././@PaxHeader0000000000000000000000000000003400000000000011452 xustar000000000000000028 mtime=1631883775.1376212 more-itertools-8.10.0/0000775000175000017500000000000000000000000013611 5ustar00bobo00000000000000././@PaxHeader0000000000000000000000000000002600000000000011453 xustar000000000000000022 mtime=1541986671.0 more-itertools-8.10.0/LICENSE0000644000175000017500000000203500000000000014614 0ustar00bobo00000000000000Copyright (c) 2012 Erik Rose Permission is hereby granted, free of charge, to any person obtaining a copy of this software and associated documentation files (the "Software"), to deal in the Software without restriction, including without limitation the rights to use, copy, modify, merge, publish, distribute, sublicense, and/or sell copies of the Software, and to permit persons to whom the Software is furnished to do so, subject to the following conditions: The above copyright notice and this permission notice shall be included in all copies or substantial portions of the Software. THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY, FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM, OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE SOFTWARE. ././@PaxHeader0000000000000000000000000000002600000000000011453 xustar000000000000000022 mtime=1575634598.0 more-itertools-8.10.0/MANIFEST.in0000644000175000017500000000030400000000000015342 0ustar00bobo00000000000000include README.rst include LICENSE include docs/*.rst include docs/Makefile include docs/make.bat include docs/conf.py include docs/_static/* include fabfile.py include tox.ini include tests/*.py ././@PaxHeader0000000000000000000000000000003400000000000011452 xustar000000000000000028 mtime=1631883775.1376212 more-itertools-8.10.0/PKG-INFO0000664000175000017500000010776400000000000014725 0ustar00bobo00000000000000Metadata-Version: 2.1 Name: more-itertools Version: 8.10.0 Summary: More routines for operating on iterables, beyond itertools Home-page: https://github.com/more-itertools/more-itertools Author: Erik Rose Author-email: erikrose@grinchcentral.com License: MIT Keywords: itertools,iterator,iteration,filter,peek,peekable,collate,chunk,chunked Platform: UNKNOWN Classifier: Development Status :: 5 - Production/Stable Classifier: Intended Audience :: Developers Classifier: Natural Language :: English Classifier: License :: OSI Approved :: MIT License Classifier: Programming Language :: Python :: 3 Classifier: Programming Language :: Python :: 3.6 Classifier: Programming Language :: Python :: 3.7 Classifier: Programming Language :: Python :: 3.8 Classifier: Programming Language :: Python :: 3.9 Classifier: Programming Language :: Python :: 3 :: Only Classifier: Programming Language :: Python :: Implementation :: CPython Classifier: Programming Language :: Python :: Implementation :: PyPy Classifier: Topic :: Software Development :: Libraries Requires-Python: >=3.5 Description-Content-Type: text/x-rst License-File: LICENSE ============== More Itertools ============== .. image:: https://readthedocs.org/projects/more-itertools/badge/?version=latest :target: https://more-itertools.readthedocs.io/en/stable/ Python's ``itertools`` library is a gem - you can compose elegant solutions for a variety of problems with the functions it provides. In ``more-itertools`` we collect additional building blocks, recipes, and routines for working with Python iterables. +------------------------+-----------------------------------------------------------------------------------------------------------------------------------------------------------------------------+ | Grouping | `chunked `_, | | | `ichunked `_, | | | `sliced `_, | | | `distribute `_, | | | `divide `_, | | | `split_at `_, | | | `split_before `_, | | | `split_after `_, | | | `split_into `_, | | | `split_when `_, | | | `bucket `_, | | | `unzip `_, | | | `grouper `_, | | | `partition `_ | +------------------------+-----------------------------------------------------------------------------------------------------------------------------------------------------------------------------+ | Lookahead and lookback | `spy `_, | | | `peekable `_, | | | `seekable `_ | +------------------------+-----------------------------------------------------------------------------------------------------------------------------------------------------------------------------+ | Windowing | `windowed `_, | | | `substrings `_, | | | `substrings_indexes `_, | | | `stagger `_, | | | `windowed_complete `_, | | | `pairwise `_ | +------------------------+-----------------------------------------------------------------------------------------------------------------------------------------------------------------------------+ | Augmenting | `count_cycle `_, | | | `intersperse `_, | | | `padded `_, | | | `mark_ends `_, | | | `repeat_last `_, | | | `adjacent `_, | | | `groupby_transform `_, | | | `pad_none `_, | | | `ncycles `_ | +------------------------+-----------------------------------------------------------------------------------------------------------------------------------------------------------------------------+ | Combining | `collapse `_, | | | `sort_together `_, | | | `interleave `_, | | | `interleave_longest `_, | | | `interleave_evenly `_, | | | `zip_offset `_, | | | `zip_equal `_, | | | `zip_broadcast `_, | | | `dotproduct `_, | | | `convolve `_, | | | `flatten `_, | | | `roundrobin `_, | | | `prepend `_, | | | `value_chain `_ | +------------------------+-----------------------------------------------------------------------------------------------------------------------------------------------------------------------------+ | Summarizing | `ilen `_, | | | `unique_to_each `_, | | | `sample `_, | | | `consecutive_groups `_, | | | `run_length `_, | | | `map_reduce `_, | | | `exactly_n `_, | | | `is_sorted `_, | | | `all_equal `_, | | | `all_unique `_, | | | `first_true `_, | | | `quantify `_ | +------------------------+-----------------------------------------------------------------------------------------------------------------------------------------------------------------------------+ | Selecting | `islice_extended `_, | | | `first `_, | | | `last `_, | | | `one `_, | | | `only `_, | | | `strip `_, | | | `lstrip `_, | | | `rstrip `_, | | | `filter_except `_ | | | `map_except `_ | | | `nth_or_last `_, | | | `nth `_, | | | `take `_, | | | `tail `_, | | | `unique_everseen `_, | | | `unique_justseen `_ | +------------------------+-----------------------------------------------------------------------------------------------------------------------------------------------------------------------------+ | Combinatorics | `distinct_permutations `_, | | | `distinct_combinations `_, | | | `circular_shifts `_, | | | `partitions `_, | | | `set_partitions `_, | | | `product_index `_, | | | `combination_index `_, | | | `permutation_index `_, | | | `powerset `_, | | | `random_product `_, | | | `random_permutation `_, | | | `random_combination `_, | | | `random_combination_with_replacement `_, | | | `nth_product `_ | | | `nth_permutation `_ | | | `nth_combination `_ | +------------------------+-----------------------------------------------------------------------------------------------------------------------------------------------------------------------------+ | Wrapping | `always_iterable `_, | | | `always_reversible `_, | | | `countable `_, | | | `consumer `_, | | | `with_iter `_, | | | `iter_except `_ | +------------------------+-----------------------------------------------------------------------------------------------------------------------------------------------------------------------------+ | Others | `locate `_, | | | `rlocate `_, | | | `replace `_, | | | `numeric_range `_, | | | `side_effect `_, | | | `iterate `_, | | | `difference `_, | | | `make_decorator `_, | | | `SequenceView `_, | | | `time_limited `_, | | | `consume `_, | | | `tabulate `_, | | | `repeatfunc `_ | +------------------------+-----------------------------------------------------------------------------------------------------------------------------------------------------------------------------+ Getting started =============== To get started, install the library with `pip `_: .. code-block:: shell pip install more-itertools The recipes from the `itertools docs `_ are included in the top-level package: .. code-block:: python >>> from more_itertools import flatten >>> iterable = [(0, 1), (2, 3)] >>> list(flatten(iterable)) [0, 1, 2, 3] Several new recipes are available as well: .. code-block:: python >>> from more_itertools import chunked >>> iterable = [0, 1, 2, 3, 4, 5, 6, 7, 8] >>> list(chunked(iterable, 3)) [[0, 1, 2], [3, 4, 5], [6, 7, 8]] >>> from more_itertools import spy >>> iterable = (x * x for x in range(1, 6)) >>> head, iterable = spy(iterable, n=3) >>> list(head) [1, 4, 9] >>> list(iterable) [1, 4, 9, 16, 25] For the full listing of functions, see the `API documentation `_. Links elsewhere =============== Blog posts about ``more-itertools``: * `Yo, I heard you like decorators `__ * `Tour of Python Itertools `__ (`Alternate `__) Development =========== ``more-itertools`` is maintained by `@erikrose `_ and `@bbayles `_, with help from `many others `_. If you have a problem or suggestion, please file a bug or pull request in this repository. Thanks for contributing! Version History =============== :noindex: 8.10.0 ------ * Changes to existing functions * The type stub for iter_except was improved (thanks to MarcinKonowalczyk) * Other changes: * Type stubs now ship with the source release (thanks to saaketp) * The Sphinx docs were improved (thanks to MarcinKonowalczyk) 8.9.0 ----- * New functions * interleave_evenly (thanks to mbugert) * repeat_each (thanks to FinalSh4re) * chunked_even (thanks to valtron) * map_if (thanks to sassbalint) * zip_broadcast (thanks to kalekundert) * Changes to existing functions * The type stub for chunked was improved (thanks to PhilMacKay) * The type stubs for zip_equal and `zip_offset` were improved (thanks to maffoo) * Building Sphinx docs locally was improved (thanks to MarcinKonowalczyk) 8.8.0 ----- * New functions * countable (thanks to krzysieq) * Changes to existing functions * split_before was updated to handle empy collections (thanks to TiunovNN) * unique_everseen got a performance boost (thanks to Numerlor) * The type hint for value_chain was corrected (thanks to vr2262) 8.7.0 ----- * New functions * convolve (from the Python itertools docs) * product_index, combination_index, and permutation_index (thanks to N8Brooks) * value_chain (thanks to jenstroeger) * Changes to existing functions * distinct_combinations now uses a non-recursive algorithm (thanks to knutdrand) * pad_none is now the preferred name for padnone, though the latter remains available. * pairwise will now use the Python standard library implementation on Python 3.10+ * sort_together now accepts a ``key`` argument (thanks to brianmaissy) * seekable now has a ``peek`` method, and can indicate whether the iterator it's wrapping is exhausted (thanks to gsakkis) * time_limited can now indicate