``nox -s tests_packaging`` to ensure this was done correctly. - Ensure that all the information in ``setup.cfg`` is up-to-date, like supported Python versions. - Add release date in ``docs/changelog.rst`` and integrate the output of ``nox -s make_changelog``. - Note that the ``nox -s make_changelog`` command inspects `needs changelog `_. - Manually clear the ``needs changelog`` labels using the GitHub web interface (very easy: start by clicking the link above). - ``git add`` and ``git commit``, ``git push``. **Ensure CI passes**. (If it fails due to a known flake issue, either ignore or restart CI.) - Add a release branch if this is a new MINOR version, or update the existing release branch if it is a patch version - New branch: ``git checkout -b vX.Y``, ``git push -u origin vX.Y`` - Update branch: ``git checkout vX.Y``, ``git merge ``, ``git push`` - Update tags (optional; if you skip this, the GitHub release makes a non-annotated tag for you) - ``git tag -a vX.Y.Z -m 'vX.Y.Z release'`` - ``grep ^__version__ pybind11/_version.py`` - Last-minute consistency check: same as tag? - ``git push --tags`` - Update stable - ``git checkout stable`` - ``git merge -X theirs vX.Y.Z`` - ``git diff vX.Y.Z`` - Carefully review and reconcile any diffs. There should be none. - ``git push`` - Make a GitHub release (this shows up in the UI, sends new release notifications to users watching releases, and also uploads PyPI packages). (Note: if you do not use an existing tag, this creates a new lightweight tag for you, so you could skip the above step.) - GUI method: Under `releases `_ click "Draft a new release" on the far right, fill in the tag name (if you didn't tag above, it will be made here), fill in a release name like "Version X.Y.Z", and copy-and-paste the markdown-formatted (!) changelog into the description. You can use ``cat docs/changelog.rst | pandoc -f rst -t gfm``, then manually remove line breaks and strip links to PRs and issues, e.g. to a bare ``#1234``, without the surrounding ``<...>_`` hyperlink markup. Check "pre-release" if this is a beta/RC. - CLI method: with ``gh`` installed, run ``gh release create vX.Y.Z -t "Version X.Y.Z"`` If this is a pre-release, add ``-p``. - Get back to work - Make sure you are on master, not somewhere else: ``git checkout master`` - Update version macros in ``include/pybind11/detail/common.h`` (set PATCH to ``0.dev1`` and increment MINOR). - Update ``pybind11/_version.py`` to match. - Run ``nox -s tests_packaging`` to ensure this was done correctly. - If the release was a new MINOR version, add a new ``IN DEVELOPMENT`` section in ``docs/changelog.rst``. - ``git add``, ``git commit``, ``git push`` If a version branch is updated, remember to set PATCH to ``1.dev1``. If you'd like to bump homebrew, run: .. code-block:: console brew bump-formula-pr --url https://github.com/pybind/pybind11/archive/vX.Y.Z.tar.gz Conda-forge should automatically make a PR in a few hours, and automatically merge it if there are no issues. Manual packaging ^^^^^^^^^^^^^^^^ If you need to manually upload releases, you can download the releases from the job artifacts and upload them with twine. You can also make the files locally (not recommended in general, as your local directory is more likely to be "dirty" and SDists love picking up random unrelated/hidden files); this is the procedure: .. code-block:: bash nox -s build twine upload dist/* This makes SDists and wheels, and the final line uploads them. pybind11-2.13.6/docs/requirements.in000066400000000000000000000001451467115402600172430ustar00rootroot00000000000000breathe furo sphinx sphinx-copybutton sphinxcontrib-moderncmakedomain sphinxcontrib-svg2pdfconverter pybind11-2.13.6/docs/requirements.txt000066400000000000000000000447371467115402600174730ustar00rootroot00000000000000# This file was autogenerated by uv via the following command: # uv pip compile --generate-hashes docs/requirements.in -o docs/requirements.txt alabaster==0.7.16 \ --hash=sha256:75a8b99c28a5dad50dd7f8ccdd447a121ddb3892da9e53d1ca5cca3106d58d65 \ --hash=sha256:b46733c07dce03ae4e150330b975c75737fa60f0a7c591b6c8bf4928a28e2c92 # via sphinx babel==2.14.0 \ --hash=sha256:6919867db036398ba21eb5c7a0f6b28ab8cbc3ae7a73a44ebe34ae74a4e7d363 \ --hash=sha256:efb1a25b7118e67ce3a259bed20545c29cb68be8ad2c784c83689981b7a57287 # via sphinx beautifulsoup4==4.12.3 \ --hash=sha256:74e3d1928edc070d21748185c46e3fb33490f22f52a3addee9aee0f4f7781051 \ --hash=sha256:b80878c9f40111313e55da8ba20bdba06d8fa3969fc68304167741bbf9e082ed # via furo breathe==4.35.0 \ --hash=sha256:5165541c3c67b6c7adde8b3ecfe895c6f7844783c4076b6d8d287e4f33d62386 \ --hash=sha256:52c581f42ca4310737f9e435e3851c3d1f15446205a85fbc272f1f97ed74f5be # via -r requirements.in certifi==2024.7.4 \ --hash=sha256:5a1e7645bc0ec61a09e26c36f6106dd4cf40c6db3a1fb6352b0244e7fb057c7b \ --hash=sha256:c198e21b1289c2ab85ee4e67bb4b4ef3ead0892059901a8d5b622f24a1101e90 # via requests charset-normalizer==3.3.2 \ --hash=sha256:06435b539f889b1f6f4ac1758871aae42dc3a8c0e24ac9e60c2384973ad73027 \ --hash=sha256:06a81e93cd441c56a9b65d8e1d043daeb97a3d0856d177d5c90ba85acb3db087 \ --hash=sha256:0a55554a2fa0d408816b3b5cedf0045f4b8e1a6065aec45849de2d6f3f8e9786 \ --hash=sha256:0b2b64d2bb6d3fb9112bafa732def486049e63de9618b5843bcdd081d8144cd8 \ --hash=sha256:10955842570876604d404661fbccbc9c7e684caf432c09c715ec38fbae45ae09 \ --hash=sha256:122c7fa62b130ed55f8f285bfd56d5f4b4a5b503609d181f9ad85e55c89f4185 \ --hash=sha256:1ceae2f17a9c33cb48e3263960dc5fc8005351ee19db217e9b1bb15d28c02574 \ --hash=sha256:1d3193f4a680c64b4b6a9115943538edb896edc190f0b222e73761716519268e \ --hash=sha256:1f79682fbe303db92bc2b1136016a38a42e835d932bab5b3b1bfcfbf0640e519 \ --hash=sha256:2127566c664442652f024c837091890cb1942c30937add288223dc895793f898 \ --hash=sha256:22afcb9f253dac0696b5a4be4a1c0f8762f8239e21b99680099abd9b2b1b2269 \ --hash=sha256:25baf083bf6f6b341f4121c2f3c548875ee6f5339300e08be3f2b2ba1721cdd3 \ --hash=sha256:2e81c7b9c8979ce92ed306c249d46894776a909505d8f5a4ba55b14206e3222f \ --hash=sha256:3287761bc4ee9e33561a7e058c72ac0938c4f57fe49a09eae428fd88aafe7bb6 \ --hash=sha256:34d1c8da1e78d2e001f363791c98a272bb734000fcef47a491c1e3b0505657a8 \ --hash=sha256:37e55c8e51c236f95b033f6fb391d7d7970ba5fe7ff453dad675e88cf303377a \ --hash=sha256:3d47fa203a7bd9c5b6cee4736ee84ca03b8ef23193c0d1ca99b5089f72645c73 \ --hash=sha256:3e4d1f6587322d2788836a99c69062fbb091331ec940e02d12d179c1d53e25fc \ --hash=sha256:42cb296636fcc8b0644486d15c12376cb9fa75443e00fb25de0b8602e64c1714 \ --hash=sha256:45485e01ff4d3630ec0d9617310448a8702f70e9c01906b0d0118bdf9d124cf2 \ --hash=sha256:4a78b2b446bd7c934f5dcedc588903fb2f5eec172f3d29e52a9096a43722adfc \ --hash=sha256:4ab2fe47fae9e0f9dee8c04187ce5d09f48eabe611be8259444906793ab7cbce \ --hash=sha256:4d0d1650369165a14e14e1e47b372cfcb31d6ab44e6e33cb2d4e57265290044d \ --hash=sha256:549a3a73da901d5bc3ce8d24e0600d1fa85524c10287f6004fbab87672bf3e1e \ --hash=sha256:55086ee1064215781fff39a1af09518bc9255b50d6333f2e4c74ca09fac6a8f6 \ --hash=sha256:572c3763a264ba47b3cf708a44ce965d98555f618ca42c926a9c1616d8f34269 \ --hash=sha256:573f6eac48f4769d667c4442081b1794f52919e7edada77495aaed9236d13a96 \ --hash=sha256:5b4c145409bef602a690e7cfad0a15a55c13320ff7a3ad7ca59c13bb8ba4d45d \ --hash=sha256:6463effa3186ea09411d50efc7d85360b38d5f09b870c48e4600f63af490e56a \ --hash=sha256:65f6f63034100ead094b8744b3b97965785388f308a64cf8d7c34f2f2e5be0c4 \ --hash=sha256:663946639d296df6a2bb2aa51b60a2454ca1cb29835324c640dafb5ff2131a77 \ --hash=sha256:6897af51655e3691ff853668779c7bad41579facacf5fd7253b0133308cf000d \ --hash=sha256:68d1f8a9e9e37c1223b656399be5d6b448dea850bed7d0f87a8311f1ff3dabb0 \ --hash=sha256:6ac7ffc7ad6d040517be39eb591cac5ff87416c2537df6ba3cba3bae290c0fed \ --hash=sha256:6b3251890fff30ee142c44144871185dbe13b11bab478a88887a639655be1068 \ --hash=sha256:6c4caeef8fa63d06bd437cd4bdcf3ffefe6738fb1b25951440d80dc7df8c03ac \ --hash=sha256:6ef1d82a3af9d3eecdba2321dc1b3c238245d890843e040e41e470ffa64c3e25 \ --hash=sha256:753f10e867343b4511128c6ed8c82f7bec3bd026875576dfd88483c5c73b2fd8 \ --hash=sha256:7cd13a2e3ddeed6913a65e66e94b51d80a041145a026c27e6bb76c31a853c6ab \ --hash=sha256:7ed9e526742851e8d5cc9e6cf41427dfc6068d4f5a3bb03659444b4cabf6bc26 \ --hash=sha256:7f04c839ed0b6b98b1a7501a002144b76c18fb1c1850c8b98d458ac269e26ed2 \ --hash=sha256:802fe99cca7457642125a8a88a084cef28ff0cf9407060f7b93dca5aa25480db \ --hash=sha256:80402cd6ee291dcb72644d6eac93785fe2c8b9cb30893c1af5b8fdd753b9d40f \ --hash=sha256:8465322196c8b4d7ab6d1e049e4c5cb460d0394da4a27d23cc242fbf0034b6b5 \ --hash=sha256:86216b5cee4b06df986d214f664305142d9c76df9b6512be2738aa72a2048f99 \ --hash=sha256:87d1351268731db79e0f8e745d92493ee2841c974128ef629dc518b937d9194c \ --hash=sha256:8bdb58ff7ba23002a4c5808d608e4e6c687175724f54a5dade5fa8c67b604e4d \ --hash=sha256:8c622a5fe39a48f78944a87d4fb8a53ee07344641b0562c540d840748571b811 \ --hash=sha256:8d756e44e94489e49571086ef83b2bb8ce311e730092d2c34ca8f7d925cb20aa \ --hash=sha256:8f4a014bc36d3c57402e2977dada34f9c12300af536839dc38c0beab8878f38a \ --hash=sha256:9063e24fdb1e498ab71cb7419e24622516c4a04476b17a2dab57e8baa30d6e03 \ --hash=sha256:90d558489962fd4918143277a773316e56c72da56ec7aa3dc3dbbe20fdfed15b \ --hash=sha256:923c0c831b7cfcb071580d3f46c4baf50f174be571576556269530f4bbd79d04 \ --hash=sha256:95f2a5796329323b8f0512e09dbb7a1860c46a39da62ecb2324f116fa8fdc85c \ --hash=sha256:96b02a3dc4381e5494fad39be677abcb5e6634bf7b4fa83a6dd3112607547001 \ --hash=sha256:9f96df6923e21816da7e0ad3fd47dd8f94b2a5ce594e00677c0013018b813458 \ --hash=sha256:a10af20b82360ab00827f916a6058451b723b4e65030c5a18577c8b2de5b3389 \ --hash=sha256:a50aebfa173e157099939b17f18600f72f84eed3049e743b68ad15bd69b6bf99 \ --hash=sha256:a981a536974bbc7a512cf44ed14938cf01030a99e9b3a06dd59578882f06f985 \ --hash=sha256:a9a8e9031d613fd2009c182b69c7b2c1ef8239a0efb1df3f7c8da66d5dd3d537 \ --hash=sha256:ae5f4161f18c61806f411a13b0310bea87f987c7d2ecdbdaad0e94eb2e404238 \ --hash=sha256:aed38f6e4fb3f5d6bf81bfa990a07806be9d83cf7bacef998ab1a9bd660a581f \ --hash=sha256:b01b88d45a6fcb69667cd6d2f7a9aeb4bf53760d7fc536bf679ec94fe9f3ff3d \ --hash=sha256:b261ccdec7821281dade748d088bb6e9b69e6d15b30652b74cbbac25e280b796 \ --hash=sha256:b2b0a0c0517616b6869869f8c581d4eb2dd83a4d79e0ebcb7d373ef9956aeb0a \ --hash=sha256:b4a23f61ce87adf89be746c8a8974fe1c823c891d8f86eb218bb957c924bb143 \ --hash=sha256:bd8f7df7d12c2db9fab40bdd87a7c09b1530128315d047a086fa3ae3435cb3a8 \ --hash=sha256:beb58fe5cdb101e3a055192ac291b7a21e3b7ef4f67fa1d74e331a7f2124341c \ --hash=sha256:c002b4ffc0be611f0d9da932eb0f704fe2602a9a949d1f738e4c34c75b0863d5 \ --hash=sha256:c083af607d2515612056a31f0a8d9e0fcb5876b7bfc0abad3ecd275bc4ebc2d5 \ --hash=sha256:c180f51afb394e165eafe4ac2936a14bee3eb10debc9d9e4db8958fe36afe711 \ --hash=sha256:c235ebd9baae02f1b77bcea61bce332cb4331dc3617d254df3323aa01ab47bd4 \ --hash=sha256:cd70574b12bb8a4d2aaa0094515df2463cb429d8536cfb6c7ce983246983e5a6 \ --hash=sha256:d0eccceffcb53201b5bfebb52600a5fb483a20b61da9dbc885f8b103cbe7598c \ --hash=sha256:d965bba47ddeec8cd560687584e88cf699fd28f192ceb452d1d7ee807c5597b7 \ --hash=sha256:db364eca23f876da6f9e16c9da0df51aa4f104a972735574842618b8c6d999d4 \ --hash=sha256:ddbb2551d7e0102e7252db79ba445cdab71b26640817ab1e3e3648dad515003b \ --hash=sha256:deb6be0ac38ece9ba87dea880e438f25ca3eddfac8b002a2ec3d9183a454e8ae \ --hash=sha256:e06ed3eb3218bc64786f7db41917d4e686cc4856944f53d5bdf83a6884432e12 \ --hash=sha256:e27ad930a842b4c5eb8ac0016b0a54f5aebbe679340c26101df33424142c143c \ --hash=sha256:e537484df0d8f426ce2afb2d0f8e1c3d0b114b83f8850e5f2fbea0e797bd82ae \ --hash=sha256:eb00ed941194665c332bf8e078baf037d6c35d7c4f3102ea2d4f16ca94a26dc8 \ --hash=sha256:eb6904c354526e758fda7167b33005998fb68c46fbc10e013ca97f21ca5c8887 \ --hash=sha256:eb8821e09e916165e160797a6c17edda0679379a4be5c716c260e836e122f54b \ --hash=sha256:efcb3f6676480691518c177e3b465bcddf57cea040302f9f4e6e191af91174d4 \ --hash=sha256:f27273b60488abe721a075bcca6d7f3964f9f6f067c8c4c605743023d7d3944f \ --hash=sha256:f30c3cb33b24454a82faecaf01b19c18562b1e89558fb6c56de4d9118a032fd5 \ --hash=sha256:fb69256e180cb6c8a894fee62b3afebae785babc1ee98b81cdf68bbca1987f33 \ --hash=sha256:fd1abc0d89e30cc4e02e4064dc67fcc51bd941eb395c502aac3ec19fab46b519 \ --hash=sha256:ff8fa367d09b717b2a17a052544193ad76cd49979c805768879cb63d9ca50561 # via requests docutils==0.20.1 \ --hash=sha256:96f387a2c5562db4476f09f13bbab2192e764cac08ebbf3a34a95d9b1e4a59d6 \ --hash=sha256:f08a4e276c3a1583a86dce3e34aba3fe04d02bba2dd51ed16106244e8a923e3b # via # breathe # sphinx furo==2024.1.29 \ --hash=sha256:3548be2cef45a32f8cdc0272d415fcb3e5fa6a0eb4ddfe21df3ecf1fe45a13cf \ --hash=sha256:4d6b2fe3f10a6e36eb9cc24c1e7beb38d7a23fc7b3c382867503b7fcac8a1e02 # via -r requirements.in idna==3.7 \ --hash=sha256:028ff3aadf0609c1fd278d8ea3089299412a7a8b9bd005dd08b9f8285bcb5cfc \ --hash=sha256:82fee1fc78add43492d3a1898bfa6d8a904cc97d8427f683ed8e798d07761aa0 # via requests imagesize==1.4.1 \ --hash=sha256:0d8d18d08f840c19d0ee7ca1fd82490fdc3729b7ac93f49870406ddde8ef8d8b \ --hash=sha256:69150444affb9cb0d5cc5a92b3676f0b2fb7cd9ae39e947a5e11a36b4497cd4a # via sphinx jinja2==3.1.4 \ --hash=sha256:4a3aee7acbbe7303aede8e9648d13b8bf88a429282aa6122a993f0ac800cb369 \ --hash=sha256:bc5dd2abb727a5319567b7a813e6a2e7318c39f4f487cfe6c89c6f9c7d25197d # via sphinx markupsafe==2.1.5 \ --hash=sha256:00e046b6dd71aa03a41079792f8473dc494d564611a8f89bbbd7cb93295ebdcf \ --hash=sha256:075202fa5b72c86ad32dc7d0b56024ebdbcf2048c0ba09f1cde31bfdd57bcfff \ --hash=sha256:0e397ac966fdf721b2c528cf028494e86172b4feba51d65f81ffd65c63798f3f \ --hash=sha256:17b950fccb810b3293638215058e432159d2b71005c74371d784862b7e4683f3 \ --hash=sha256:1f3fbcb7ef1f16e48246f704ab79d79da8a46891e2da03f8783a5b6fa41a9532 \ --hash=sha256:2174c595a0d73a3080ca3257b40096db99799265e1c27cc5a610743acd86d62f \ --hash=sha256:2b7c57a4dfc4f16f7142221afe5ba4e093e09e728ca65c51f5620c9aaeb9a617 \ --hash=sha256:2d2d793e36e230fd32babe143b04cec8a8b3eb8a3122d2aceb4a371e6b09b8df \ --hash=sha256:30b600cf0a7ac9234b2638fbc0fb6158ba5bdcdf46aeb631ead21248b9affbc4 \ --hash=sha256:397081c1a0bfb5124355710fe79478cdbeb39626492b15d399526ae53422b906 \ --hash=sha256:3a57fdd7ce31c7ff06cdfbf31dafa96cc533c21e443d57f5b1ecc6cdc668ec7f \ --hash=sha256:3c6b973f22eb18a789b1460b4b91bf04ae3f0c4234a0a6aa6b0a92f6f7b951d4 \ --hash=sha256:3e53af139f8579a6d5f7b76549125f0d94d7e630761a2111bc431fd820e163b8 \ --hash=sha256:4096e9de5c6fdf43fb4f04c26fb114f61ef0bf2e5604b6ee3019d51b69e8c371 \ --hash=sha256:4275d846e41ecefa46e2015117a9f491e57a71ddd59bbead77e904dc02b1bed2 \ --hash=sha256:4c31f53cdae6ecfa91a77820e8b151dba54ab528ba65dfd235c80b086d68a465 \ --hash=sha256:4f11aa001c540f62c6166c7726f71f7573b52c68c31f014c25cc7901deea0b52 \ --hash=sha256:5049256f536511ee3f7e1b3f87d1d1209d327e818e6ae1365e8653d7e3abb6a6 \ --hash=sha256:58c98fee265677f63a4385256a6d7683ab1832f3ddd1e66fe948d5880c21a169 \ --hash=sha256:598e3276b64aff0e7b3451b72e94fa3c238d452e7ddcd893c3ab324717456bad \ --hash=sha256:5b7b716f97b52c5a14bffdf688f971b2d5ef4029127f1ad7a513973cfd818df2 \ --hash=sha256:5dedb4db619ba5a2787a94d877bc8ffc0566f92a01c0ef214865e54ecc9ee5e0 \ --hash=sha256:619bc166c4f2de5caa5a633b8b7326fbe98e0ccbfacabd87268a2b15ff73a029 \ --hash=sha256:629ddd2ca402ae6dbedfceeba9c46d5f7b2a61d9749597d4307f943ef198fc1f \ --hash=sha256:656f7526c69fac7f600bd1f400991cc282b417d17539a1b228617081106feb4a \ --hash=sha256:6ec585f69cec0aa07d945b20805be741395e28ac1627333b1c5b0105962ffced \ --hash=sha256:72b6be590cc35924b02c78ef34b467da4ba07e4e0f0454a2c5907f473fc50ce5 \ --hash=sha256:7502934a33b54030eaf1194c21c692a534196063db72176b0c4028e140f8f32c \ --hash=sha256:7a68b554d356a91cce1236aa7682dc01df0edba8d043fd1ce607c49dd3c1edcf \ --hash=sha256:7b2e5a267c855eea6b4283940daa6e88a285f5f2a67f2220203786dfa59b37e9 \ --hash=sha256:823b65d8706e32ad2df51ed89496147a42a2a6e01c13cfb6ffb8b1e92bc910bb \ --hash=sha256:8590b4ae07a35970728874632fed7bd57b26b0102df2d2b233b6d9d82f6c62ad \ --hash=sha256:8dd717634f5a044f860435c1d8c16a270ddf0ef8588d4887037c5028b859b0c3 \ --hash=sha256:8dec4936e9c3100156f8a2dc89c4b88d5c435175ff03413b443469c7c8c5f4d1 \ --hash=sha256:97cafb1f3cbcd3fd2b6fbfb99ae11cdb14deea0736fc2b0952ee177f2b813a46 \ --hash=sha256:a17a92de5231666cfbe003f0e4b9b3a7ae3afb1ec2845aadc2bacc93ff85febc \ --hash=sha256:a549b9c31bec33820e885335b451286e2969a2d9e24879f83fe904a5ce59d70a \ --hash=sha256:ac07bad82163452a6884fe8fa0963fb98c2346ba78d779ec06bd7a6262132aee \ --hash=sha256:ae2ad8ae6ebee9d2d94b17fb62763125f3f374c25618198f40cbb8b525411900 \ --hash=sha256:b91c037585eba9095565a3556f611e3cbfaa42ca1e865f7b8015fe5c7336d5a5 \ --hash=sha256:bc1667f8b83f48511b94671e0e441401371dfd0f0a795c7daa4a3cd1dde55bea \ --hash=sha256:bec0a414d016ac1a18862a519e54b2fd0fc8bbfd6890376898a6c0891dd82e9f \ --hash=sha256:bf50cd79a75d181c9181df03572cdce0fbb75cc353bc350712073108cba98de5 \ --hash=sha256:bff1b4290a66b490a2f4719358c0cdcd9bafb6b8f061e45c7a2460866bf50c2e \ --hash=sha256:c061bb86a71b42465156a3ee7bd58c8c2ceacdbeb95d05a99893e08b8467359a \ --hash=sha256:c8b29db45f8fe46ad280a7294f5c3ec36dbac9491f2d1c17345be8e69cc5928f \ --hash=sha256:ce409136744f6521e39fd8e2a24c53fa18ad67aa5bc7c2cf83645cce5b5c4e50 \ --hash=sha256:d050b3361367a06d752db6ead6e7edeb0009be66bc3bae0ee9d97fb326badc2a \ --hash=sha256:d283d37a890ba4c1ae73ffadf8046435c76e7bc2247bbb63c00bd1a709c6544b \ --hash=sha256:d9fad5155d72433c921b782e58892377c44bd6252b5af2f67f16b194987338a4 \ --hash=sha256:daa4ee5a243f0f20d528d939d06670a298dd39b1ad5f8a72a4275124a7819eff \ --hash=sha256:db0b55e0f3cc0be60c1f19efdde9a637c32740486004f20d1cff53c3c0ece4d2 \ --hash=sha256:e61659ba32cf2cf1481e575d0462554625196a1f2fc06a1c777d3f48e8865d46 \ --hash=sha256:ea3d8a3d18833cf4304cd2fc9cbb1efe188ca9b5efef2bdac7adc20594a0e46b \ --hash=sha256:ec6a563cff360b50eed26f13adc43e61bc0c04d94b8be985e6fb24b81f6dcfdf \ --hash=sha256:f5dfb42c4604dddc8e4305050aa6deb084540643ed5804d7455b5df8fe16f5e5 \ --hash=sha256:fa173ec60341d6bb97a89f5ea19c85c5643c1e7dedebc22f5181eb73573142c5 \ --hash=sha256:fa9db3f79de01457b03d4f01b34cf91bc0048eb2c3846ff26f66687c2f6d16ab \ --hash=sha256:fce659a462a1be54d2ffcacea5e3ba2d74daa74f30f5f143fe0c58636e355fdd \ --hash=sha256:ffee1f21e5ef0d712f9033568f8344d5da8cc2869dbd08d87c84656e6a2d2f68 # via jinja2 packaging==24.0 \ --hash=sha256:2ddfb553fdf02fb784c234c7ba6ccc288296ceabec964ad2eae3777778130bc5 \ --hash=sha256:eb82c5e3e56209074766e6885bb04b8c38a0c015d0a30036ebe7ece34c9989e9 # via sphinx pygments==2.17.2 \ --hash=sha256:b27c2826c47d0f3219f29554824c30c5e8945175d888647acd804ddd04af846c \ --hash=sha256:da46cec9fd2de5be3a8a784f434e4c4ab670b4ff54d605c4c2717e9d49c4c367 # via # furo # sphinx requests==2.32.0 \ --hash=sha256:f2c3881dddb70d056c5bd7600a4fae312b2a300e39be6a118d30b90bd27262b5 \ --hash=sha256:fa5490319474c82ef1d2c9bc459d3652e3ae4ef4c4ebdd18a21145a47ca4b6b8 # via sphinx snowballstemmer==2.2.0 \ --hash=sha256:09b16deb8547d3412ad7b590689584cd0fe25ec8db3be37788be3810cbf19cb1 \ --hash=sha256:c8e1716e83cc398ae16824e5572ae04e0d9fc2c6b985fb0f900f5f0c96ecba1a # via sphinx soupsieve==2.5 \ --hash=sha256:5663d5a7b3bfaeee0bc4372e7fc48f9cff4940b3eec54a6451cc5299f1097690 \ --hash=sha256:eaa337ff55a1579b6549dc679565eac1e3d000563bcb1c8ab0d0fefbc0c2cdc7 # via beautifulsoup4 sphinx==7.2.6 \ --hash=sha256:1e09160a40b956dc623c910118fa636da93bd3ca0b9876a7b3df90f07d691560 \ --hash=sha256:9a5160e1ea90688d5963ba09a2dcd8bdd526620edbb65c328728f1b2228d5ab5 # via # -r requirements.in # breathe # furo # sphinx-basic-ng # sphinx-copybutton # sphinxcontrib-moderncmakedomain # sphinxcontrib-svg2pdfconverter sphinx-basic-ng==1.0.0b2 \ --hash=sha256:9ec55a47c90c8c002b5960c57492ec3021f5193cb26cebc2dc4ea226848651c9 \ --hash=sha256:eb09aedbabfb650607e9b4b68c9d240b90b1e1be221d6ad71d61c52e29f7932b # via furo sphinx-copybutton==0.5.2 \ --hash=sha256:4cf17c82fb9646d1bc9ca92ac280813a3b605d8c421225fd9913154103ee1fbd \ --hash=sha256:fb543fd386d917746c9a2c50360c7905b605726b9355cd26e9974857afeae06e # via -r requirements.in sphinxcontrib-applehelp==1.0.8 \ --hash=sha256:c40a4f96f3776c4393d933412053962fac2b84f4c99a7982ba42e09576a70619 \ --hash=sha256:cb61eb0ec1b61f349e5cc36b2028e9e7ca765be05e49641c97241274753067b4 # via sphinx sphinxcontrib-devhelp==1.0.6 \ --hash=sha256:6485d09629944511c893fa11355bda18b742b83a2b181f9a009f7e500595c90f \ --hash=sha256:9893fd3f90506bc4b97bdb977ceb8fbd823989f4316b28c3841ec128544372d3 # via sphinx sphinxcontrib-htmlhelp==2.0.5 \ --hash=sha256:0dc87637d5de53dd5eec3a6a01753b1ccf99494bd756aafecd74b4fa9e729015 \ --hash=sha256:393f04f112b4d2f53d93448d4bce35842f62b307ccdc549ec1585e950bc35e04 # via sphinx sphinxcontrib-jsmath==1.0.1 \ --hash=sha256:2ec2eaebfb78f3f2078e73666b1415417a116cc848b72e5172e596c871103178 \ --hash=sha256:a9925e4a4587247ed2191a22df5f6970656cb8ca2bd6284309578f2153e0c4b8 # via sphinx sphinxcontrib-moderncmakedomain==3.27.0 \ --hash=sha256:51e259e91f58d17cc0fac9307fd40106aa59d5acaa741887903fc3660361d1a1 \ --hash=sha256:70a73e0e7cff1b117074e968ccb7f72383ed0f572414df0e216cea06914de988 # via -r requirements.in sphinxcontrib-qthelp==1.0.7 \ --hash=sha256:053dedc38823a80a7209a80860b16b722e9e0209e32fea98c90e4e6624588ed6 \ --hash=sha256:e2ae3b5c492d58fcbd73281fbd27e34b8393ec34a073c792642cd8e529288182 # via sphinx sphinxcontrib-serializinghtml==1.1.10 \ --hash=sha256:326369b8df80a7d2d8d7f99aa5ac577f51ea51556ed974e7716cfd4fca3f6cb7 \ --hash=sha256:93f3f5dc458b91b192fe10c397e324f262cf163d79f3282c158e8436a2c4511f # via sphinx sphinxcontrib-svg2pdfconverter==1.2.2 \ --hash=sha256:04ec767b55780a6b18d89cc1a8ada6d900c6efde9d1683abdb98a49b144465ca \ --hash=sha256:80a55ca61f70eae93efc65f3814f2f177c86ba55934a9f6c5022f1778b62146b # via -r requirements.in urllib3==2.2.2 \ --hash=sha256:a448b2f64d686155468037e1ace9f2d2199776e17f0a46610480d311f73e3472 \ --hash=sha256:dd505485549a7a552833da5e6063639d0d177c04f23bc3864e41e5dc5f612168 # via requests pybind11-2.13.6/docs/upgrade.rst000066400000000000000000000611711467115402600163570ustar00rootroot00000000000000Upgrade guide ############# This is a companion guide to the :doc:`changelog`. While the changelog briefly lists all of the new features, improvements and bug fixes, this upgrade guide focuses only the subset which directly impacts your experience when upgrading to a new version. But it goes into more detail. This includes things like deprecated APIs and their replacements, build system changes, general code modernization and other useful information. .. _upgrade-guide-2.12: v2.12 ===== NumPy support has been