whether its iterator has expired (thanks to roysmith) * The implementation of unique_everseen was improved (thanks to plammens) * Other changes: * Various documentation updates (thanks to cthoyt, Evantm, and cyphase) 8.6.0 ----- * New itertools * all_unique (thanks to brianmaissy) * nth_product and nth_permutation (thanks to N8Brooks) * Changes to existing itertools * chunked and sliced now accept a ``strict`` parameter (thanks to shlomif and jtwool) * Other changes * Python 3.5 has reached its end of life and is no longer supported. * Python 3.9 is officially supported. * Various documentation fixes (thanks to timgates42) 8.5.0 ----- * New itertools * windowed_complete (thanks to MarcinKonowalczyk) * Changes to existing itertools: * The is_sorted implementation was improved (thanks to cool-RR) * The groupby_transform now accepts a ``reducefunc`` parameter. * The last implementation was improved (thanks to brianmaissy) * Other changes * Various documentation fixes (thanks to craigrosie, samuelstjean, PiCT0) * The tests for distinct_combinations were improved (thanks to Minabsapi) * Automated tests now run on GitHub Actions. All commits now check: * That unit tests pass * That the examples in docstrings work * That test coverage remains high (using `coverage`) * For linting errors (using `flake8`) * For consistent style (using `black`) * That the type stubs work (using `mypy`) * That the docs build correctly (using `sphinx`) * That packages build correctly (using `twine`) 8.4.0 ----- * New itertools * mark_ends (thanks to kalekundert) * is_sorted * Changes to existing itertools: * islice_extended can now be used with real slices (thanks to cool-RR) * The implementations for filter_except and map_except were improved (thanks to SergBobrovsky) * Other changes * Automated tests now enforce code style (using `black `__) * The various signatures of islice_extended and numeric_range now appear in the docs (thanks to dsfulf) * The test configuration for mypy was updated (thanks to blueyed) 8.3.0 ----- * New itertools * zip_equal (thanks to frankier and alexmojaki) * Changes to existing itertools: * split_at, split_before, split_after, and split_when all got a ``maxsplit`` paramter (thanks to jferard and ilai-deutel) * split_at now accepts a ``keep_separator`` parameter (thanks to jferard) * distinct_permutations can now generate ``r``-length permutations (thanks to SergBobrovsky and ilai-deutel) * The windowed implementation was improved (thanks to SergBobrovsky) * The spy implementation was improved (thanks to has2k1) * Other changes * Type stubs are now tested with ``stubtest`` (thanks to ilai-deutel) * Tests now run with ``python -m unittest`` instead of ``python setup.py test`` (thanks to jdufresne) 8.2.0 ----- * Bug fixes * The .pyi files for typing were updated. (thanks to blueyed and ilai-deutel) * Changes to existing itertools: * numeric_range now behaves more like the built-in range. (thanks to jferard) * bucket now allows for enumerating keys. (thanks to alexchandel) * sliced now should now work for numpy arrays. (thanks to sswingle) * seekable now has a ``maxlen`` parameter. 8.1.0 ----- * Bug fixes * partition works with ``pred=None`` again. (thanks to MSeifert04) * New itertools * sample (thanks to tommyod) * nth_or_last (thanks to d-ryzhikov) * Changes to existing itertools: * The implementation for divide was improved. (thanks to jferard) 8.0.2 ----- * Bug fixes * The type stub files are now part of the wheel distribution (thanks to keisheiled) 8.0.1 ----- * Bug fixes * The type stub files now work for functions imported from the root package (thanks to keisheiled) 8.0.0 ----- * New itertools and other additions * This library now ships type hints for use with mypy. (thanks to ilai-deutel for the implementation, and to gabbard and fmagin for assistance) * split_when (thanks to jferard) * repeat_last (thanks to d-ryzhikov) * Changes to existing itertools: * The implementation for set_partitions was improved. (thanks to jferard) * partition was optimized for expensive predicates. (thanks to stevecj) * unique_everseen and groupby_transform were re-factored. (thanks to SergBobrovsky) * The implementation for difference was improved. (thanks to Jabbey92) * Other changes * Python 3.4 has reached its end of life and is no longer supported. * Python 3.8 is officially supported. (thanks to jdufresne) * The ``collate`` function has been deprecated. It raises a ``DeprecationWarning`` if used, and will be removed in a future release. * one and only now provide more informative error messages. (thanks to gabbard) * Unit tests were moved outside of the main package (thanks to jdufresne) * Various documentation fixes (thanks to kriomant, gabbard, jdufresne) 7.2.0 ----- * New itertools * distinct_combinations * set_partitions (thanks to kbarrett) * filter_except * map_except 7.1.0 ----- * New itertools * ichunked (thanks davebelais and youtux) * only (thanks jaraco) * Changes to existing itertools: * numeric_range now supports ranges specified by ``datetime.datetime`` and ``datetime.timedelta`` objects (thanks to MSeifert04 for tests). * difference now supports an *initial* keyword argument. * Other changes * Various documentation fixes (thanks raimon49, pylang) 7.0.0 ----- * New itertools: * time_limited * partitions (thanks to rominf and Saluev) * substrings_indexes (thanks to rominf) * Changes to existing itertools: * collapse now treats ``bytes`` objects the same as ``str`` objects. (thanks to Sweenpet) The major version update is due to the change in the default behavior of collapse. It now treats ``bytes`` objects the same as ``str`` objects. This aligns its behavior with always_iterable. .. code-block:: python >>> from more_itertools import collapse >>> iterable = [[1, 2], b'345', [6]] >>> print(list(collapse(iterable))) [1, 2, b'345', 6] 6.0.0 ----- * Major changes: * Python 2.7 is no longer supported. The 5.0.0 release will be the last version targeting Python 2.7. * All future releases will target the active versions of Python 3. As of 2019, those are Python 3.4 and above. * The ``six`` library is no longer a dependency. * The accumulate function is no longer part of this library. You may import a better version from the standard ``itertools`` module. * Changes to existing itertools: * The order of the parameters in grouper have changed to match the latest recipe in the itertools documentation. Use of the old order will be supported in this release, but emit a ``DeprecationWarning``. The legacy behavior will be dropped in a future release. (thanks to jaraco) * distinct_permutations was improved (thanks to jferard - see also `permutations with unique values `_ at StackOverflow.) * An unused parameter was removed from substrings. (thanks to pylang) * Other changes: * The docs for unique_everseen were improved. (thanks to jferard and MSeifert04) * Several Python 2-isms were removed. (thanks to jaraco, MSeifert04, and hugovk) ././@PaxHeader0000000000000000000000000000002600000000000011453 xustar000000000000000022 mtime=1631476336.0 more-itertools-8.10.0/README.rst0000664000175000017500000006324200000000000015307 0ustar00bobo00000000000000============== More Itertools ============== .. image:: https://readthedocs.org/projects/more-itertools/badge/?version=latest :target: https://more-itertools.readthedocs.io/en/stable/ Python's ``itertools`` library is a gem - you can compose elegant solutions for a variety of problems with the functions it provides. In ``more-itertools`` we collect additional building blocks, recipes, and routines for working with Python iterables. +------------------------+-----------------------------------------------------------------------------------------------------------------------------------------------------------------------------+ | Grouping | `chunked `_, | | | `ichunked `_, | | | `sliced `_, | | | `distribute `_, | | | `divide `_, | | | `split_at `_, | | | `split_before `_, | | | `split_after `_, | | | `split_into `_, | | | `split_when `_, | | | `bucket `_, | | | `unzip `_, | | | `grouper `_, | | | `partition `_ | +------------------------+-----------------------------------------------------------------------------------------------------------------------------------------------------------------------------+ | Lookahead and lookback | `spy `_, | | | `peekable `_, | | | `seekable `_ | +------------------------+-----------------------------------------------------------------------------------------------------------------------------------------------------------------------------+ | Windowing | `windowed `_, | | | `substrings `_, | | | `substrings_indexes `_, | | | `stagger `_, | | | `windowed_complete `_, | | | `pairwise `_ | +------------------------+-----------------------------------------------------------------------------------------------------------------------------------------------------------------------------+ | Augmenting | `count_cycle `_, | | | `intersperse `_, | | | `padded `_, | | | `mark_ends `_, | | | `repeat_last `_, | | | `adjacent `_, | | | `groupby_transform `_, | | | `pad_none `_, | | | `ncycles `_ | +------------------------+-----------------------------------------------------------------------------------------------------------------------------------------------------------------------------+ | Combining | `collapse `_, | | | `sort_together `_, | | | `interleave `_, | | | `interleave_longest `_, | | | `interleave_evenly `_, | | | `zip_offset `_, | | | `zip_equal `_, | | | `zip_broadcast `_, | | | `dotproduct `_, | | | `convolve `_, | | | `flatten `_, | | | `roundrobin `_, | | | `prepend `_, | | | `value_chain `_ | +------------------------+-----------------------------------------------------------------------------------------------------------------------------------------------------------------------------+ | Summarizing | `ilen `_, | | | `unique_to_each `_, | | | `sample `_, | | | `consecutive_groups `_, | | | `run_length `_, | | | `map_reduce `_, | | | `exactly_n `_, | | | `is_sorted `_, | | | `all_equal `_, | | | `all_unique `_, | | | `first_true `_, | | | `quantify `_ | +------------------------+-----------------------------------------------------------------------------------------------------------------------------------------------------------------------------+ | Selecting | `islice_extended `_, | | | `first `_, | | | `last `_, | | | `one `_, | | | `only `_, | | | `strip `_, | | | `lstrip `_, | | | `rstrip `_, | | | `filter_except `_ | | | `map_except `_ | | | `nth_or_last `_, | | | `nth `_, | | | `take `_, | | | `tail `_, | | | `unique_everseen `_, | | | `unique_justseen `_ | +------------------------+-----------------------------------------------------------------------------------------------------------------------------------------------------------------------------+ | Combinatorics | `distinct_permutations `_, | | | `distinct_combinations `_, | | | `circular_shifts `_, | | | `partitions `_, | | | `set_partitions `_, | | | `product_index `_, | | | `combination_index `_, | | | `permutation_index `_, | | | `powerset `_, | | | `random_product `_, | | | `random_permutation `_, | | | `random_combination `_, | | | `random_combination_with_replacement `_, | | | `nth_product `_ | | | `nth_permutation `_ | | | `nth_combination `_ | +------------------------+-----------------------------------------------------------------------------------------------------------------------------------------------------------------------------+ | Wrapping | `always_iterable `_, | | | `always_reversible `_, | | | `countable `_, | | | `consumer `_, | | | `with_iter `_, | | | `iter_except `_ | +------------------------+-----------------------------------------------------------------------------------------------------------------------------------------------------------------------------+ | Others | `locate `_, | | | `rlocate `_, | | | `replace `_, | | | `numeric_range `_, | | | `side_effect `_, | | | `iterate `_, | | | `difference `_, | | | `make_decorator `_, | | | `SequenceView `_, | | | `time_limited `_, | | | `consume `_, | | | `tabulate `_, | | | `repeatfunc `_ | +------------------------+-----------------------------------------------------------------------------------------------------------------------------------------------------------------------------+ Getting started =============== To get started, install the library with `pip `_: .. code-block:: shell pip install more-itertools The recipes from the `itertools docs `_ are included in the top-level package: .. code-block:: python >>> from more_itertools import flatten >>> iterable = [(0, 1), (2, 3)] >>> list(flatten(iterable)) [0, 1, 2, 3] Several new recipes are available as well: .. code-block:: python >>> from more_itertools import chunked >>> iterable = [0, 1, 2, 3, 4, 5, 6, 7, 8] >>> list(chunked(iterable, 3)) [[0, 1, 2], [3, 4, 5], [6, 7, 8]] >>> from more_itertools import spy >>> iterable = (x * x for x in range(1, 6)) >>> head, iterable = spy(iterable, n=3) >>> list(head) [1, 4, 9] >>> list(iterable) [1, 4, 9, 16, 25] For the full listing of functions, see the `API documentation `_. Links elsewhere =============== Blog posts about ``more-itertools``: * `Yo, I heard you like decorators `__ * `Tour of Python Itertools `__ (`Alternate `__) Development =========== ``more-itertools`` is maintained by `@erikrose `_ and `@bbayles `_, with help from `many others `_. If you have a problem or suggestion, please file a bug or pull request in this repository. Thanks for contributing! ././@PaxHeader0000000000000000000000000000003400000000000011452 xustar000000000000000028 mtime=1631883775.1376212 more-itertools-8.10.0/docs/0000775000175000017500000000000000000000000014541 5ustar00bobo00000000000000././@PaxHeader0000000000000000000000000000002600000000000011453 xustar000000000000000022 mtime=1541986671.0 more-itertools-8.10.0/docs/Makefile0000644000175000017500000001273400000000000016206 0ustar00bobo00000000000000# Makefile for Sphinx documentation # # You can set these variables from the command line. 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The epub file is in $(BUILDDIR)/epub." latex: $(SPHINXBUILD) -b latex $(ALLSPHINXOPTS) $(BUILDDIR)/latex @echo @echo "Build finished; the LaTeX files are in $(BUILDDIR)/latex." @echo "Run \`make' in that directory to run these through (pdf)latex" \ "(use \`make latexpdf' here to do that automatically)." latexpdf: $(SPHINXBUILD) -b latex $(ALLSPHINXOPTS) $(BUILDDIR)/latex @echo "Running LaTeX files through pdflatex..." $(MAKE) -C $(BUILDDIR)/latex all-pdf @echo "pdflatex finished; the PDF files are in $(BUILDDIR)/latex." text: $(SPHINXBUILD) -b text $(ALLSPHINXOPTS) $(BUILDDIR)/text @echo @echo "Build finished. The text files are in $(BUILDDIR)/text." man: $(SPHINXBUILD) -b man $(ALLSPHINXOPTS) $(BUILDDIR)/man @echo @echo "Build finished. The manual pages are in $(BUILDDIR)/man." texinfo: $(SPHINXBUILD) -b texinfo $(ALLSPHINXOPTS) $(BUILDDIR)/texinfo @echo @echo "Build finished. The Texinfo files are in $(BUILDDIR)/texinfo." @echo "Run \`make' in that directory to run these through makeinfo" \ "(use \`make info' here to do that automatically)." info: $(SPHINXBUILD) -b texinfo $(ALLSPHINXOPTS) $(BUILDDIR)/texinfo @echo "Running Texinfo files through makeinfo..." make -C $(BUILDDIR)/texinfo info @echo "makeinfo finished; the Info files are in $(BUILDDIR)/texinfo." gettext: $(SPHINXBUILD) -b gettext $(I18NSPHINXOPTS) $(BUILDDIR)/locale @echo @echo "Build finished. The message catalogs are in $(BUILDDIR)/locale." changes: $(SPHINXBUILD) -b changes $(ALLSPHINXOPTS) $(BUILDDIR)/changes @echo @echo "The overview file is in $(BUILDDIR)/changes." linkcheck: $(SPHINXBUILD) -b linkcheck $(ALLSPHINXOPTS) $(BUILDDIR)/linkcheck @echo @echo "Link check complete; look for any errors in the above output " \ "or in $(BUILDDIR)/linkcheck/output.txt." doctest: $(SPHINXBUILD) -b doctest $(ALLSPHINXOPTS) $(BUILDDIR)/doctest @echo "Testing of doctests in the sources finished, look at the " \ "results in $(BUILDDIR)/doctest/output.txt." ././@PaxHeader0000000000000000000000000000003400000000000011452 xustar000000000000000028 mtime=1631883775.1376212 more-itertools-8.10.0/docs/_static/0000775000175000017500000000000000000000000016167 5ustar00bobo00000000000000././@PaxHeader0000000000000000000000000000002600000000000011453 xustar000000000000000022 mtime=1541986671.0 more-itertools-8.10.0/docs/_static/theme_overrides.css0000644000175000017500000000066500000000000022072 0ustar00bobo00000000000000/* https://rackerlabs.github.io/docs-rackspace/tools/rtd-tables.html */ /* override table width restrictions */ @media screen and (min-width: 767px) { .wy-table-responsive table td { /* !important prevents the common CSS stylesheets from overriding this as on RTD they are loaded after this stylesheet */ white-space: normal !important; } .wy-table-responsive { overflow: visible !important; } } ././@PaxHeader0000000000000000000000000000002600000000000011453 xustar000000000000000022 mtime=1631795601.0 more-itertools-8.10.0/docs/api.rst0000664000175000017500000001252200000000000016046 0ustar00bobo00000000000000============= API Reference ============= .. automodule:: more_itertools Grouping ======== These tools yield groups of items from a source iterable. ---- **New itertools** .. autofunction:: chunked .. autofunction:: ichunked .. autofunction:: chunked_even .. autofunction:: sliced .. autofunction:: distribute .. autofunction:: divide .. autofunction:: split_at .. autofunction:: split_before .. autofunction:: split_after .. autofunction:: split_into .. autofunction:: split_when .. autofunction:: bucket .. autofunction:: unzip ---- **Itertools recipes** .. autofunction:: grouper .. autofunction:: partition Lookahead and lookback ====================== These tools peek at an iterable's values without advancing it. ---- **New itertools** .. autofunction:: spy .. autoclass:: peekable .. autoclass:: seekable Windowing ========= These tools yield windows of items from an iterable. ---- **New itertools** .. autofunction:: windowed .. autofunction:: substrings .. autofunction:: substrings_indexes .. autofunction:: stagger .. autofunction:: windowed_complete ---- **Itertools recipes** .. autofunction:: pairwise Augmenting ========== These tools yield items from an iterable, plus additional data. ---- **New itertools** .. autofunction:: count_cycle .. autofunction:: intersperse .. autofunction:: padded .. autofunction:: mark_ends .. autofunction:: repeat_each .. autofunction:: repeat_last .. autofunction:: adjacent .. autofunction:: groupby_transform ---- **Itertools recipes** .. function:: padnone :noindex: .. autofunction:: pad_none .. autofunction:: ncycles Combining ========= These tools combine multiple iterables. ---- **New itertools** .. autofunction:: collapse .. autofunction:: interleave .. autofunction:: interleave_longest .. autofunction:: interleave_evenly .. autofunction:: sort_together .. autofunction:: value_chain .. autofunction:: zip_offset(*iterables, offsets, longest=False, fillvalue=None) .. autofunction:: zip_equal .. autofunction:: zip_broadcast(*objects, scalar_types=(str, bytes), strict=False) ---- **Itertools recipes** .. autofunction:: dotproduct .. autofunction:: convolve .. autofunction:: flatten .. autofunction:: roundrobin .. autofunction:: prepend Summarizing =========== These tools return summarized or aggregated data from an iterable. ---- **New itertools** .. autofunction:: ilen .. autofunction:: unique_to_each .. autofunction:: sample(iterable, k=1, weights=None) .. autofunction:: consecutive_groups(iterable, ordering=lambda x: x) .. autoclass:: run_length .. autofunction:: map_reduce .. autofunction:: exactly_n(iterable, n, predicate=bool) .. autofunction:: is_sorted .. autofunction:: all_unique ---- **Itertools recipes** .. autofunction:: all_equal .. autofunction:: first_true .. autofunction:: quantify(iterable, pred=bool) Selecting ========= These tools yield certain items from an iterable. ---- **New itertools** .. class:: islice_extended(iterable, stop) .. autoclass:: islice_extended(iterable, start, stop[, step]) :noindex: .. autofunction:: first(iterable[, default]) .. autofunction:: last(iterable[, default]) .. autofunction:: one(iterable, too_short=ValueError, too_long=ValueError) .. autofunction:: only(iterable, default=None, too_long=ValueError) .. autofunction:: strip .. autofunction:: lstrip .. autofunction:: rstrip .. autofunction:: filter_except .. autofunction:: map_except .. autofunction:: nth_or_last(iterable, n[, default]) ---- **Itertools recipes** .. autofunction:: nth .. autofunction:: take .. autofunction:: tail .. autofunction:: unique_everseen .. autofunction:: unique_justseen Combinatorics ============= These tools yield combinatorial arrangements of items from iterables. ---- **New itertools** .. autofunction:: distinct_permutations .. autofunction:: distinct_combinations .. autofunction:: circular_shifts .. autofunction:: partitions .. autofunction:: set_partitions .. autofunction:: product_index .. autofunction:: combination_index .. autofunction:: permutation_index ---- **Itertools recipes** .. autofunction:: powerset .. autofunction:: random_product .. autofunction:: random_permutation .. autofunction:: random_combination .. autofunction:: random_combination_with_replacement .. autofunction:: nth_product .. autofunction:: nth_permutation .. autofunction:: nth_combination Wrapping ======== These tools provide wrappers to smooth working with objects that produce or consume iterables. ---- **New itertools** .. autofunction:: always_iterable .. autofunction:: always_reversible .. autofunction:: countable .. autofunction:: consumer .. autofunction:: with_iter .. autoclass:: callback_iter ---- **Itertools recipes** .. autofunction:: iter_except Others ====== **New itertools** .. autofunction:: locate(iterable, pred=bool, window_size=None) .. autofunction:: rlocate(iterable, pred=bool, window_size=None) .. autofunction:: replace .. function:: numeric_range(stop) .. autofunction:: numeric_range(start, stop[, step]) :noindex: .. autofunction:: side_effect .. autofunction:: iterate .. autofunction:: difference(iterable, func=operator.sub, *, initial=None) .. autofunction:: make_decorator .. autoclass:: SequenceView .. autofunction:: time_limited .. autofunction:: map_if(iterable, pred, func, func_else=lambda x: x) ---- **Itertools recipes** .. autofunction:: consume .. autofunction:: tabulate .. autofunction:: repeatfunc ././@PaxHeader0000000000000000000000000000002600000000000011453 xustar000000000000000022 mtime=1631476336.0 more-itertools-8.10.0/docs/conf.py0000664000175000017500000002167600000000000016054 0ustar00bobo00000000000000# # more-itertools documentation build configuration file, created by # sphinx-quickstart on Mon Jun 25 20:42:39 2012. # # This file is execfile()d with the current directory set to its containing dir. # # Note that not all possible configuration values are present in this # autogenerated file. # # All configuration values have a default; values that are commented out # serve to show the default. import sys, os import sphinx_rtd_theme # 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('..')) import more_itertools # -- Preprocess README.rst ----------------------------------------------------- # We include README.rst from the root directory. It has absolute links # to readthedocs.io for display on github.com, but those links can be # relative when being built for Sphinx. with open('../README.rst', 'rt') as source: readme_file = source.readlines() build_dir = '_build' os.makedirs(build_dir, exist_ok=True) rtd_path = 'https://more-itertools.readthedocs.io/en/stable/' table_width = 200 in_table = False with open(os.path.join('.', build_dir, 'README.pprst'), 'wt') as target: for line in readme_file: old_len = len(line) if line.startswith('|') and line.endswith('|\n'): # Inside table line = line.replace(rtd_path, '').rstrip(' |\n') spaces = ' ' * (table_width - len(line) - 1) line = f'{line}{spaces}|\n' target.write(line) # -- General configuration ----------------------------------------------------- # If your documentation needs a minimal Sphinx version, state it here. # needs_sphinx = '1.0' # Add any Sphinx extension module names here, as strings. They can be extensions # coming with Sphinx (named 'sphinx.ext.*') or your custom ones. extensions = ['sphinx.ext.autodoc', 'sphinx.ext.viewcode'] # Add any paths that contain templates here, relative to this directory. templates_path = ['_templates'] # The suffix of source filenames. 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 = 'more-itertools' copyright = '2012, Erik Rose' # The version info for the project you're documenting, acts as replacement for # |version| and |release|, also used in various other places throughout the # built documents. # # The short X.Y version. version = more_itertools.__version__ # The full version, including alpha/beta/rc tags. release = version # The language for content autogenerated by Sphinx. Refer to documentation # for a list of supported languages. # language = None # There are two options for replacing |today|: either, you set today to some # non-false value, then it is used: # today = '' # Else, today_fmt is used as the format for a strftime call. # today_fmt = '%B %d, %Y' # List of patterns, relative to source directory, that match files and # directories to ignore when looking for source files. exclude_patterns = [build_dir] # The reST default role (used for this markup: `text`) to use for all documents. # default_role = None # If true, '()' will be appended to :func: etc. cross-reference text. # add_function_parentheses = True # If true, the current module name will be prepended to all description # unit titles (such as .. function::). # add_module_names = True # If true, sectionauthor and moduleauthor directives will be shown in the # output. They are ignored by default. # show_authors = False # The name of the Pygments (syntax highlighting) style to use. pygments_style = 'sphinx' # A list of ignored prefixes for module index sorting. # modindex_common_prefix = [] # -- Options for HTML output --------------------------------------------------- # The theme to use for HTML and HTML Help pages. See the documentation for # a list of builtin themes. html_theme = 'sphinx_rtd_theme' # Theme options are theme-specific and customize the look and feel of a theme # further. For a list of options available for each theme, see the # documentation. # html_theme_options = {} # Add any paths that contain custom themes here, relative to this directory. html_theme_path = [sphinx_rtd_theme.get_html_theme_path()] # The name for this set of Sphinx documents. If None, it defaults to # " v documentation". # html_title = None # A shorter title for the navigation bar. Default is the same as html_title. # html_short_title = None # The name of an image file (relative to this directory) to place at the top # of the sidebar. # html_logo = None # The name of an image file (within the static path) to use as favicon of the # docs. This file should be a Windows icon file (.ico) being 16x16 or 32x32 # pixels large. # html_favicon = None # Add any paths that contain custom static files (such as style sheets) here, # relative to this directory. They are copied after the builtin static files, # so a file named "default.css" will overwrite the builtin "default.css". html_static_path = ['_static'] html_context = { # https://rackerlabs.github.io/docs-rackspace/tools/rtd-tables.html 'css_files': ['_static/theme_overrides.css'], } # If not '', a 'Last updated on:' timestamp is inserted at every page bottom, # using the given strftime format. # html_last_updated_fmt = '%b %d, %Y' # If true, SmartyPants will be used to convert quotes and dashes to # typographically correct entities. # html_use_smartypants = True # Custom sidebar templates, maps document names to template names. # html_sidebars = {} # Additional templates that should be rendered to pages, maps page names to # template names. # html_additional_pages = {} # If false, no module index is generated. # html_domain_indices = True # If false, no index is generated. # html_use_index = True # If true, the index is split into individual pages for each letter. # html_split_index = False # If true, links to the reST sources are added to the pages. # html_show_sourcelink = True # If true, "Created using Sphinx" is shown in the HTML footer. Default is True. # html_show_sphinx = True # If true, "(C) Copyright ..." is shown in the HTML footer. Default is True. # html_show_copyright = True # If true, an OpenSearch description file will be output, and all pages will # contain a tag referring to it. The value of this option must be the # base URL from which the finished HTML is served. # html_use_opensearch = '' # This is the file name suffix for HTML files (e.g. ".xhtml"). # html_file_suffix = None # Output file base name for HTML help builder. htmlhelp_basename = 'more-itertoolsdoc' # -- Options for LaTeX output -------------------------------------------------- latex_elements = { # The paper size ('letterpaper' or 'a4paper'). #'papersize': 'letterpaper', # The font size ('10pt', '11pt' or '12pt'). #'pointsize': '10pt', # Additional stuff for the LaTeX preamble. #'preamble': '', } # Grouping the document tree into LaTeX files. List of tuples # (source start file, target name, title, author, documentclass [howto/manual]). latex_documents = [ ( 'index', 'more-itertools.tex', 'more-itertools Documentation', 'Erik Rose', 'manual', ), ] # The name of an image file (relative to this directory) to place at the top of # the title page. # latex_logo = None # For "manual" documents, if this is true, then toplevel headings are parts, # not chapters. # latex_use_parts = False # If true, show page references after internal links. # latex_show_pagerefs = False # If true, show URL addresses after external links. # latex_show_urls = False # Documents to append as an appendix to all manuals. # latex_appendices = [] # If false, no module index is generated. # latex_domain_indices = True # -- Options for manual page output -------------------------------------------- # One entry per manual page. List of tuples # (source start file, name, description, authors, manual section). man_pages = [ ( 'index', 'more-itertools', 'more-itertools Documentation', ['Erik Rose'], 1, ) ] # If true, show URL addresses after external links. # man_show_urls = False # -- Options for Texinfo output ------------------------------------------------ # Grouping the document tree into Texinfo files. List of tuples # (source start file, target name, title, author, # dir menu entry, description, category) texinfo_documents = [ ( 'index', 'more-itertools', 'more-itertools Documentation', 'Erik Rose', 'more-itertools', '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' ././@PaxHeader0000000000000000000000000000002600000000000011453 xustar000000000000000022 mtime=1631476336.0 more-itertools-8.10.0/docs/index.rst0000664000175000017500000000024300000000000016401 0ustar00bobo00000000000000.. include:: ./_build/README.pprst Contents ======== .. toctree:: :maxdepth: 2 api .. toctree:: :maxdepth: 1 license testing versions ././@PaxHeader0000000000000000000000000000002600000000000011453 xustar000000000000000022 mtime=1541986671.0 more-itertools-8.10.0/docs/license.rst0000644000175000017500000000120600000000000016712 0ustar00bobo00000000000000======= License ======= more-itertools is under the MIT License. See the LICENSE file. Conditions for Contributors =========================== By contributing to this software project, you are agreeing to the following terms and conditions for your contributions: First, you agree your contributions are submitted under the MIT license. Second, you represent you are authorized to make the contributions and grant the license. If your employer has rights to intellectual property that includes your contributions, you represent that you have received permission to make contributions and grant the required license on behalf of that employer. ././@PaxHeader0000000000000000000000000000002600000000000011453 xustar000000000000000022 mtime=1541986671.0 more-itertools-8.10.0/docs/make.bat0000644000175000017500000001177000000000000016152 0ustar00bobo00000000000000@ECHO OFF REM Command file for Sphinx documentation if "%SPHINXBUILD%" == "" ( set SPHINXBUILD=sphinx-build ) set BUILDDIR=_build set ALLSPHINXOPTS=-d %BUILDDIR%/doctrees %SPHINXOPTS% . set I18NSPHINXOPTS=%SPHINXOPTS% . if NOT "%PAPER%" == "" ( set ALLSPHINXOPTS=-D latex_paper_size=%PAPER% %ALLSPHINXOPTS% set I18NSPHINXOPTS=-D latex_paper_size=%PAPER% %I18NSPHINXOPTS% ) if "%1" == "" goto help if "%1" == "help" ( :help echo.Please use `make ^` where ^ is one of echo. html to make standalone HTML files echo. dirhtml to make HTML files named index.html in directories echo. singlehtml to make a single large HTML file echo. pickle to make pickle files echo. json to make JSON files echo. htmlhelp to make HTML files and a HTML help project echo. qthelp to make HTML files and a qthelp project echo. devhelp to make HTML files and a Devhelp project echo. epub to make an epub echo. latex to make LaTeX files, you can set PAPER=a4 or PAPER=letter echo. text to make text files echo. man to make manual pages echo. texinfo to make Texinfo files echo. gettext to make PO message catalogs echo. changes to make an overview over all changed/added/deprecated items echo. linkcheck to check all external links for integrity echo. doctest to run all doctests embedded in the documentation if enabled goto end ) if "%1" == "clean" ( for /d %%i in (%BUILDDIR%\*) do rmdir /q /s %%i del /q /s %BUILDDIR%\* goto end ) if "%1" == "html" ( %SPHINXBUILD% -b html %ALLSPHINXOPTS% %BUILDDIR%/html if errorlevel 1 exit /b 1 echo. echo.Build finished. 