upgraded to support the 2.x series too. The two relevant changes are that: * ``dtype.flags()`` is now a ``uint64`` and ``dtype.alignment()`` an ``ssize_t`` (and NumPy may return an larger than integer value for ``itemsize()`` in NumPy 2.x). * The long deprecated NumPy function ``PyArray_GetArrayParamsFromObject`` function is not available anymore. Due to NumPy changes, you may experience difficulties updating to NumPy 2. Please see the [NumPy 2 migration guide](https://numpy.org/devdocs/numpy_2_0_migration_guide.html) for details. For example, a more direct change could be that the default integer ``"int_"`` (and ``"uint"``) is now ``ssize_t`` and not ``long`` (affects 64bit windows). If you want to only support NumPy 1.x for now and are having problems due to the two internal changes listed above, you can define ``PYBIND11_NUMPY_1_ONLY`` to disable the new support for now. Make sure you define this on all pybind11 compile units, since it could be a source of ODR violations if used inconsistently. This option will be removed in the future, so adapting your code is highly recommended. .. _upgrade-guide-2.11: v2.11 ===== * The minimum version of CMake is now 3.5. A future version will likely move to requiring something like CMake 3.15. Note that CMake 3.27 is removing the long-deprecated support for ``FindPythonInterp`` if you set 3.27 as the minimum or maximum supported version. To prepare for that future, CMake 3.15+ using ``FindPython`` or setting ``PYBIND11_FINDPYTHON`` is highly recommended, otherwise pybind11 will automatically switch to using ``FindPython`` if ``FindPythonInterp`` is not available. .. _upgrade-guide-2.9: v2.9 ==== * Any usage of the recently added ``py::make_simple_namespace`` should be converted to using ``py::module_::import("types").attr("SimpleNamespace")`` instead. * The use of ``_`` in custom type casters can now be replaced with the more readable ``const_name`` instead. The old ``_`` shortcut has been retained unless it is being used as a macro (like for gettext). .. _upgrade-guide-2.7: v2.7 ==== *Before* v2.7, ``py::str`` can hold ``PyUnicodeObject`` or ``PyBytesObject``, and ``py::isinstance()`` is ``true`` for both ``py::str`` and ``py::bytes``. Starting with v2.7, ``py::str`` exclusively holds ``PyUnicodeObject`` (`#2409 `_), and ``py::isinstance()`` is ``true`` only for ``py::str``. To help in the transition of user code, the ``PYBIND11_STR_LEGACY_PERMISSIVE`` macro is provided as an escape hatch to go back to the legacy behavior. This macro will be removed in future releases. Two types of required fixes are expected to be common: * Accidental use of ``py::str`` instead of ``py::bytes``, masked by the legacy behavior. These are probably very easy to fix, by changing from ``py::str`` to ``py::bytes``. * Reliance on py::isinstance(obj) being ``true`` for ``py::bytes``. This is likely to be easy to fix in most cases by adding ``|| py::isinstance(obj)``, but a fix may be more involved, e.g. if ``py::isinstance`` appears in a template. Such situations will require careful review and custom fixes. .. _upgrade-guide-2.6: v2.6 ==== Usage of the ``PYBIND11_OVERLOAD*`` macros and ``get_overload`` function should be replaced by ``PYBIND11_OVERRIDE*`` and ``get_override``. In the future, the old macros may be deprecated and removed. ``py::module`` has been renamed ``py::module_``, but a backward compatible typedef has been included. This change was to avoid a language change in C++20 that requires unqualified ``module`` not be placed at the start of a logical line. Qualified usage is unaffected and the typedef will remain unless the C++ language rules change again. The public constructors of ``py::module_`` have been deprecated. Use ``PYBIND11_MODULE`` or ``module_::create_extension_module`` instead. An error is now thrown when ``__init__`` is forgotten on subclasses. This was incorrect before, but was not checked. Add a call to ``__init__`` if it is missing. A ``py::type_error`` is now thrown when casting to a subclass (like ``py::bytes`` from ``py::object``) if the conversion is not valid. Make a valid conversion instead. The undocumented ``h.get_type()`` method has been deprecated and replaced by ``py::type::of(h)``. Enums now have a ``__str__`` method pre-defined; if you want to override it, the simplest fix is to add the new ``py::prepend()`` tag when defining ``"__str__"``. If ``__eq__`` defined but not ``__hash__``, ``__hash__`` is now set to ``None``, as in normal CPython. You should add ``__hash__`` if you intended the class to be hashable, possibly using the new ``py::hash`` shortcut. The constructors for ``py::array`` now always take signed integers for size, for consistency. This may lead to compiler warnings on some systems. Cast to ``py::ssize_t`` instead of ``std::size_t``. The ``tools/clang`` submodule and ``tools/mkdoc.py`` have been moved to a standalone package, `pybind11-mkdoc`_. If you were using those tools, please use them via a pip install from the new location. The ``pybind11`` package on PyPI no longer fills the wheel "headers" slot - if you were using the headers from this slot, they are available by requesting the ``global`` extra, that is, ``pip install "pybind11[global]"``. (Most users will be unaffected, as the ``pybind11/include`` location is reported by ``python -m pybind11 --includes`` and ``pybind11.get_include()`` is still correct and has not changed since 2.5). .. _pybind11-mkdoc: https://github.com/pybind/pybind11-mkdoc CMake support: -------------- The minimum required version of CMake is now 3.4. Several details of the CMake support have been deprecated; warnings will be shown if you need to change something. The changes are: * ``PYBIND11_CPP_STANDARD=`` is deprecated, please use ``CMAKE_CXX_STANDARD=`` instead, or any other valid CMake CXX or CUDA standard selection method, like ``target_compile_features``. * If you do not request a standard, pybind11 targets will compile with the compiler default, but not less than C++11, instead of forcing C++14 always. If you depend on the old behavior, please use ``set(CMAKE_CXX_STANDARD 14 CACHE STRING "")`` instead. * Direct ``pybind11::module`` usage should always be accompanied by at least ``set(CMAKE_CXX_VISIBILITY_PRESET hidden)`` or similar - it used to try to manually force this compiler flag (but not correctly on all compilers or with CUDA). * ``pybind11_add_module``'s ``SYSTEM`` argument is deprecated and does nothing; linking now behaves like other imported libraries consistently in both config and submodule mode, and behaves like a ``SYSTEM`` library by default. * If ``PYTHON_EXECUTABLE`` is not set, virtual environments (``venv``, ``virtualenv``, and ``conda``) are prioritized over the standard search (similar to the new FindPython mode). In addition, the following changes may be of interest: * ``CMAKE_INTERPROCEDURAL_OPTIMIZATION`` will be respected by ``pybind11_add_module`` if set instead of linking to ``pybind11::lto`` or ``pybind11::thin_lto``. * Using ``find_package(Python COMPONENTS Interpreter Development)`` before pybind11 will cause pybind11 to use the new Python mechanisms instead of its own custom search, based on a patched version of classic ``FindPythonInterp`` / ``FindPythonLibs``. In the future, this may become the default. A recent (3.15+ or 3.18.2+) version of CMake is recommended. v2.5 ==== The Python package now includes the headers as data in the package itself, as well as in the "headers" wheel slot. ``pybind11 --includes`` and ``pybind11.get_include()`` report the new location, which is always correct regardless of how pybind11 was installed, making the old ``user=`` argument meaningless. If you are not using the function to get the location already, you are encouraged to switch to the package location. v2.2 ==== Deprecation of the ``PYBIND11_PLUGIN`` macro -------------------------------------------- ``PYBIND11_MODULE`` is now the preferred way to create module entry points. The old macro emits a compile-time deprecation warning. .. code-block:: cpp // old PYBIND11_PLUGIN(example) { py::module m("example", "documentation string"); m.def("add", [](int a, int b) { return a + b; }); return m.ptr(); } // new PYBIND11_MODULE(example, m) { m.doc() = "documentation string"; // optional m.def("add", [](int a, int b) { return a + b; }); } New API for defining custom constructors and pickling functions --------------------------------------------------------------- The old placement-new custom constructors have been deprecated. The new approach uses ``py::init()`` and factory functions to greatly improve type safety. Placement-new can be called accidentally with an incompatible type (without any compiler errors or warnings), or it can initialize the same object multiple times if not careful with the Python-side ``__init__`` calls. The new-style custom constructors prevent such mistakes. See :ref:`custom_constructors` for details. .. code-block:: cpp // old -- deprecated (runtime warning shown only in debug mode) py::class(m, "Foo") .def("__init__", [](Foo &self, ...) { new (&self) Foo(...); // uses placement-new }); // new py::class(m, "Foo") .def(py::init([](...) { // Note: no `self` argument return new Foo(...); // return by raw pointer // or: return std::make_unique(...); // return by holder // or: return Foo(...); // return by value (move constructor) })); Mirroring the custom constructor changes, ``py::pickle()`` is now the preferred way to get and set object state. See :ref:`pickling` for details. .. code-block:: cpp // old -- deprecated (runtime warning shown only in debug mode) py::class(m, "Foo") ... .def("__getstate__", [](const Foo &self) { return py::make_tuple(self.value1(), self.value2(), ...); }) .def("__setstate__", [](Foo &self, py::tuple t) { new (&self) Foo(t[0].cast(), ...); }); // new py::class(m, "Foo") ... .def(py::pickle( [](const Foo &self) { // __getstate__ return py::make_tuple(self.value1(), self.value2(), ...); // unchanged }, [](py::tuple t) { // __setstate__, note: no `self` argument return new Foo(t[0].cast(), ...); // or: return std::make_unique(...); // return by holder // or: return Foo(...); // return by value (move constructor) } )); For both the constructors and pickling, warnings are shown at module initialization time (on import, not when the functions are called). They're only visible when compiled in debug mode. Sample warning: .. code-block:: none pybind11-bound class 'mymodule.Foo' is using an old-style placement-new '__init__' which has been deprecated. See the upgrade guide in pybind11's docs. Stricter enforcement of hidden symbol visibility for pybind11 modules --------------------------------------------------------------------- pybind11 now tries to actively enforce hidden symbol visibility for modules. If you're using either one of pybind11's :doc:`CMake or Python build systems ` (the two example repositories) and you haven't been exporting any symbols, there's nothing to be concerned about. All the changes have been done transparently in the background. If you were building manually or relied on specific default visibility, read on. Setting default symbol visibility to *hidden* has