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The epub file is in %BUILDDIR%/epub. goto end ) if "%1" == "latex" ( %SPHINXBUILD% -b latex %ALLSPHINXOPTS% %BUILDDIR%/latex if errorlevel 1 exit /b 1 echo. echo.Build finished; the LaTeX files are in %BUILDDIR%/latex. goto end ) if "%1" == "text" ( %SPHINXBUILD% -b text %ALLSPHINXOPTS% %BUILDDIR%/text if errorlevel 1 exit /b 1 echo. echo.Build finished. The text files are in %BUILDDIR%/text. goto end ) if "%1" == "man" ( %SPHINXBUILD% -b man %ALLSPHINXOPTS% %BUILDDIR%/man if errorlevel 1 exit /b 1 echo. echo.Build finished. The manual pages are in %BUILDDIR%/man. goto end ) if "%1" == "texinfo" ( %SPHINXBUILD% -b texinfo %ALLSPHINXOPTS% %BUILDDIR%/texinfo if errorlevel 1 exit /b 1 echo. echo.Build finished. The Texinfo files are in %BUILDDIR%/texinfo. goto end ) if "%1" == "gettext" ( %SPHINXBUILD% -b gettext %I18NSPHINXOPTS% %BUILDDIR%/locale if errorlevel 1 exit /b 1 echo. echo.Build finished. The message catalogs are in %BUILDDIR%/locale. goto end ) if "%1" == "changes" ( %SPHINXBUILD% -b changes %ALLSPHINXOPTS% %BUILDDIR%/changes if errorlevel 1 exit /b 1 echo. echo.The overview file is in %BUILDDIR%/changes. goto end ) if "%1" == "linkcheck" ( %SPHINXBUILD% -b linkcheck %ALLSPHINXOPTS% %BUILDDIR%/linkcheck if errorlevel 1 exit /b 1 echo. echo.Link check complete; look for any errors in the above output ^ or in %BUILDDIR%/linkcheck/output.txt. goto end ) if "%1" == "doctest" ( %SPHINXBUILD% -b doctest %ALLSPHINXOPTS% %BUILDDIR%/doctest if errorlevel 1 exit /b 1 echo. echo.Testing of doctests in the sources finished, look at the ^ results in %BUILDDIR%/doctest/output.txt. goto end ) :end ././@PaxHeader0000000000000000000000000000002600000000000011453 xustar000000000000000022 mtime=1583076694.0 more-itertools-8.10.0/docs/testing.rst0000644000175000017500000000045600000000000016753 0ustar00bobo00000000000000======= Testing ======= To run install dependencies and run tests, use this command:: python -m unittest Multiple Python Versions ======================== To run the tests on all the versions of Python more-itertools supports, install tox:: pip install tox Then, run the tests:: tox ././@PaxHeader0000000000000000000000000000002600000000000011453 xustar000000000000000022 mtime=1631795930.0 more-itertools-8.10.0/docs/versions.rst0000664000175000017500000004574600000000000017163 0ustar00bobo00000000000000=============== Version History =============== .. automodule:: more_itertools :noindex: 8.10.0 ------ * Changes to existing functions * The type stub for :func:`iter_except` was improved (thanks to MarcinKonowalczyk) * Other changes: * Type stubs now ship with the source release (thanks to saaketp) * The Sphinx docs were improved (thanks to MarcinKonowalczyk) 8.9.0 ----- * New functions * :func:`interleave_evenly` (thanks to mbugert) * :func:`repeat_each` (thanks to FinalSh4re) * :func:`chunked_even` (thanks to valtron) * :func:`map_if` (thanks to sassbalint) * :func:`zip_broadcast` (thanks to kalekundert) * Changes to existing functions * The type stub for :func:`chunked` was improved (thanks to PhilMacKay) * The type stubs for :func:`zip_equal` and `zip_offset` were improved (thanks to maffoo) * Building Sphinx docs locally was improved (thanks to MarcinKonowalczyk) 8.8.0 ----- * New functions * :func:`countable` (thanks to krzysieq) * Changes to existing functions * :func:`split_before` was updated to handle empy collections (thanks to TiunovNN) * :func:`unique_everseen` got a performance boost (thanks to Numerlor) * The type hint for :func:`value_chain` was corrected (thanks to vr2262) 8.7.0 ----- * New functions * :func:`convolve` (from the Python itertools docs) * :func:`product_index`, :func:`combination_index`, and :func:`permutation_index` (thanks to N8Brooks) * :func:`value_chain` (thanks to jenstroeger) * Changes to existing functions * :func:`distinct_combinations` now uses a non-recursive algorithm (thanks to knutdrand) * :func:`pad_none` is now the preferred name for :func:`padnone`, though the latter remains available. * :func:`pairwise` will now use the Python standard library implementation on Python 3.10+ * :func:`sort_together` now accepts a ``key`` argument (thanks to brianmaissy) * :func:`seekable` now has a ``peek`` method, and can indicate whether the iterator it's wrapping is exhausted (thanks to gsakkis) * :func:`time_limited` can now indicate whether its iterator has expired (thanks to roysmith) * The implementation of :func:`unique_everseen` was improved (thanks to plammens) * Other changes: * Various documentation updates (thanks to cthoyt, Evantm, and cyphase) 8.6.0 ----- * New itertools * :func:`all_unique` (thanks to brianmaissy) * :func:`nth_product` and :func:`nth_permutation` (thanks to N8Brooks) * Changes to existing itertools * :func:`chunked` and :func:`sliced` now accept a ``strict`` parameter (thanks to shlomif and jtwool) * Other changes * Python 3.5 has reached its end of life and is no longer supported. * Python 3.9 is officially supported. * Various documentation fixes (thanks to timgates42) 8.5.0 ----- * New itertools * :func:`windowed_complete` (thanks to MarcinKonowalczyk) * Changes to existing itertools: * The :func:`is_sorted` implementation was improved (thanks to cool-RR) * The :func:`groupby_transform` now accepts a ``reducefunc`` parameter. * The :func:`last` implementation was improved (thanks to brianmaissy) * Other changes * Various documentation fixes (thanks to craigrosie, samuelstjean, PiCT0) * The tests for :func:`distinct_combinations` were improved (thanks to Minabsapi) * Automated tests now run on GitHub Actions. All commits now check: * That unit tests pass * That the examples in docstrings work * That test coverage remains high (using `coverage`) * For linting errors (using `flake8`) * For consistent style (using `black`) * That the type stubs work (using `mypy`) * That the docs build correctly (using `sphinx`) * That packages build correctly (using `twine`) 8.4.0 ----- * New itertools * :func:`mark_ends` (thanks to kalekundert) * :func:`is_sorted` * Changes to existing itertools: * :func:`islice_extended` can now be used with real slices (thanks to cool-RR) * The implementations for :func:`filter_except` and :func:`map_except` were improved (thanks to SergBobrovsky) * Other changes * Automated tests now enforce code style (using `black `__) * The various signatures of :func:`islice_extended` and :func:`numeric_range` now appear in the docs (thanks to dsfulf) * The test configuration for mypy was updated (thanks to blueyed) 8.3.0 ----- * New itertools * :func:`zip_equal` (thanks to frankier and alexmojaki) * Changes to existing itertools: * :func:`split_at`, :func:`split_before`, :func:`split_after`, and :func:`split_when` all got a ``maxsplit`` paramter (thanks to jferard and ilai-deutel) * :func:`split_at` now accepts a ``keep_separator`` parameter (thanks to jferard) * :func:`distinct_permutations` can now generate ``r``-length permutations (thanks to SergBobrovsky and ilai-deutel) * The :func:`windowed` implementation was improved (thanks to SergBobrovsky) * The :func:`spy` implementation was improved (thanks to has2k1) * Other changes * Type stubs are now tested with ``stubtest`` (thanks to ilai-deutel) * Tests now run with ``python -m unittest`` instead of ``python setup.py test`` (thanks to jdufresne) 8.2.0 ----- * Bug fixes * The .pyi files for typing were updated. (thanks to blueyed and ilai-deutel) * Changes to existing itertools: * :func:`numeric_range` now behaves more like the built-in :func:`range`. (thanks to jferard) * :func:`bucket` now allows for enumerating keys. (thanks to alexchandel) * :func:`sliced` now should now work for numpy arrays. (thanks to sswingle) * :func:`seekable` now has a ``maxlen`` parameter. 8.1.0 ----- * Bug fixes * :func:`partition` works with ``pred=None`` again. (thanks to MSeifert04) * New itertools * :func:`sample` (thanks to tommyod) * :func:`nth_or_last` (thanks to d-ryzhikov) * Changes to existing itertools: * The implementation for :func:`divide` was improved. (thanks to jferard) 8.0.2 ----- * Bug fixes * The type stub files are now part of the wheel distribution (thanks to keisheiled) 8.0.1 ----- * Bug fixes * The type stub files now work for functions imported from the root package (thanks to keisheiled) 8.0.0 ----- * New itertools and other additions * This library now ships type hints for use with mypy. (thanks to ilai-deutel for the implementation, and to gabbard and fmagin for assistance) * :func:`split_when` (thanks to jferard) * :func:`repeat_last` (thanks to d-ryzhikov) * Changes to existing itertools: * The implementation for :func:`set_partitions` was improved. (thanks to jferard) * :func:`partition` was optimized for expensive predicates. (thanks to stevecj) * :func:`unique_everseen` and :func:`groupby_transform` were re-factored. (thanks to SergBobrovsky) * The implementation for :func:`difference` was improved. (thanks to Jabbey92) * Other changes * Python 3.4 has reached its end of life and is no longer supported. * Python 3.8 is officially supported. (thanks to jdufresne) * The ``collate`` function has been deprecated. It raises a ``DeprecationWarning`` if used, and will be removed in a future release. * :func:`one` and :func:`only` now provide more informative error messages. (thanks to gabbard) * Unit tests were moved outside of the main package (thanks to jdufresne) * Various documentation fixes (thanks to kriomant, gabbard, jdufresne) 7.2.0 ----- * New itertools * :func:`distinct_combinations` * :func:`set_partitions` (thanks to kbarrett) * :func:`filter_except` * :func:`map_except` 7.1.0 ----- * New itertools * :func:`ichunked` (thanks davebelais and youtux) * :func:`only` (thanks jaraco) * Changes to existing itertools: * :func:`numeric_range` now supports ranges specified by ``datetime.datetime`` and ``datetime.timedelta`` objects (thanks to MSeifert04 for tests). * :func:`difference` now supports an *initial* keyword argument. * Other changes * Various documentation fixes (thanks raimon49, pylang) 7.0.0 ----- * New itertools: * :func:`time_limited` * :func:`partitions` (thanks to rominf and Saluev) * :func:`substrings_indexes` (thanks to rominf) * Changes to existing itertools: * :func:`collapse` now treats ``bytes`` objects the same as ``str`` objects. (thanks to Sweenpet) The major version update is due to the change in the default behavior of :func:`collapse`. It now treats ``bytes`` objects the same as ``str`` objects. This aligns its behavior with :func:`always_iterable`. .. code-block:: python >>> from more_itertools import collapse >>> iterable = [[1, 2], b'345', [6]] >>> print(list(collapse(iterable))) [1, 2, b'345', 6] 6.0.0 ----- * Major changes: * Python 2.7 is no longer supported. The 5.0.0 release will be the last version targeting Python 2.7. * All future releases will target the active versions of Python 3. As of 2019, those are Python 3.4 and above. * The ``six`` library is no longer a dependency. * The :func:`accumulate` function is no longer part of this library. You may import a better version from the standard ``itertools`` module. * Changes to existing itertools: * The order of the parameters in :func:`grouper` have changed to match the latest recipe in the itertools documentation. Use of the old order will be supported in this release, but emit a ``DeprecationWarning``. The legacy behavior will be dropped in a future release. (thanks to jaraco) * :func:`distinct_permutations` was improved (thanks to jferard - see also `permutations with unique values `_ at StackOverflow.) * An unused parameter was removed from :func:`substrings`. (thanks to pylang) * Other changes: * The docs for :func:`unique_everseen` were improved. (thanks to jferard and MSeifert04) * Several Python 2-isms were removed. (thanks to jaraco, MSeifert04, and hugovk) 5.0.0 ----- * New itertools: * :func:`split_into` (thanks to rovyko) * :func:`unzip` (thanks to bmintz) * :func:`substrings` (thanks to pylang) * Changes to existing itertools: * :func:`ilen` was optimized a bit (thanks to MSeifert04, achampion, and bmintz) * :func:`first_true` now returns ``None`` by default. This is the reason for the major version bump - see below. (thanks to sk and OJFord) * Other changes: * Some code for old Python versions was removed (thanks to hugovk) * Some documentation mistakes were corrected (thanks to belm0 and hugovk) * Tests now run properly on 32-bit versions of Python (thanks to Millak) * Newer versions of CPython and PyPy are now tested against The major version update is due to the change in the default return value of :func:`first_true`. It's now ``None``. .. code-block:: python >>> from more_itertools import first_true >>> iterable = [0, '', False, [], ()] # All these are False >>> answer = first_true(iterable) >>> print(answer) None 4.3.0 ----- * New itertools: * :func:`last` (thanks to tmshn) * :func:`replace` (thanks to pylang) * :func:`rlocate` (thanks to jferard and pylang) * Improvements to existing itertools: * :func:`locate` can now search for multiple items * Other changes: * The docs now include a nice table of tools (thanks MSeifert04) 4.2.0 ----- * New itertools: * :func:`map_reduce` (thanks to pylang) * :func:`prepend` (from the `Python 3.7 docs `_) * Improvements to existing itertools: * :func:`bucket` now complies with PEP 479 (thanks to irmen) * Other changes: * Python 3.7 is now supported (thanks to irmen) * Python 3.3 is no longer supported * The test suite no longer requires third-party modules to run * The API docs now include links to source code 4.1.0 ----- * New itertools: * :func:`split_at` (thanks to michael-celani) * :func:`circular_shifts` (thanks to hiqua) * :func:`make_decorator` - see the blog post `Yo, I heard you like decorators `_ for a tour (thanks to pylang) * :func:`always_reversible` (thanks to michael-celani) * :func:`nth_combination` (from the `Python 3.7 docs `_) * Improvements to existing itertools: * :func:`seekable` now has an ``elements`` method to return cached items. * The performance tradeoffs between :func:`roundrobin` and :func:`interleave_longest` are now documented (thanks michael-celani, pylang, and MSeifert04) 4.0.1 ----- * No code changes - this release fixes how the docs display on PyPI. 4.0.0 ----- * New itertools: * :func:`consecutive_groups` (Based on the example in the `Python 2.4 docs `_) * :func:`seekable` (If you're looking for how to "reset" an iterator, you're in luck!) * :func:`exactly_n` (thanks to michael-celani) * :func:`run_length.encode` and :func:`run_length.decode` * :func:`difference` * Improvements to existing itertools: * The number of items between filler elements in :func:`intersperse` can now be specified (thanks to pylang) * :func:`distinct_permutations` and :func:`peekable` got some minor adjustments (thanks to MSeifert04) * :func:`always_iterable` now returns an iterator object. It also now allows different types to be considered iterable (thanks to jaraco) * :func:`bucket` can now limit the keys it stores in memory * :func:`one` now allows for custom exceptions (thanks to kalekundert) * Other changes: * A few typos were fixed (thanks to EdwardBetts) * All tests can now be run with ``python setup.py test`` The major version update is due to the change in the return value of :func:`always_iterable`. It now always returns iterator objects: .. code-block:: python >>> from more_itertools import always_iterable # Non-iterable objects are wrapped with iter(tuple(obj)) >>> always_iterable(12345) >>> list(always_iterable(12345)) [12345] # Iterable objects are wrapped with iter() >>> always_iterable([1, 2, 3, 4, 5]) 3.2.0 ----- * New itertools: * :func:`lstrip`, :func:`rstrip`, and :func:`strip` (thanks to MSeifert04 and pylang) * :func:`islice_extended` * Improvements to existing itertools: * Some bugs with slicing :func:`peekable`-wrapped iterables were fixed 3.1.0 ----- * New itertools: * :func:`numeric_range` (Thanks to BebeSparkelSparkel and MSeifert04) * :func:`count_cycle` (Thanks to BebeSparkelSparkel) * :func:`locate` (Thanks to pylang and MSeifert04) * Improvements to existing itertools: * A few itertools are now slightly faster due to some function optimizations. (Thanks to MSeifert04) * The docs have been substantially revised with installation notes, categories for library functions, links, and more. (Thanks to pylang) 3.0.0 ----- * Removed itertools: * ``context`` has been removed due to a design flaw - see below for replacement options. (thanks to NeilGirdhar) * Improvements to existing itertools: * ``side_effect`` now supports ``before`` and ``after`` keyword arguments. (Thanks to yardsale8) * PyPy and PyPy3 are now supported. The major version change is due to the removal of the ``context`` function. Replace it with standard ``with`` statement context management: .. code-block:: python # Don't use context() anymore file_obj = StringIO() consume(print(x, file=f) for f in context(file_obj) for x in u'123') # Use a with statement instead file_obj = StringIO() with file_obj as f: consume(print(x, file=f) for x in u'123') 2.6.0 ----- * New itertools: * ``adjacent`` and ``groupby_transform`` (Thanks to diazona) * ``always_iterable`` (Thanks to jaraco) * (Removed in 3.0.0) ``context`` (Thanks to yardsale8) * ``divide`` (Thanks to mozbhearsum) * Improvements to existing itertools: * ``ilen`` is now slightly faster. (Thanks to wbolster) * ``peekable`` can now prepend items to an iterable. (Thanks to diazona) 2.5.0 ----- * New itertools: * ``distribute`` (Thanks to mozbhearsum and coady) * ``sort_together`` (Thanks to clintval) * ``stagger`` and ``zip_offset`` (Thanks to joshbode) * ``padded`` * Improvements to existing itertools: * ``peekable`` now handles negative indexes and slices with negative components properly. * ``intersperse`` is now slightly faster. (Thanks to pylang) * ``windowed`` now accepts a ``step`` keyword argument. (Thanks to pylang) * Python 3.6 is now supported. 2.4.1 ----- * Move docs 100% to readthedocs.io. 2.4 ----- * New itertools: * ``accumulate``, ``all_equal``, ``first_true``, ``partition``, and ``tail`` from the itertools documentation. * ``bucket`` (Thanks to Rosuav and cvrebert) * ``collapse`` (Thanks to abarnet) * ``interleave`` and ``interleave_longest`` (Thanks to abarnet) * ``side_effect`` (Thanks to nvie) * ``sliced`` (Thanks to j4mie and coady) * ``split_before`` and ``split_after`` (Thanks to astronouth7303) * ``spy`` (Thanks to themiurgo and mathieulongtin) * Improvements to existing itertools: * ``chunked`` is now simpler and more friendly to garbage collection. (Contributed by coady, with thanks to piskvorky) * ``collate`` now delegates to ``heapq.merge`` when possible. (Thanks to kmike and julianpistorius) * ``peekable``-wrapped iterables are now indexable and sliceable. Iterating through ``peekable``-wrapped iterables is also faster. * ``one`` and ``unique_to_each`` have been simplified. (Thanks to coady) 2.3 ----- * Added ``one`` from ``jaraco.util.itertools``. (Thanks, jaraco!) * Added ``distinct_permutations`` and ``unique_to_each``. (Contributed by bbayles) * Added ``windowed``. (Contributed by bbayles, with thanks to buchanae, jaraco, and abarnert) * Simplified the implementation of ``chunked``. (Thanks, nvie!) * Python 3.5 is now supported. Python 2.6 is no longer supported. * Python 3 is now supported directly; there is no 2to3 step. 2.2 ----- * Added ``iterate`` and ``with_iter``. (Thanks, abarnert!) 2.1 ----- * Added (tested!) implementations of the recipes from the itertools documentation. (Thanks, Chris Lonnen!) * Added ``ilen``. (Thanks for the inspiration, Matt Basta!) 2.0 ----- * ``chunked`` now returns lists rather than tuples. After all, they're homogeneous. This slightly backward-incompatible change is the reason for the major version bump. * Added ``@consumer``. * Improved test machinery. 1.1 ----- * Added ``first`` function. * Added Python 3 support. * Added a default arg to ``peekable.peek()``. * Noted how to easily test whether a peekable iterator is exhausted. * Rewrote documentation. 