always been recommended for pybind11 (see :ref:`faq:symhidden`). On Linux and macOS, hidden symbol visibility (in conjunction with the ``strip`` utility) yields much smaller module binaries. `CPython's extension docs`_ also recommend hiding symbols by default, with the goal of avoiding symbol name clashes between modules. Starting with v2.2, pybind11 enforces this more strictly: (1) by declaring all symbols inside the ``pybind11`` namespace as hidden and (2) by including the ``-fvisibility=hidden`` flag on Linux and macOS (only for extension modules, not for embedding the interpreter). .. _CPython's extension docs: https://docs.python.org/3/extending/extending.html#providing-a-c-api-for-an-extension-module The namespace-scope hidden visibility is done automatically in pybind11's headers and it's generally transparent to users. It ensures that: * Modules compiled with different pybind11 versions don't clash with each other. * Some new features, like ``py::module_local`` bindings, can work as intended. The ``-fvisibility=hidden`` flag applies the same visibility to user bindings outside of the ``pybind11`` namespace. It's now set automatic by pybind11's CMake and Python build systems, but this needs to be done manually by users of other build systems. Adding this flag: * Minimizes the chances of symbol conflicts between modules. E.g. if two unrelated modules were statically linked to different (ABI-incompatible) versions of the same third-party library, a symbol clash would be likely (and would end with unpredictable results). * Produces smaller binaries on Linux and macOS, as pointed out previously. Within pybind11's CMake build system, ``pybind11_add_module`` has always been setting the ``-fvisibility=hidden`` flag in release mode. From now on, it's being applied unconditionally, even in debug mode and it can no longer be opted out of with the ``NO_EXTRAS`` option. The ``pybind11::module`` target now also adds this flag to its interface. The ``pybind11::embed`` target is unchanged. The most significant change here is for the ``pybind11::module`` target. If you were previously relying on default visibility, i.e. if your Python module was doubling as a shared library with dependents, you'll need to either export symbols manually (recommended for cross-platform libraries) or factor out the shared library (and have the Python module link to it like the other dependents). As a temporary workaround, you can also restore default visibility using the CMake code below, but this is not recommended in the long run: .. code-block:: cmake target_link_libraries(mymodule PRIVATE pybind11::module) add_library(restore_default_visibility INTERFACE) target_compile_options(restore_default_visibility INTERFACE -fvisibility=default) target_link_libraries(mymodule PRIVATE restore_default_visibility) Local STL container bindings ---------------------------- Previous pybind11 versions could only bind types globally -- all pybind11 modules, even unrelated ones, would have access to the same exported types. However, this would also result in a conflict if two modules exported the same C++ type, which is especially problematic for very common types, e.g. ``std::vector``. :ref:`module_local` were added to resolve this (see that section for a complete usage guide). ``py::class_`` still defaults to global bindings (because these types are usually unique across modules), however in order to avoid clashes of opaque types, ``py::bind_vector`` and ``py::bind_map`` will now bind STL containers as ``py::module_local`` if their elements are: builtins (``int``, ``float``, etc.), not bound using ``py::class_``, or bound as ``py::module_local``. For example, this change allows multiple modules to bind ``std::vector`` without causing conflicts. See :ref:`stl_bind` for more details. When upgrading to this version, if you have multiple modules which depend on a single global binding of an STL container, note that all modules can still accept foreign ``py::module_local`` types in the direction of Python-to-C++. The locality only affects the C++-to-Python direction. If this is needed in multiple modules, you'll need to either: * Add a copy of the same STL binding to all of the modules which need it. * Restore the global status of that single binding by marking it ``py::module_local(false)``. The latter is an easy workaround, but in the long run it would be best to localize all common type bindings in order to avoid conflicts with third-party modules. Negative strides for Python buffer objects and numpy arrays ----------------------------------------------------------- Support for negative strides required changing the integer type from unsigned to signed in the interfaces of ``py::buffer_info`` and ``py::array``. If you have compiler warnings enabled, you may notice some new conversion warnings after upgrading. These can be resolved using ``static_cast``. Deprecation of some ``py::object`` APIs --------------------------------------- To compare ``py::object`` instances by pointer, you should now use ``obj1.is(obj2)`` which is equivalent to ``obj1 is obj2`` in Python. Previously, pybind11 used ``operator==`` for this (``obj1 == obj2``), but that could be confusing and is now deprecated (so that it can eventually be replaced with proper rich object comparison in a future release). For classes which inherit from ``py::object``, ``borrowed`` and ``stolen`` were previously available as protected constructor tags. Now the types should be used directly instead: ``borrowed_t{}`` and ``stolen_t{}`` (`#771 `_). Stricter compile-time error checking ------------------------------------ Some error checks have been moved from run time to compile time. Notably, automatic conversion of ``std::shared_ptr`` is not possible when ``T`` is not directly registered with ``py::class_`` (e.g. ``std::shared_ptr`` or ``std::shared_ptr>`` are not automatically convertible). Attempting to bind a function with such arguments now results in a compile-time error instead of waiting to fail at run time. ``py::init<...>()`` constructor definitions are also stricter and now prevent bindings which could cause unexpected behavior: .. code-block:: cpp struct Example { Example(int &); }; py::class_(m, "Example") .def(py::init()); // OK, exact match // .def(py::init()); // compile-time error, mismatch A non-``const`` lvalue reference is not allowed to bind to an rvalue. However, note that a constructor taking ``const T &`` can still be registered using ``py::init()`` because a ``const`` lvalue reference can bind to an rvalue. v2.1 ==== Minimum compiler versions are enforced at compile time ------------------------------------------------------ The minimums also apply to v2.0 but the check is now explicit and a compile-time error is raised if the compiler does not meet the requirements: * GCC >= 4.8 * clang >= 3.3 (appleclang >= 5.0) * MSVC >= 2015u3 * Intel C++ >= 15.0 The ``py::metaclass`` attribute is not required for static properties --------------------------------------------------------------------- Binding classes with static properties is now possible by default. The zero-parameter version of ``py::metaclass()`` is deprecated. However, a new one-parameter ``py::metaclass(python_type)`` version was added for rare cases when a custom metaclass is needed to override pybind11's default. .. code-block:: cpp // old -- emits a deprecation warning py::class_(m, "Foo", py::metaclass()) .def_property_readonly_static("foo", ...); // new -- static properties work without the attribute py::class_(m, "Foo") .def_property_readonly_static("foo", ...); // new -- advanced feature, override pybind11's default metaclass py::class_(m, "Bar", py::metaclass(custom_python_type)) ... v2.0 ==== Breaking changes in ``py::class_`` ---------------------------------- These changes were necessary to make type definitions in pybind11 future-proof, to support PyPy via its ``cpyext`` mechanism (`#527 `_), and to improve efficiency (`rev. 86d825 `_). 1. Declarations of types that provide access via the buffer protocol must now include the ``py::buffer_protocol()`` annotation as an argument to the ``py::class_`` constructor. .. code-block:: cpp py::class_("Matrix", py::buffer_protocol()) .def(py::init<...>()) .def_buffer(...); 2. Classes which include static properties (e.g. ``def_readwrite_static()``) must now include the ``py::metaclass()`` attribute. Note: this requirement has since been removed in v2.1. If you're upgrading from 1.x, it's recommended to skip directly to v2.1 or newer. 3. This version of pybind11 uses a redesigned mechanism for instantiating trampoline classes that are used to override virtual methods from within Python. This led to the following user-visible syntax change: .. code-block:: cpp // old v1.x syntax py::class_("MyClass") .alias() ... // new v2.x syntax py::class_("MyClass") ... Importantly, both the original and the trampoline class are now specified as arguments to the ``py::class_`` template, and the ``alias<..>()`` call is gone. The new scheme has zero overhead in cases when Python doesn't override any functions of the underlying C++ class. `rev. 86d825 `_. The class type must be the first template argument given to ``py::class_`` while the trampoline can be mixed in arbitrary order with other arguments (see the following section). Deprecation of the ``py::base()`` attribute ---------------------------------------------- ``py::base()`` was deprecated in favor of specifying ``T`` as a template argument to ``py::class_``. This new syntax also supports multiple inheritance. Note that, while the type being exported must be the first argument in the ``py::class_`` template, the order of the following types (bases, holder and/or trampoline) is not important. .. code-block:: cpp // old v1.x py::class_("Derived", py::base()); // new v2.x py::class_("Derived"); // new -- multiple inheritance py::class_("Derived"); // new -- apart from `Derived` the argument order can be arbitrary py::class_("Derived"); Out-of-the-box support for ``std::shared_ptr`` ---------------------------------------------- The relevant type caster is now built in, so it's no longer necessary to include a declaration of the form: .. code-block:: cpp PYBIND11_DECLARE_HOLDER_TYPE(T, std::shared_ptr) Continuing to do so won't cause an error or even a deprecation warning, but it's completely redundant. Deprecation of a few ``py::object`` APIs ---------------------------------------- All of the old-style calls emit deprecation warnings. +---------------------------------------+---------------------------------------------+ | Old syntax | New syntax | +=======================================+=============================================+ | ``obj.call(args...)`` | ``obj(args...)`` | +---------------------------------------+---------------------------------------------+ | ``obj.str()`` | ``py::str(obj)`` | +---------------------------------------+---------------------------------------------+ | ``auto l = py::list(obj); l.check()`` | ``py::isinstance(obj)`` | +---------------------------------------+---------------------------------------------+ | ``py::object(ptr, true)`` | ``py::reinterpret_borrow(ptr)`` | +---------------------------------------+---------------------------------------------+ | ``py::object(ptr, false)`` | ``py::reinterpret_steal(ptr)`` | +---------------------------------------+---------------------------------------------+ | ``if (obj.attr("foo"))`` | ``if (py::hasattr(obj, "foo"))`` | +---------------------------------------+---------------------------------------------+ | ``if (obj["bar"])`` | ``if (obj.contains("bar"))`` | +---------------------------------------+---------------------------------------------+ pybind11-2.13.6/include/000077500000000000000000000000001467115402600146635ustar00rootroot00000000000000pybind11-2.13.6/include/pybind11/000077500000000000000000000000001467115402600163125ustar00rootroot00000000000000pybind11-2.13.6/include/pybind11/attr.h000066400000000000000000000574161467115402600174520ustar00rootroot00000000000000/* pybind11/attr.h: Infrastructure for processing custom type and function attributes Copyright (c) 2016 Wenzel Jakob All rights reserved. Use of this source code is governed by a BSD-style license that can be found in the LICENSE file. */ #pragma once #include "detail/common.h" #include "cast.h" #include PYBIND11_NAMESPACE_BEGIN(PYBIND11_NAMESPACE) /// \addtogroup annotations /// @{ /// Annotation for methods struct is_method { handle class_; explicit is_method(const handle &c) : class_(c) {} }; /// Annotation for setters struct is_setter {}; /// Annotation for operators struct is_operator {}; /// Annotation for classes that cannot be subclassed struct is_final {}; /// Annotation for parent scope struct scope { handle value; explicit scope(const handle &s) : value(s) {} }; /// Annotation for documentation struct doc { const char *value; explicit doc(const char *value) : value(value) {} }; /// Annotation for function names struct name { const char *value; explicit name(const char *value) : value(value) {} }; /// Annotation indicating that a function is an overload associated with a given "sibling" struct sibling { handle value; explicit sibling(const handle &value) : value(value.ptr()) {} }; /// Annotation indicating that a class derives from another given type template struct base { PYBIND11_DEPRECATED( "base() was deprecated in favor of specifying 'T' as a template argument to class_") base() = default; }; /// Keep patient alive while nurse lives template struct keep_alive {}; /// Annotation indicating that a class is involved in a multiple inheritance relationship struct multiple_inheritance {}; /// Annotation which enables dynamic attributes, i.e. adds `__dict__` to a class struct dynamic_attr {}; /// Annotation which enables the buffer protocol for a type struct buffer_protocol {}; /// Annotation which requests that a special metaclass is created for a type struct metaclass { handle value; PYBIND11_DEPRECATED("py::metaclass() is no longer required. It's turned on by default now.") metaclass() = default; /// Override pybind11's default metaclass explicit metaclass(handle value) : value(value) {} }; /// Specifies a custom callback with signature `void (PyHeapTypeObject*)` that /// may be used to customize the Python type. /// /// The callback is invoked immediately before `PyType_Ready`. /// /// Note: This is an advanced interface, and uses of it may require changes to /// work with later versions of pybind11. You may wish to consult the /// implementation of `make_new_python_type` in `detail/classes.h` to understand /// the context in which the callback will be run. struct custom_type_setup { using callback = std::function; explicit custom_type_setup(callback value) : value(std::move(value)) {} callback value; }; /// Annotation that marks a class as local to the module: struct module_local { const bool value; constexpr explicit module_local(bool v = true) : value(v) {} }; /// Annotation to mark enums as an arithmetic type struct arithmetic {}; /// Mark a function for addition at the beginning of the existing overload chain instead of the end struct prepend {}; /** \rst A call policy which places one or more guard variables (``Ts...``) around the function call. For example, this definition: .. code-block:: cpp m.def("foo", foo, py::call_guard()); is equivalent to the following pseudocode: .. code-block:: cpp m.def("foo", [](args...) { T scope_guard; return foo(args...); // forwarded arguments }); \endrst */ template struct call_guard; template <> struct call_guard<> { using type = detail::void_type; }; template struct call_guard { static_assert(std::is_default_constructible::value, "The guard type must be default constructible"); using type = T; }; template struct call_guard { struct type { T guard{}; // Compose multiple guard types with left-to-right default-constructor order typename call_guard::type next{}; }; }; /// @} annotations PYBIND11_NAMESPACE_BEGIN(detail) /* Forward declarations */ enum op_id : int; enum op_type : int; struct undefined_t; template struct op_; void keep_alive_impl(size_t Nurse, size_t Patient, function_call &call, handle ret); /// Internal data structure which holds metadata about a keyword argument struct argument_record { const char *name; ///< Argument name const char *descr; ///< Human-readable version of the argument value handle value; ///< Associated Python object bool convert : 1; ///< True if the argument is allowed to convert when loading bool none : 1; ///< True if None is allowed when loading argument_record(const char *name, const char *descr, handle value, bool convert, bool none) : name(name), descr(descr), value(value), convert(convert), none(none) {} }; /// Internal data structure which holds metadata about a bound function (signature, overloads, /// etc.) struct function_record { function_record() : is_constructor(false), is_new_style_constructor(false), is_stateless(false), is_operator(false), is_method(false), is_setter(false), has_args(false), has_kwargs(false), prepend(false) {} /// Function name char *name = nullptr; /* why no C++ strings? They generate heavier code.. */ // User-specified documentation string char *doc = nullptr; /// Human-readable version of the function signature char *signature = nullptr; /// List of registered keyword arguments std::vector args; /// Pointer to lambda function which converts arguments and performs the actual call handle (*impl)(function_call &) = nullptr; /// Storage for the wrapped function pointer and captured data, if any void *data[3] = {}; /// Pointer to custom destructor for 'data' (if needed) void (*free_data)(function_record *ptr) = nullptr; /// Return value policy associated with this function return_value_policy policy = return_value_policy::automatic; /// True if name == '__init__' bool is_constructor : 1; /// True if this is a new-style `__init__` defined in `detail/init.h` bool is_new_style_constructor : 1; /// True if this is a stateless function pointer bool is_stateless : 1; /// True if this is an operator (__add__), etc. bool is_operator : 1; /// True if this is a method bool is_method : 1; /// True if this is a setter bool is_setter : 1; /// True if the function has a '*args' argument bool has_args : 1; /// True if the function has a '**kwargs' argument bool has_kwargs : 1; /// True if this function is to be inserted at the beginning of the overload resolution chain bool prepend : 1; /// Number of arguments (including py::args and/or py::kwargs, if present) std::uint16_t nargs; /// Number of leading positional arguments, which are terminated by a py::args or py::kwargs /// argument or by a py::kw_only annotation. std::uint16_t nargs_pos = 0; /// Number of leading arguments (counted in `nargs`) that are positional-only std::uint16_t nargs_pos_only = 0; /// Python method object PyMethodDef *def = nullptr; /// Python handle to the parent scope (a class or a module) handle scope; /// Python handle to the sibling function representing an overload chain handle sibling; /// Pointer to next overload function_record *next = nullptr; }; /// Special data structure which (temporarily) holds metadata about a bound class struct type_record { PYBIND11_NOINLINE type_record() : multiple_inheritance(false), dynamic_attr(false), buffer_protocol(false), default_holder(true), module_local(false), is_final(false) {} /// Handle to the parent scope handle scope; /// Name of the class const char *name = nullptr; // Pointer to RTTI type_info data structure const std::type_info *type = nullptr; /// How large is the underlying C++ type? size_t type_size = 0; /// What is the alignment of the underlying C++ type? size_t type_align = 0; /// How large is the type's holder? size_t holder_size = 0; /// The global operator new can be overridden with a class-specific variant void *(*operator_new)(size_t) = nullptr; /// Function pointer to class_<..>::init_instance void (*init_instance)(instance *, const void *) = nullptr; /// Function pointer to class_<..>::dealloc void (*dealloc)(detail::value_and_holder &) = nullptr; /// List of base classes of the newly created type list bases; /// Optional docstring const char *doc = nullptr; /// Custom metaclass (optional) handle metaclass; /// Custom type setup. custom_type_setup::callback custom_type_setup_callback; /// Multiple inheritance marker bool multiple_inheritance : 1; /// Does the class manage a __dict__? bool dynamic_attr : 1; /// Does the class implement the buffer protocol? bool buffer_protocol : 1; /// Is the default (unique_ptr) holder type used? bool default_holder : 1; /// Is the class definition local to the module shared object? bool module_local : 1; /// Is the class inheritable from python classes? bool is_final : 1; PYBIND11_NOINLINE void add_base(const std::type_info &base, void *(*caster)(void *) ) { auto *base_info = detail::get_type_info(base, false); if (!base_info) { std::string tname(base.name()); detail::clean_type_id(tname); pybind11_fail("generic_type: type \"" + std::string(name) + "\" referenced unknown base type \"" + tname + "\""); } if (default_holder != base_info->default_holder) { std::string tname(base.name()); detail::clean_type_id(tname); pybind11_fail("generic_type: type \"" + std::string(name) + "\" " + (default_holder ? "does not have" : "has") + " a non-default holder type while its base \"" + tname + "\" " + (base_info->default_holder ? "does not" : "does")); } bases.append((PyObject *) base_info->type); #if PY_VERSION_HEX < 0x030B0000 dynamic_attr |= base_info->type->tp_dictoffset != 0; #else dynamic_attr |= (base_info->type->tp_flags & Py_TPFLAGS_MANAGED_DICT) != 0; #endif if (caster) { base_info->implicit_casts.emplace_back(type, caster); } } }; inline function_call::function_call(const function_record &f, handle p) : func(f), parent(p) { args.reserve(f.nargs); args_convert.reserve(f.nargs); } /// Tag for a new-style `__init__` defined in `detail/init.h` struct is_new_style_constructor {}; /** * Partial template specializations to process custom attributes provided to * cpp_function_ and class_. These are either used to initialize the respective * fields in the type_record and function_record data structures or executed at * runtime to deal with custom call policies (e.g. keep_alive). */ template struct