1.0 ----- * Initial release, with ``collate``, ``peekable``, and ``chunked``. Could really use better docs. ././@PaxHeader0000000000000000000000000000003400000000000011452 xustar000000000000000028 mtime=1631883775.1376212 more-itertools-8.10.0/more_itertools/0000775000175000017500000000000000000000000016657 5ustar00bobo00000000000000././@PaxHeader0000000000000000000000000000002600000000000011453 xustar000000000000000022 mtime=1631795897.0 more-itertools-8.10.0/more_itertools/__init__.py0000664000175000017500000000012300000000000020764 0ustar00bobo00000000000000from .more import * # noqa from .recipes import * # noqa __version__ = '8.10.0' ././@PaxHeader0000000000000000000000000000002600000000000011453 xustar000000000000000022 mtime=1575597954.0 more-itertools-8.10.0/more_itertools/__init__.pyi0000644000175000017500000000005300000000000021135 0ustar00bobo00000000000000from .more import * from .recipes import * ././@PaxHeader0000000000000000000000000000002600000000000011453 xustar000000000000000022 mtime=1631273514.0 more-itertools-8.10.0/more_itertools/more.py0000775000175000017500000036534300000000000020214 0ustar00bobo00000000000000import warnings from collections import Counter, defaultdict, deque, abc from collections.abc import Sequence from concurrent.futures import ThreadPoolExecutor from functools import partial, reduce, wraps from heapq import merge, heapify, heapreplace, heappop from itertools import ( chain, compress, count, cycle, dropwhile, groupby, islice, repeat, starmap, takewhile, tee, zip_longest, ) from math import exp, factorial, floor, log from queue import Empty, Queue from random import random, randrange, uniform from operator import itemgetter, mul, sub, gt, lt from sys import hexversion, maxsize from time import monotonic from .recipes import ( consume, flatten, pairwise, powerset, take, unique_everseen, ) __all__ = [ 'AbortThread', 'adjacent', 'always_iterable', 'always_reversible', 'bucket', 'callback_iter', 'chunked', 'chunked_even', 'circular_shifts', 'collapse', 'collate', 'consecutive_groups', 'consumer', 'countable', 'count_cycle', 'mark_ends', 'difference', 'distinct_combinations', 'distinct_permutations', 'distribute', 'divide', 'exactly_n', 'filter_except', 'first', 'groupby_transform', 'ilen', 'interleave_longest', 'interleave', 'interleave_evenly', 'intersperse', 'islice_extended', 'iterate', 'ichunked', 'is_sorted', 'last', 'locate', 'lstrip', 'make_decorator', 'map_except', 'map_if', 'map_reduce', 'nth_or_last', 'nth_permutation', 'nth_product', 'numeric_range', 'one', 'only', 'padded', 'partitions', 'set_partitions', 'peekable', 'repeat_each', 'repeat_last', 'replace', 'rlocate', 'rstrip', 'run_length', 'sample', 'seekable', 'SequenceView', 'side_effect', 'sliced', 'sort_together', 'split_at', 'split_after', 'split_before', 'split_when', 'split_into', 'spy', 'stagger', 'strip', 'substrings', 'substrings_indexes', 'time_limited', 'unique_to_each', 'unzip', 'windowed', 'with_iter', 'UnequalIterablesError', 'zip_equal', 'zip_offset', 'windowed_complete', 'all_unique', 'value_chain', 'product_index', 'combination_index', 'permutation_index', 'zip_broadcast', ] _marker = object() def chunked(iterable, n, strict=False): """Break *iterable* into lists of length *n*: >>> list(chunked([1, 2, 3, 4, 5, 6], 3)) [[1, 2, 3], [4, 5, 6]] By the default, the last yielded list will have fewer than *n* elements if the length of *iterable* is not divisible by *n*: >>> list(chunked([1, 2, 3, 4, 5, 6, 7, 8], 3)) [[1, 2, 3], [4, 5, 6], [7, 8]] To use a fill-in value instead, see the :func:`grouper` recipe. If the length of *iterable* is not divisible by *n* and *strict* is ``True``, then ``ValueError`` will be raised before the last list is yielded. """ iterator = iter(partial(take, n, iter(iterable)), []) if strict: if n is None: raise ValueError('n must not be None when using strict mode.') def ret(): for chunk in iterator: if len(chunk) != n: raise ValueError('iterable is not divisible by n.') yield chunk return iter(ret()) else: return iterator def first(iterable, default=_marker): """Return the first item of *iterable*, or *default* if *iterable* is empty. >>> first([0, 1, 2, 3]) 0 >>> first([], 'some default') 'some default' If *default* is not provided and there are no items in the iterable, raise ``ValueError``. :func:`first` is useful when you have a generator of expensive-to-retrieve values and want any arbitrary one. It is marginally shorter than ``next(iter(iterable), default)``. """ try: return next(iter(iterable)) except StopIteration as e: if default is _marker: raise ValueError( 'first() was called on an empty iterable, and no ' 'default value was provided.' ) from e return default def last(iterable, default=_marker): """Return the last item of *iterable*, or *default* if *iterable* is empty. >>> last([0, 1, 2, 3]) 3 >>> last([], 'some default') 'some default' If *default* is not provided and there are no items in the iterable, raise ``ValueError``. """ try: if isinstance(iterable, Sequence): return iterable[-1] # Work around https://bugs.python.org/issue38525 elif hasattr(iterable, '__reversed__') and (hexversion != 0x030800F0): return next(reversed(iterable)) else: return deque(iterable, maxlen=1)[-1] except (IndexError, TypeError, StopIteration): if default is _marker: raise ValueError( 'last() was called on an empty iterable, and no default was ' 'provided.' ) return default def nth_or_last(iterable, n, default=_marker): """Return the nth or the last item of *iterable*, or *default* if *iterable* is empty. >>> nth_or_last([0, 1, 2, 3], 2) 2 >>> nth_or_last([0, 1], 2) 1 >>> nth_or_last([], 0, 'some default') 'some default' If *default* is not provided and there are no items in the iterable, raise ``ValueError``. """ return last(islice(iterable, n + 1), default=default) class peekable: """Wrap an iterator to allow lookahead and prepending elements. Call :meth:`peek` on the result to get the value that will be returned by :func:`next`. This won't advance the iterator: >>> p = peekable(['a', 'b']) >>> p.peek() 'a' >>> next(p) 'a' Pass :meth:`peek` a default value to return that instead of raising ``StopIteration`` when the iterator is exhausted. >>> p = peekable([]) >>> p.peek('hi') 'hi' peekables also offer a :meth:`prepend` method, which "inserts" items at the head of the iterable: >>> p = peekable([1, 2, 3]) >>> p.prepend(10, 11, 12) >>> next(p) 10 >>> p.peek() 11 >>> list(p) [11, 12, 1, 2, 3] peekables can be indexed. Index 0 is the item that will be returned by :func:`next`, index 1 is the item after that, and so on: The values up to the given index will be cached. >>> p = peekable(['a', 'b', 'c', 'd']) >>> p[0] 'a' >>> p[1] 'b' >>> next(p) 'a' Negative indexes are supported, but be aware that they will cache the remaining items in the source iterator, which may require significant storage. To check whether a peekable is exhausted, check its truth value: >>> p = peekable(['a', 'b']) >>> if p: # peekable has items ... list(p) ['a', 'b'] >>> if not p: # peekable is exhausted ... list(p) [] """ def __init__(self, iterable): self._it = iter(iterable) self._cache = deque() def __iter__(self): return self def __bool__(self): try: self.peek() except StopIteration: return False return True def peek(self, default=_marker): """Return the item that will be next returned from ``next()``. Return ``default`` if there are no items left. If ``default`` is not provided, raise ``StopIteration``. """ if not self._cache: try: self._cache.append(next(self._it)) except StopIteration: if default is _marker: raise return default return self._cache[0] def prepend(self, *items): """Stack up items to be the next ones returned from ``next()`` or ``self.peek()``. The items will be returned in first in, first out order:: >>> p = peekable([1, 2, 3]) >>> p.prepend(10, 11, 12) >>> next(p) 10 >>> list(p) [11, 12, 1, 2, 3] It is possible, by prepending items, to "resurrect" a peekable that previously raised ``StopIteration``. >>> p = peekable([]) >>> next(p) Traceback (most recent call last): ... StopIteration >>> p.prepend(1) >>> next(p) 1 >>> next(p) Traceback (most recent call last): ... StopIteration """ self._cache.extendleft(reversed(items)) def __next__(self): if self._cache: return self._cache.popleft() return next(self._it) def _get_slice(self, index): # Normalize the slice's arguments step = 1 if (index.step is None) else index.step if step > 0: start = 0 if (index.start is None) else index.start stop = maxsize if (index.stop is None) else index.stop elif step < 0: start = -1 if (index.start is None) else index.start stop = (-maxsize - 1) if (index.stop is None) else index.stop else: raise ValueError('slice step cannot be zero') # If either the start or stop index is negative, we'll need to cache # the rest of the iterable in order to slice from the right side. if (start < 0) or (stop < 0): self._cache.extend(self._it) # Otherwise we'll need to find the rightmost index and cache to that # point. else: n = min(max(start, stop) + 1, maxsize) cache_len = len(self._cache) if n >= cache_len: self._cache.extend(islice(self._it, n - cache_len)) return list(self._cache)[index] def __getitem__(self, index): if isinstance(index, slice): return self._get_slice(index) cache_len = len(self._cache) if index < 0: self._cache.extend(self._it) elif index >= cache_len: self._cache.extend(islice(self._it, index + 1 - cache_len)) return self._cache[index] def collate(*iterables, **kwargs): """Return a sorted merge of the items from each of several already-sorted *iterables*. >>> list(collate('ACDZ', 'AZ', 'JKL')) ['A', 'A', 'C', 'D', 'J', 'K', 'L', 'Z', 'Z'] Works lazily, keeping only the next value from each iterable in memory. Use :func:`collate` to, for example, perform a n-way mergesort of items that don't fit in memory. If a *key* function is specified, the iterables will be sorted according to its result: >>> key = lambda s: int(s) # Sort by numeric value, not by string >>> list(collate(['1', '10'], ['2', '11'], key=key)) ['1', '2', '10', '11'] If the *iterables* are sorted in descending order, set *reverse* to ``True``: >>> list(collate([5, 3, 1], [4, 2, 0], reverse=True)) [5, 4, 3, 2, 1, 0] If the elements of the passed-in iterables are out of order, you might get unexpected results. On Python 3.5+, this function is an alias for :func:`heapq.merge`. """ warnings.warn( "collate is no longer part of more_itertools, use heapq.merge", DeprecationWarning, ) return merge(*iterables, **kwargs) def consumer(func): """Decorator that automatically advances a PEP-342-style "reverse iterator" to its first yield point so you don't have to call ``next()`` on it manually. >>> @consumer ... def tally(): ... i = 0 ... while True: ... print('Thing number %s is %s.' % (i, (yield))) ... i += 1 ... >>> t = tally() >>> t.send('red') Thing number 0 is red. >>> t.send('fish') Thing number 1 is fish. Without the decorator, you would have to call ``next(t)`` before ``t.send()`` could be used. """ @wraps(func) def wrapper(*args, **kwargs): gen = func(*args, **kwargs) next(gen) return gen return wrapper def ilen(iterable): """Return the number of items in *iterable*. >>> ilen(x for x in range(1000000) if x % 3 == 0) 333334 This consumes the iterable, so handle with care. """ # This approach was selected because benchmarks showed it's likely the # fastest of the known implementations at the time of writing. # See GitHub tracker: #236, #230. counter = count() deque(zip(iterable, counter), maxlen=0) return next(counter) def iterate(func, start): """Return ``start``, ``func(start)``, ``func(func(start))``, ... >>> from itertools import islice >>> list(islice(iterate(lambda x: 2*x, 1), 10)) [1, 2, 4, 8, 16, 32, 64, 128, 256, 512] """ while True: yield start start = func(start) def with_iter(context_manager): """Wrap an iterable in a ``with`` statement, so it closes once exhausted. For example, this will close the file when the iterator is exhausted:: upper_lines = (line.upper() for line in with_iter(open('foo'))) Any context manager which returns an iterable is a candidate for ``with_iter``. """ with context_manager as iterable: yield from iterable def one(iterable, too_short=None, too_long=None): """Return the first item from *iterable*, which is expected to contain only that item. Raise an exception if *iterable* is empty or has more than one item. :func:`one` is useful for ensuring that an iterable contains only one item. For example, it can be used to retrieve the result of a database query that is expected to return a single row. If *iterable* is empty, ``ValueError`` will be raised. You may specify a different exception with the *too_short* keyword: >>> it = [] >>> one(it) # doctest: +IGNORE_EXCEPTION_DETAIL Traceback (most recent call last): ... ValueError: too many items in iterable (expected 1)' >>> too_short = IndexError('too few items') >>> one(it, too_short=too_short) # doctest: +IGNORE_EXCEPTION_DETAIL Traceback (most recent call last): ... IndexError: too few items Similarly, if *iterable* contains more than one item, ``ValueError`` will be raised. You may specify a different exception with the *too_long* keyword: >>> it = ['too', 'many'] >>> one(it) # doctest: +IGNORE_EXCEPTION_DETAIL Traceback (most recent call last): ... ValueError: Expected exactly one item in iterable, but got 'too', 'many', and perhaps more. >>> too_long = RuntimeError >>> one(it, too_long=too_long) # doctest: +IGNORE_EXCEPTION_DETAIL Traceback (most recent call last): ... RuntimeError Note that :func:`one` attempts to advance *iterable* twice to ensure there is only one item. See :func:`spy` or :func:`peekable` to check iterable contents less destructively. """ it = iter(iterable) try: first_value = next(it) except StopIteration as e: raise ( too_short or ValueError('too few items in iterable (expected 1)') ) from e try: second_value = next(it) except StopIteration: pass else: msg = ( 'Expected exactly one item in iterable, but got {!r}, {!r}, ' 'and perhaps more.'