process_attribute; template struct process_attribute_default { /// Default implementation: do nothing static void init(const T &, function_record *) {} static void init(const T &, type_record *) {} static void precall(function_call &) {} static void postcall(function_call &, handle) {} }; /// Process an attribute specifying the function's name template <> struct process_attribute : process_attribute_default { static void init(const name &n, function_record *r) { r->name = const_cast(n.value); } }; /// Process an attribute specifying the function's docstring template <> struct process_attribute : process_attribute_default { static void init(const doc &n, function_record *r) { r->doc = const_cast(n.value); } }; /// Process an attribute specifying the function's docstring (provided as a C-style string) template <> struct process_attribute : process_attribute_default { static void init(const char *d, function_record *r) { r->doc = const_cast(d); } static void init(const char *d, type_record *r) { r->doc = d; } }; template <> struct process_attribute : process_attribute {}; /// Process an attribute indicating the function's return value policy template <> struct process_attribute : process_attribute_default { static void init(const return_value_policy &p, function_record *r) { r->policy = p; } }; /// Process an attribute which indicates that this is an overloaded function associated with a /// given sibling template <> struct process_attribute : process_attribute_default { static void init(const sibling &s, function_record *r) { r->sibling = s.value; } }; /// Process an attribute which indicates that this function is a method template <> struct process_attribute : process_attribute_default { static void init(const is_method &s, function_record *r) { r->is_method = true; r->scope = s.class_; } }; /// Process an attribute which indicates that this function is a setter template <> struct process_attribute : process_attribute_default { static void init(const is_setter &, function_record *r) { r->is_setter = true; } }; /// Process an attribute which indicates the parent scope of a method template <> struct process_attribute : process_attribute_default { static void init(const scope &s, function_record *r) { r->scope = s.value; } }; /// Process an attribute which indicates that this function is an operator template <> struct process_attribute : process_attribute_default { static void init(const is_operator &, function_record *r) { r->is_operator = true; } }; template <> struct process_attribute : process_attribute_default { static void init(const is_new_style_constructor &, function_record *r) { r->is_new_style_constructor = true; } }; inline void check_kw_only_arg(const arg &a, function_record *r) { if (r->args.size() > r->nargs_pos && (!a.name || a.name[0] == '\0')) { pybind11_fail("arg(): cannot specify an unnamed argument after a kw_only() annotation or " "args() argument"); } } inline void append_self_arg_if_needed(function_record *r) { if (r->is_method && r->args.empty()) { r->args.emplace_back("self", nullptr, handle(), /*convert=*/true, /*none=*/false); } } /// Process a keyword argument attribute (*without* a default value) template <> struct process_attribute : process_attribute_default { static void init(const arg &a, function_record *r) { append_self_arg_if_needed(r); r->args.emplace_back(a.name, nullptr, handle(), !a.flag_noconvert, a.flag_none); check_kw_only_arg(a, r); } }; /// Process a keyword argument attribute (*with* a default value) template <> struct process_attribute : process_attribute_default { static void init(const arg_v &a, function_record *r) { if (r->is_method && r->args.empty()) { r->args.emplace_back( "self", /*descr=*/nullptr, /*parent=*/handle(), /*convert=*/true, /*none=*/false); } if (!a.value) { #if defined(PYBIND11_DETAILED_ERROR_MESSAGES) std::string descr("'"); if (a.name) { descr += std::string(a.name) + ": "; } descr += a.type + "'"; if (r->is_method) { if (r->name) { descr += " in method '" + (std::string) str(r->scope) + "." + (std::string) r->name + "'"; } else { descr += " in method of '" + (std::string) str(r->scope) + "'"; } } else if (r->name) { descr += " in function '" + (std::string) r->name + "'"; } pybind11_fail("arg(): could not convert default argument " + descr + " into a Python object (type not registered yet?)"); #else pybind11_fail("arg(): could not convert default argument " "into a Python object (type not registered yet?). " "#define PYBIND11_DETAILED_ERROR_MESSAGES or compile in debug mode for " "more information."); #endif } r->args.emplace_back(a.name, a.descr, a.value.inc_ref(), !a.flag_noconvert, a.flag_none); check_kw_only_arg(a, r); } }; /// Process a keyword-only-arguments-follow pseudo argument template <> struct process_attribute : process_attribute_default { static void init(const kw_only &, function_record *r) { append_self_arg_if_needed(r); if (r->has_args && r->nargs_pos != static_cast(r->args.size())) { pybind11_fail("Mismatched args() and kw_only(): they must occur at the same relative " "argument location (or omit kw_only() entirely)"); } r->nargs_pos = static_cast(r->args.size()); } }; /// Process a positional-only-argument maker template <> struct process_attribute : process_attribute_default { static void init(const pos_only &, function_record *r) { append_self_arg_if_needed(r); r->nargs_pos_only = static_cast(r->args.size()); if (r->nargs_pos_only > r->nargs_pos) { pybind11_fail("pos_only(): cannot follow a py::args() argument"); } // It also can't follow a kw_only, but a static_assert in pybind11.h checks that } }; /// Process a parent class attribute. Single inheritance only (class_ itself already guarantees /// that) template struct process_attribute::value>> : process_attribute_default { static void init(const handle &h, type_record *r) { r->bases.append(h); } }; /// Process a parent class attribute (deprecated, does not support multiple inheritance) template struct process_attribute> : process_attribute_default> { static void init(const base &, type_record *r) { r->add_base(typeid(T), nullptr); } }; /// Process a multiple inheritance attribute template <> struct process_attribute : process_attribute_default { static void init(const multiple_inheritance &, type_record *r) { r->multiple_inheritance = true; } }; template <> struct process_attribute : process_attribute_default { static void init(const dynamic_attr &, type_record *r) { r->dynamic_attr = true; } }; template <> struct process_attribute { static void init(const custom_type_setup &value, type_record *r) { r->custom_type_setup_callback = value.value; } }; template <> struct process_attribute : process_attribute_default { static void init(const is_final &, type_record *r) { r->is_final = true; } }; template <> struct process_attribute : process_attribute_default { static void init(const buffer_protocol &, type_record *r) { r->buffer_protocol = true; } }; template <> struct process_attribute : process_attribute_default { static void init(const metaclass &m, type_record *r) { r->metaclass = m.value; } }; template <> struct process_attribute : process_attribute_default { static void init(const module_local &l, type_record *r) { r->module_local = l.value; } }; /// Process a 'prepend' attribute, putting this at the beginning of the overload chain template <> struct process_attribute : process_attribute_default { static void init(const prepend &, function_record *r) { r->prepend = true; } }; /// Process an 'arithmetic' attribute for enums (does nothing here) template <> struct process_attribute : process_attribute_default {}; template struct process_attribute> : process_attribute_default> {}; /** * Process a keep_alive call policy -- invokes keep_alive_impl during the * pre-call handler if both Nurse, Patient != 0 and use the post-call handler * otherwise */ template struct process_attribute> : public process_attribute_default> { template = 0> static void precall(function_call &call) { keep_alive_impl(Nurse, Patient, call, handle()); } template = 0> static void postcall(function_call &, handle) {} template = 0> static void precall(function_call &) {} template = 0> static void postcall(function_call &call, handle ret) { keep_alive_impl(Nurse, Patient, call, ret); } }; /// Recursively iterate over variadic template arguments template struct process_attributes { static void init(const Args &...args, function_record *r) { PYBIND11_WORKAROUND_INCORRECT_MSVC_C4100(r); PYBIND11_WORKAROUND_INCORRECT_GCC_UNUSED_BUT_SET_PARAMETER(r); using expander = int[]; (void) expander{ 0, ((void) process_attribute::type>::init(args, r), 0)...}; } static void init(const Args &...args, type_record *r) { PYBIND11_WORKAROUND_INCORRECT_MSVC_C4100(r); PYBIND11_WORKAROUND_INCORRECT_GCC_UNUSED_BUT_SET_PARAMETER(r); using expander = int[]; (void) expander{0, (process_attribute::type>::init(args, r), 0)...}; } static void precall(function_call &call) { PYBIND11_WORKAROUND_INCORRECT_MSVC_C4100(call); using expander = int[]; (void) expander{0, (process_attribute::type>::precall(call), 0)...}; } static void postcall(function_call &call, handle fn_ret) { PYBIND11_WORKAROUND_INCORRECT_MSVC_C4100(call, fn_ret); PYBIND11_WORKAROUND_INCORRECT_GCC_UNUSED_BUT_SET_PARAMETER(fn_ret); using expander = int[]; (void) expander{ 0, (process_attribute::type>::postcall(call, fn_ret), 0)...}; } }; template using is_call_guard = is_instantiation; /// Extract the ``type`` from the first `call_guard` in `Extras...` (or `void_type` if none found) template using extract_guard_t = typename exactly_one_t, Extra...>::type; /// Check the number of named arguments at compile time template ::value...), size_t self = constexpr_sum(std::is_same::value...)> constexpr bool expected_num_args(size_t nargs, bool has_args, bool has_kwargs) { PYBIND11_WORKAROUND_INCORRECT_MSVC_C4100(nargs, has_args, has_kwargs); return named == 0 || (self + named + size_t(has_args) + size_t(has_kwargs)) == nargs; } PYBIND11_NAMESPACE_END(detail) PYBIND11_NAMESPACE_END(PYBIND11_NAMESPACE) pybind11-2.13.6/include/pybind11/buffer_info.h000066400000000000000000000171421467115402600207540ustar00rootroot00000000000000/* pybind11/buffer_info.h: Python buffer object interface Copyright (c) 2016 Wenzel Jakob All rights reserved. Use of this source code is governed by a BSD-style license that can be found in the LICENSE file. */ #pragma once #include "detail/common.h" PYBIND11_NAMESPACE_BEGIN(PYBIND11_NAMESPACE) PYBIND11_NAMESPACE_BEGIN(detail) // Default, C-style strides inline std::vector c_strides(const std::vector &shape, ssize_t itemsize) { auto ndim = shape.size(); std::vector strides(ndim, itemsize); if (ndim > 0) { for (size_t i = ndim - 1; i > 0; --i) { strides[i - 1] = strides[i] * shape[i]; } } return strides; } // F-style strides; default when constructing an array_t with `ExtraFlags & f_style` inline std::vector f_strides(const std::vector &shape, ssize_t itemsize) { auto ndim = shape.size(); std::vector strides(ndim, itemsize); for (size_t i = 1; i < ndim; ++i) { strides[i] = strides[i - 1] * shape[i - 1]; } return strides; } template struct compare_buffer_info; PYBIND11_NAMESPACE_END(detail) /// Information record describing a Python buffer object struct buffer_info { void *ptr = nullptr; // Pointer to the underlying storage ssize_t itemsize = 0; // Size of individual items in bytes ssize_t size = 0; // Total number of entries std::string format; // For homogeneous buffers, this should be set to // format_descriptor::format() ssize_t ndim = 0; // Number of dimensions std::vector shape; // Shape of the tensor (1 entry per dimension) std::vector strides; // Number of bytes between adjacent entries // (for each per dimension) bool readonly = false; // flag to indicate if the underlying storage may be written to buffer_info() = default; buffer_info(void *ptr, ssize_t itemsize, const std::string &format, ssize_t ndim, detail::any_container shape_in, detail::any_container strides_in, bool readonly = false) : ptr(ptr), itemsize(itemsize), size(1), format(format), ndim(ndim), shape(std::move(shape_in)), strides(std::move(strides_in)), readonly(readonly) { if (ndim != (ssize_t) shape.size() || ndim != (ssize_t) strides.size()) { pybind11_fail("buffer_info: ndim doesn't match shape and/or strides length"); } for (size_t i = 0; i < (size_t) ndim; ++i) { size *= shape[i]; } } template buffer_info(T *ptr, detail::any_container shape_in, detail::any_container strides_in, bool readonly = false) : buffer_info(private_ctr_tag(), ptr, sizeof(T), format_descriptor::format(), static_cast(shape_in->size()), std::move(shape_in), std::move(strides_in), readonly) {} buffer_info(void *ptr, ssize_t itemsize, const std::string &format, ssize_t size, bool readonly = false) : buffer_info(ptr, itemsize, format, 1, {size}, {itemsize}, readonly) {} template buffer_info(T *ptr, ssize_t size, bool readonly = false) : buffer_info(ptr, sizeof(T), format_descriptor::format(), size, readonly) {} template buffer_info(const T *ptr, ssize_t size, bool readonly = true) : buffer_info( const_cast(ptr), sizeof(T), format_descriptor::format(), size, readonly) {} explicit buffer_info(Py_buffer *view, bool ownview = true) : buffer_info( view->buf, view->itemsize, view->format, view->ndim, {view->shape, view->shape + view->ndim}, /* Though buffer::request() requests PyBUF_STRIDES, ctypes objects * ignore this flag and return a view with NULL strides. * When strides are NULL, build them manually. */ view->strides ? std::vector(view->strides, view->strides + view->ndim) : detail::c_strides({view->shape, view->shape + view->ndim}, view->itemsize), (view->readonly != 0)) { // NOLINTNEXTLINE(cppcoreguidelines-prefer-member-initializer) this->m_view = view; // NOLINTNEXTLINE(cppcoreguidelines-prefer-member-initializer) this->ownview = ownview; } buffer_info(const buffer_info &) = delete; buffer_info &operator=(const buffer_info &) = delete; buffer_info(buffer_info &&other) noexcept { (*this) = std::move(other); } buffer_info &operator=(buffer_info &&rhs) noexcept { ptr = rhs.ptr; itemsize = rhs.itemsize; size = rhs.size; format = std::move(rhs.format); ndim = rhs.ndim; shape = std::move(rhs.shape); strides = std::move(rhs.strides); std::swap(m_view, rhs.m_view); std::swap(ownview, rhs.ownview); readonly = rhs.readonly; return *this; } ~buffer_info() { if (m_view && ownview) { PyBuffer_Release(m_view); delete m_view; } } Py_buffer *view() const { return m_view; } Py_buffer *&view() { return m_view; } /* True if the buffer item type is equivalent to `T`. */ // To define "equivalent" by example: // `buffer_info::item_type_is_equivalent_to(b)` and // `buffer_info::item_type_is_equivalent_to(b)` may both be true // on some platforms, but `int` and `unsigned` will never be equivalent. // For the ground truth, please inspect `detail::compare_buffer_info<>`. template bool item_type_is_equivalent_to() const { return detail::compare_buffer_info::compare(*this); } private: struct private_ctr_tag {}; buffer_info(private_ctr_tag, void *ptr, ssize_t itemsize, const std::string &format, ssize_t ndim, detail::any_container &&shape_in, detail::any_container &&strides_in, bool readonly) : buffer_info( ptr, itemsize, format, ndim, std::move(shape_in), std::move(strides_in), readonly) {} Py_buffer *m_view = nullptr; bool ownview = false; }; PYBIND11_NAMESPACE_BEGIN(detail) template struct compare_buffer_info { static bool compare(const buffer_info &b) { // NOLINTNEXTLINE(bugprone-sizeof-expression) Needed for `PyObject *` return b.format == format_descriptor::format() && b.itemsize == (ssize_t) sizeof(T); } }; template struct compare_buffer_info::value>> { static bool compare(const buffer_info &b) { return (size_t) b.itemsize == sizeof(T) && (b.format == format_descriptor::value || ((sizeof(T) == sizeof(long)) && b.format == (std::is_unsigned::value ? "L" : "l")) || ((sizeof(T) == sizeof(size_t)) && b.format == (std::is_unsigned::value ? "N" : "n"))); } }; PYBIND11_NAMESPACE_END(detail) PYBIND11_NAMESPACE_END(PYBIND11_NAMESPACE) pybind11-2.13.6/include/pybind11/cast.h000066400000000000000000002140201467115402600174140ustar00rootroot00000000000000/* pybind11/cast.h: Partial template specializations to cast between C++ and Python types Copyright (c) 2016 Wenzel Jakob All rights reserved. Use of this source code is governed by a BSD-style license that can be found in the LICENSE file. */ #pragma once #include "detail/common.h" #include "detail/descr.h" #include "detail/type_caster_base.h" #include "detail/typeid.h" #include "pytypes.h" #include #include #include #include #include #include #include #include #include #include #include PYBIND11_NAMESPACE_BEGIN(PYBIND11_NAMESPACE) PYBIND11_WARNING_DISABLE_MSVC(4127) PYBIND11_NAMESPACE_BEGIN(detail) template class type_caster : public type_caster_base {}; template using make_caster = type_caster>; // Shortcut for calling a caster's `cast_op_type` cast operator for casting a type_caster to a T template typename make_caster::template cast_op_type cast_op(make_caster &caster) { using result_t = typename make_caster::template cast_op_type; // See PR #4893 return caster.operator result_t(); } template typename make_caster::template cast_op_type::type> cast_op(make_caster &&caster) { using result_t = typename make_caster::template cast_op_type< typename std::add_rvalue_reference::type>; // See PR #4893 return std::move(caster).operator result_t(); } template class type_caster> { private: using caster_t = make_caster; caster_t subcaster; using reference_t = type &; using subcaster_cast_op_type = typename caster_t::template cast_op_type; static_assert( std::is_same::type &, subcaster_cast_op_type>::value || std::is_same::value, "std::reference_wrapper caster requires T to have a caster with an " "`operator T &()` or `operator const T &()`"); public: bool load(handle src, bool convert) { return subcaster.load(src, convert); } static constexpr auto name = caster_t::name; static handle cast(const std::reference_wrapper &src, return_value_policy policy, handle parent) { // It is definitely wrong to take ownership of this pointer, so mask that rvp if (policy == return_value_policy::take_ownership || policy == return_value_policy::automatic) { policy = return_value_policy::automatic_reference; } return caster_t::cast(&src.get(), policy, parent); } template using cast_op_type = std::reference_wrapper; explicit operator std::reference_wrapper() { return cast_op(subcaster); } }; #define PYBIND11_TYPE_CASTER(type, py_name) \ protected: \ type value; \ \ public: \ static constexpr auto name = py_name; \ template >::value, \ int> \ = 0> \ static ::pybind11::handle cast( \ T_ *src, ::pybind11::return_value_policy policy, ::pybind11::handle parent) { \ if (!src) \ return ::pybind11::none().release(); \ if (policy == ::pybind11::return_value_policy::take_ownership) { \ auto h = cast(std::move(*src), policy, parent); \ delete src; \ return h; \ } \ return cast(*src, policy, parent); \ } \ operator type *() { return &value; } /* NOLINT(bugprone-macro-parentheses) */ \ operator type &() { return value; } /* NOLINT(bugprone-macro-parentheses) */ \ operator type &&() && { return std::move(value); } /* NOLINT(bugprone-macro-parentheses) */ \ template \ using cast_op_type = ::pybind11::detail::movable_cast_op_type template using is_std_char_type = any_of, /* std::string */ #if defined(PYBIND11_HAS_U8STRING) std::is_same, /* std::u8string */ #endif std::is_same, /* std::u16string */ std::is_same, /* std::u32string */ std::is_same /* std::wstring */ >; template struct type_caster::value && !is_std_char_type::value>> { using _py_type_0 = conditional_t; using _py_type_1 = conditional_t::value, _py_type_0, typename std::make_unsigned<_py_type_0>::type>; using py_type = conditional_t::value, double, _py_type_1>; public: bool load(handle src, bool convert) { py_type py_value; if (!src) { return false; } #if !defined(PYPY_VERSION) auto index_check = [](PyObject *o) { return PyIndex_Check(o); }; #else // In PyPy 7.3.3, `PyIndex_Check` is implemented by calling `__index__`, // while CPython only considers the existence of `nb_index`/`__index__`. auto index_check = [](PyObject *o) { return hasattr(o, "__index__"); }; #endif if (std::is_floating_point::value) { if (convert || PyFloat_Check(src.ptr())) { py_value = (py_type) PyFloat_AsDouble(src.ptr()); } else { return false; } } else if (PyFloat_Check(src.ptr()) || (!convert && !PYBIND11_LONG_CHECK(src.ptr()) && !index_check(src.ptr()))) { return false; } else { handle src_or_index = src; // PyPy: 7.3.7's 3.8 does not implement PyLong_*'s __index__ calls. #if PY_VERSION_HEX < 0x03080000 || defined(PYPY_VERSION) object index; if (!PYBIND11_LONG_CHECK(src.ptr())) { // So: index_check(src.ptr()) index = reinterpret_steal(PyNumber_Index(src.ptr())); if (!index) { PyErr_Clear(); if (!convert) return false; } else { src_or_index = index; } } #endif if (std::is_unsigned::value) { py_value = as_unsigned(src_or_index.ptr()); } else { // signed integer: py_value = sizeof(T) <= sizeof(long) ? (py_type) PyLong_AsLong(src_or_index.ptr()) : (py_type) PYBIND11_LONG_AS_LONGLONG(src_or_index.ptr()); } } // Python API reported an error bool py_err = py_value == (py_type) -1 && PyErr_Occurred(); // Check to see if the conversion is valid (integers should match exactly) // Signed/unsigned checks happen elsewhere if (py_err || (std::is_integral::value && sizeof(py_type) != sizeof(T) && py_value != (py_type) (T) py_value)) { PyErr_Clear(); if (py_err && convert && (PyNumber_Check(src.ptr()) != 0)) { auto tmp = reinterpret_steal(std::is_floating_point::value ? PyNumber_Float(src.ptr()) : PyNumber_Long(src.ptr())); PyErr_Clear(); return load(tmp, false); } return false; } value = (T) py_value; return true; } template static typename std::enable_if::value, handle>::type cast(U src, return_value_policy /* policy */, handle /* parent */) { return PyFloat_FromDouble((double) src); } template static typename std::enable_if::value && std::is_signed::value && (sizeof(U) <= sizeof(long)), handle>::type cast(U src, return_value_policy /* policy */, handle /* parent */) { return PYBIND11_LONG_FROM_SIGNED((long) src); } template static typename std::enable_if::value && std::is_unsigned::value && (sizeof(U) <= sizeof(unsigned long)), handle>::type cast(U src, return_value_policy /* policy */, handle /* parent */) { return PYBIND11_LONG_FROM_UNSIGNED((unsigned long) src); } template static typename std::enable_if::value && std::is_signed::value && (sizeof(U) > sizeof(long)), handle>::type cast(U src, return_value_policy /* policy */, handle /* parent */) { return PyLong_FromLongLong((long long) src); } template static typename std::enable_if::value && std::is_unsigned::value && (sizeof(U) > sizeof(unsigned long)), handle>::type cast(U src, return_value_policy /* policy */, handle /* parent */) { return PyLong_FromUnsignedLongLong((unsigned long long) src); } PYBIND11_TYPE_CASTER(T, const_name::value>("int", "float")); }; template struct void_caster { public: bool load(handle src, bool) { if (src && src.is_none()) { return true; } return false; } static handle cast(T, return_value_policy /* policy */, handle /* parent */) { return none().release(); } PYBIND11_TYPE_CASTER(T, const_name("None")); }; template <> class type_caster : public void_caster {}; template <> class type_caster : public type_caster { public: using type_caster::cast; bool load(handle h, bool) { if (!h) { return false; } if (h.is_none()) { value = nullptr; return true; } /* Check if this is a capsule */ if (isinstance(h)) { value = reinterpret_borrow(h); return true; } /* Check if this is a C++ type */ const auto &bases = all_type_info((PyTypeObject *) type::handle_of(h).ptr()); if (bases.size() == 1) { // Only allowing loading from a single-value type value = values_and_holders(reinterpret_cast(h.ptr())).begin()->value_ptr(); return true; } /* Fail */ return false; } static handle cast(const void *ptr, return_value_policy /* policy */, handle /* parent */) { if (ptr) { return capsule(ptr).release(); } return none().release(); } template using cast_op_type = void *&; explicit operator void *&() { return value; } static constexpr auto name = const_name("capsule"); private: void *value = nullptr; }; template <> class type_caster : public void_caster {}; template <> class type_caster { public: bool load(handle src, bool convert) { if (!src) { return false; } if (src.ptr() == Py_True) { value = true; return true; } if (src.ptr() == Py_False) { value = false; return true; } if (convert || is_numpy_bool(src)) { // (allow non-implicit conversion for numpy booleans), use strncmp // since NumPy 1.x had an additional trailing underscore. Py_ssize_t res = -1; if (src.is_none()) { res = 0; // None is implicitly converted to False } #if defined(PYPY_VERSION) // On PyPy, check that "__bool__" attr exists else if (hasattr(src, PYBIND11_BOOL_ATTR)) { res = PyObject_IsTrue(src.ptr()); } #else // Alternate approach for CPython: this does the same as the above, but optimized // using the CPython API so as to avoid an unneeded attribute lookup. else if (auto *tp_as_number = src.ptr()->ob_type->tp_as_number) { if (PYBIND11_NB_BOOL(tp_as_number)) { res = (*PYBIND11_NB_BOOL(tp_as_number))(src.ptr()); } } #endif if (res == 0 || res == 1) { value = (res != 0); return true; } PyErr_Clear(); } return false; } static handle cast(bool src, return_value_policy /* policy */, handle /* parent */) { return handle(src ? Py_True : Py_False).inc_ref(); } PYBIND11_TYPE_CASTER(bool, const_name("bool")); private: // Test if an object is a NumPy boolean (without fetching the type). static inline bool is_numpy_bool(handle object) { const char *type_name = Py_TYPE(object.ptr())->tp_name; // Name changed to `numpy.bool` in NumPy 2, `numpy.bool_` is needed for 1.x support return std::strcmp("numpy.bool", type_name) == 0 || std::strcmp("numpy.bool_", type_name) == 0; } }; // Helper class for UTF-{8,16,32} C++ stl strings: template struct string_caster { using CharT = typename StringType::value_type; // Simplify life by being able to assume standard char sizes (the standard only guarantees // minimums, but Python requires exact sizes) static_assert(!std::is_same::value || sizeof(CharT) == 1, "Unsupported char size != 1"); #if defined(PYBIND11_HAS_U8STRING) static_assert(!std::is_same::value || sizeof(CharT) == 1, "Unsupported char8_t size != 1"); #endif static_assert(!std::is_same::value || sizeof(CharT) == 2, "Unsupported char16_t size != 2"); static_assert(!std::is_same::value || sizeof(CharT) == 4, "Unsupported char32_t size != 4"); // wchar_t can be either 16 bits (Windows) or 32 (everywhere else) static_assert(!std::is_same::value || sizeof(CharT) == 2 || sizeof(CharT) == 4, "Unsupported wchar_t size != 2/4"); static constexpr size_t UTF_N = 8 * sizeof(CharT); bool load(handle src, bool) { handle load_src = src; if (!src) { return false; } if (!PyUnicode_Check(load_src.ptr())) { return load_raw(load_src); } // For UTF-8 we avoid the need for a temporary `bytes` object by using // `PyUnicode_AsUTF8AndSize`. if (UTF_N == 8) { Py_ssize_t size = -1; const auto *buffer = reinterpret_cast(PyUnicode_AsUTF8AndSize(load_src.ptr(), &size)); if (!buffer) { PyErr_Clear(); return false; } value = StringType(buffer, static_cast(size)); return true; } auto utfNbytes = reinterpret_steal(PyUnicode_AsEncodedString(load_src.ptr(), UTF_N == 8 ? "utf-8" : UTF_N == 16 ? "utf-16" : "utf-32", nullptr)); if (!utfNbytes) { PyErr_Clear(); return false; } const auto *buffer = reinterpret_cast(PYBIND11_BYTES_AS_STRING(utfNbytes.ptr())); size_t length = (size_t) PYBIND11_BYTES_SIZE(utfNbytes.ptr()) / sizeof(CharT); // Skip BOM for UTF-16/32 if (UTF_N > 8) { buffer++; length--; } value = StringType(buffer, length); // If we're loading a string_view we need to keep the encoded Python object alive: if (IsView) { loader_life_support::add_patient(utfNbytes); } return true; } static handle cast(const StringType &src, return_value_policy /* policy */, handle /* parent */) { const char *buffer = reinterpret_cast(src.data()); auto nbytes = ssize_t(src.size() * sizeof(CharT)); handle s = decode_utfN(buffer, nbytes); if (!s) { throw error_already_set(); } return s; } PYBIND11_TYPE_CASTER(StringType, const_name(PYBIND11_STRING_NAME)); private: static handle decode_utfN(const char *buffer, ssize_t nbytes) { #if !defined(PYPY_VERSION) return UTF_N == 8 ? PyUnicode_DecodeUTF8(buffer, nbytes, nullptr) : UTF_N == 16 ? PyUnicode_DecodeUTF16(buffer, nbytes, nullptr, nullptr) : PyUnicode_DecodeUTF32(buffer, nbytes, nullptr, nullptr); #else // PyPy segfaults when on PyUnicode_DecodeUTF16 (and possibly on PyUnicode_DecodeUTF32 as // well), so bypass the whole thing by just passing the encoding as a string value, which // works properly: return PyUnicode_Decode(buffer, nbytes, UTF_N == 8 ? "utf-8" : UTF_N == 16 ? "utf-16" : "utf-32", nullptr); #endif } // When loading into a std::string or char*, accept a bytes/bytearray object as-is (i.e. // without any encoding/decoding attempt). For other C++ char sizes this is a no-op. // which supports loading a unicode from a str, doesn't take this path. template bool load_raw(enable_if_t::value, handle> src) { if (PYBIND11_BYTES_CHECK(src.ptr())) { // We were passed raw bytes; accept it into a std::string or char* // without any encoding attempt. const char *bytes = PYBIND11_BYTES_AS_STRING(src.ptr()); if (!bytes) { pybind11_fail("Unexpected PYBIND11_BYTES_AS_STRING() failure."); } value = StringType(bytes, (size_t) PYBIND11_BYTES_SIZE(src.ptr())); return true; } if (PyByteArray_Check(src.ptr())) { // We were passed a bytearray; accept it into a std::string or char* // without any encoding attempt. const char *bytearray = PyByteArray_AsString(src.ptr()); if (!bytearray) { pybind11_fail("Unexpected PyByteArray_AsString() failure."); } value = StringType(bytearray, (size_t) PyByteArray_Size(src.ptr())); return true; } return false; } template bool load_raw(enable_if_t::value, handle>) { return false; } }; template struct type_caster, enable_if_t::value>> : string_caster> {}; #ifdef PYBIND11_HAS_STRING_VIEW template struct type_caster, enable_if_t::value>> : string_caster, true> {}; #endif // Type caster for C-style strings. We basically use a std::string type caster, but also add the // ability to use None as a nullptr char* (which the string caster doesn't allow). template struct type_caster::value>> { using StringType = std::basic_string; using StringCaster = make_caster; StringCaster str_caster; bool none = false; CharT one_char = 0; public: bool load(handle src, bool convert) { if (!src) { return false; } if (src.is_none()) { // Defer accepting None to other overloads (if we aren't in convert mode): if (!convert) { return false; } none = true; return true; } return str_caster.load(src, convert); } static handle cast(const CharT *src, return_value_policy policy, handle parent) { if (src == nullptr) { return pybind11::none().release(); } return StringCaster::cast(StringType(src), policy, parent); } static handle cast(CharT src, return_value_policy policy, handle parent) { if (std::is_same::value) { handle s = PyUnicode_DecodeLatin1((const char *) &src, 1, nullptr); if (!s) { throw error_already_set(); } return s; } return StringCaster::cast(StringType(1, src), policy, parent); } explicit operator CharT *() { return none ? nullptr : const_cast(static_cast(str_caster).c_str()); } explicit operator CharT &() { if (none) { throw value_error("Cannot convert None to a character"); } auto &value = static_cast(str_caster); size_t str_len = value.size(); if (str_len == 0) { throw value_error("Cannot convert empty string to a character"); } // If we're in UTF-8 mode, we have two possible failures: one for a unicode character that // is too high, and one for multiple unicode characters (caught later), so we need to // figure out how long the first encoded character is in bytes to distinguish between these // two errors. We also allow want to allow unicode characters U+0080 through U+00FF, as // those can fit into a single char value. if (StringCaster::UTF_N == 8 && str_len > 1 && str_len <= 4) { auto v0 = static_cast(value[0]); // low bits only: 0-127 // 0b110xxxxx - start of 2-byte sequence // 0b1110xxxx - start of 3-byte sequence // 0b11110xxx - start of 4-byte sequence size_t char0_bytes = (v0 & 0x80) == 0 ? 1 : (v0 & 0xE0) == 0xC0 ? 2 : (v0 & 0xF0) == 0xE0 ? 3 : 4; if (char0_bytes == str_len) { // If we have a 128-255 value, we can decode it into a single char: if (char0_bytes == 2 && (v0 & 0xFC) == 0xC0) { // 0x110000xx 0x10xxxxxx one_char = static_cast(((v0 & 3) << 6) + (static_cast(value[1]) & 0x3F)); return one_char; } // Otherwise we have a single character, but it's > U+00FF throw value_error("Character code point not in range(0x100)"); } } // UTF-16 is much easier: we can only have a surrogate pair for values above U+FFFF, thus a // surrogate pair with total length 2 instantly indicates a range error (but not a "your // string was too long" error). else if (StringCaster::UTF_N == 16 && str_len == 2) { one_char = static_cast(value[0]); if (one_char >= 0xD800 && one_char < 0xE000) { throw value_error("Character code point not in range(0x10000)"); } } if (str_len != 1) { throw value_error("Expected a character, but multi-character string found"); } one_char = value[0]; return one_char; } static constexpr auto name = const_name(PYBIND11_STRING_NAME); template using cast_op_type = pybind11::detail::cast_op_type<_T>; }; // Base implementation for std::tuple and std::pair template