.format(first_value, second_value) ) raise too_long or ValueError(msg) return first_value def distinct_permutations(iterable, r=None): """Yield successive distinct permutations of the elements in *iterable*. >>> sorted(distinct_permutations([1, 0, 1])) [(0, 1, 1), (1, 0, 1), (1, 1, 0)] Equivalent to ``set(permutations(iterable))``, except duplicates are not generated and thrown away. For larger input sequences this is much more efficient. Duplicate permutations arise when there are duplicated elements in the input iterable. The number of items returned is `n! / (x_1! * x_2! * ... * x_n!)`, where `n` is the total number of items input, and each `x_i` is the count of a distinct item in the input sequence. If *r* is given, only the *r*-length permutations are yielded. >>> sorted(distinct_permutations([1, 0, 1], r=2)) [(0, 1), (1, 0), (1, 1)] >>> sorted(distinct_permutations(range(3), r=2)) [(0, 1), (0, 2), (1, 0), (1, 2), (2, 0), (2, 1)] """ # Algorithm: https://w.wiki/Qai def _full(A): while True: # Yield the permutation we have yield tuple(A) # Find the largest index i such that A[i] < A[i + 1] for i in range(size - 2, -1, -1): if A[i] < A[i + 1]: break # If no such index exists, this permutation is the last one else: return # Find the largest index j greater than j such that A[i] < A[j] for j in range(size - 1, i, -1): if A[i] < A[j]: break # Swap the value of A[i] with that of A[j], then reverse the # sequence from A[i + 1] to form the new permutation A[i], A[j] = A[j], A[i] A[i + 1 :] = A[: i - size : -1] # A[i + 1:][::-1] # Algorithm: modified from the above def _partial(A, r): # Split A into the first r items and the last r items head, tail = A[:r], A[r:] right_head_indexes = range(r - 1, -1, -1) left_tail_indexes = range(len(tail)) while True: # Yield the permutation we have yield tuple(head) # Starting from the right, find the first index of the head with # value smaller than the maximum value of the tail - call it i. pivot = tail[-1] for i in right_head_indexes: if head[i] < pivot: break pivot = head[i] else: return # Starting from the left, find the first value of the tail # with a value greater than head[i] and swap. for j in left_tail_indexes: if tail[j] > head[i]: head[i], tail[j] = tail[j], head[i] break # If we didn't find one, start from the right and find the first # index of the head with a value greater than head[i] and swap. else: for j in right_head_indexes: if head[j] > head[i]: head[i], head[j] = head[j], head[i] break # Reverse head[i + 1:] and swap it with tail[:r - (i + 1)] tail += head[: i - r : -1] # head[i + 1:][::-1] i += 1 head[i:], tail[:] = tail[: r - i], tail[r - i :] items = sorted(iterable) size = len(items) if r is None: r = size if 0 < r <= size: return _full(items) if (r == size) else _partial(items, r) return iter(() if r else ((),)) def intersperse(e, iterable, n=1): """Intersperse filler element *e* among the items in *iterable*, leaving *n* items between each filler element. >>> list(intersperse('!', [1, 2, 3, 4, 5])) [1, '!', 2, '!', 3, '!', 4, '!', 5] >>> list(intersperse(None, [1, 2, 3, 4, 5], n=2)) [1, 2, None, 3, 4, None, 5] """ if n == 0: raise ValueError('n must be > 0') elif n == 1: # interleave(repeat(e), iterable) -> e, x_0, e, e, x_1, e, x_2... # islice(..., 1, None) -> x_0, e, e, x_1, e, x_2... return islice(interleave(repeat(e), iterable), 1, None) else: # interleave(filler, chunks) -> [e], [x_0, x_1], [e], [x_2, x_3]... # islice(..., 1, None) -> [x_0, x_1], [e], [x_2, x_3]... # flatten(...) -> x_0, x_1, e, x_2, x_3... filler = repeat([e]) chunks = chunked(iterable, n) return flatten(islice(interleave(filler, chunks), 1, None)) def unique_to_each(*iterables): """Return the elements from each of the input iterables that aren't in the other input iterables. For example, suppose you have a set of packages, each with a set of dependencies:: {'pkg_1': {'A', 'B'}, 'pkg_2': {'B', 'C'}, 'pkg_3': {'B', 'D'}} If you remove one package, which dependencies can also be removed? If ``pkg_1`` is removed, then ``A`` is no longer necessary - it is not associated with ``pkg_2`` or ``pkg_3``. Similarly, ``C`` is only needed for ``pkg_2``, and ``D`` is only needed for ``pkg_3``:: >>> unique_to_each({'A', 'B'}, {'B', 'C'}, {'B', 'D'}) [['A'], ['C'], ['D']] If there are duplicates in one input iterable that aren't in the others they will be duplicated in the output. Input order is preserved:: >>> unique_to_each("mississippi", "missouri") [['p', 'p'], ['o', 'u', 'r']] It is assumed that the elements of each iterable are hashable. """ pool = [list(it) for it in iterables] counts = Counter(chain.from_iterable(map(set, pool))) uniques = {element for element in counts if counts[element] == 1} return [list(filter(uniques.__contains__, it)) for it in pool] def windowed(seq, n, fillvalue=None, step=1): """Return a sliding window of width *n* over the given iterable. >>> all_windows = windowed([1, 2, 3, 4, 5], 3) >>> list(all_windows) [(1, 2, 3), (2, 3, 4), (3, 4, 5)] When the window is larger than the iterable, *fillvalue* is used in place of missing values: >>> list(windowed([1, 2, 3], 4)) [(1, 2, 3, None)] Each window will advance in increments of *step*: >>> list(windowed([1, 2, 3, 4, 5, 6], 3, fillvalue='!', step=2)) [(1, 2, 3), (3, 4, 5), (5, 6, '!')] To slide into the iterable's items, use :func:`chain` to add filler items to the left: >>> iterable = [1, 2, 3, 4] >>> n = 3 >>> padding = [None] * (n - 1) >>> list(windowed(chain(padding, iterable), 3)) [(None, None, 1), (None, 1, 2), (1, 2, 3), (2, 3, 4)] """ if n < 0: raise ValueError('n must be >= 0') if n == 0: yield tuple() return if step < 1: raise ValueError('step must be >= 1') window = deque(maxlen=n) i = n for _ in map(window.append, seq): i -= 1 if not i: i = step yield tuple(window) size = len(window) if size < n: yield tuple(chain(window, repeat(fillvalue, n - size))) elif 0 < i < min(step, n): window += (fillvalue,) * i yield tuple(window) def substrings(iterable): """Yield all of the substrings of *iterable*. >>> [''.join(s) for s in substrings('more')] ['m', 'o', 'r', 'e', 'mo', 'or', 're', 'mor', 'ore', 'more'] Note that non-string iterables can also be subdivided. >>> list(substrings([0, 1, 2])) [(0,), (1,), (2,), (0, 1), (1, 2), (0, 1, 2)] """ # The length-1 substrings seq = [] for item in iter(iterable): seq.append(item) yield (item,) seq = tuple(seq) item_count = len(seq) # And the rest for n in range(2, item_count + 1): for i in range(item_count - n + 1): yield seq[i : i + n] def substrings_indexes(seq, reverse=False): """Yield all substrings and their positions in *seq* The items yielded will be a tuple of the form ``(substr, i, j)``, where ``substr == seq[i:j]``. This function only works for iterables that support slicing, such as ``str`` objects. >>> for item in substrings_indexes('more'): ... print(item) ('m', 0, 1) ('o', 1, 2) ('r', 2, 3) ('e', 3, 4) ('mo', 0, 2) ('or', 1, 3) ('re', 2, 4) ('mor', 0, 3) ('ore', 1, 4) ('more', 0, 4) Set *reverse* to ``True`` to yield the same items in the opposite order. """ r = range(1, len(seq) + 1) if reverse: r = reversed(r) return ( (seq[i : i + L], i, i + L) for L in r for i in range(len(seq) - L + 1) ) class bucket: """Wrap *iterable* and return an object that buckets it iterable into child iterables based on a *key* function. >>> iterable = ['a1', 'b1', 'c1', 'a2', 'b2', 'c2', 'b3'] >>> s = bucket(iterable, key=lambda x: x[0]) # Bucket by 1st character >>> sorted(list(s)) # Get the keys ['a', 'b', 'c'] >>> a_iterable = s['a'] >>> next(a_iterable) 'a1' >>> next(a_iterable) 'a2' >>> list(s['b']) ['b1', 'b2', 'b3'] The original iterable will be advanced and its items will be cached until they are used by the child iterables. This may require significant storage. By default, attempting to select a bucket to which no items belong will exhaust the iterable and cache all values. If you specify a *validator* function, selected buckets will instead be checked against it. >>> from itertools import count >>> it = count(1, 2) # Infinite sequence of odd numbers >>> key = lambda x: x % 10 # Bucket by last digit >>> validator = lambda x: x in {1, 3, 5, 7, 9} # Odd digits only >>> s = bucket(it, key=key, validator=validator) >>> 2 in s False >>> list(s[2]) [] """ def __init__(self, iterable, key, validator=None): self._it = iter(iterable) self._key = key self._cache = defaultdict(deque) self._validator = validator or (lambda x: True) def __contains__(self, value): if not self._validator(value): return False try: item = next(self[value]) except StopIteration: return False else: self._cache[value].appendleft(item) return True def _get_values(self, value): """ Helper to yield items from the parent iterator that match *value*. Items that don't match are stored in the local cache as they are encountered. """ while True: # If we've cached some items that match the target value, emit # the first one and evict it from the cache. if self._cache[value]: yield self._cache[value].popleft() # Otherwise we need to advance the parent iterator to search for # a matching item, caching the rest. else: while True: try: item = next(self._it) except StopIteration: return item_value = self._key(item) if item_value == value: yield item break elif self._validator(item_value): self._cache[item_value].append(item) def __iter__(self): for item in self._it: item_value = self._key(item) if self._validator(item_value): self._cache[item_value].append(item) yield from self._cache.keys() def __getitem__(self, value): if not self._validator(value): return iter(()) return self._get_values(value) def spy(iterable, n=1): """Return a 2-tuple with a list containing the first *n* elements of *iterable*, and an iterator with the same items as *iterable*. This allows you to "look ahead" at the items in the iterable without advancing it. There is one item in the list by default: >>> iterable = 'abcdefg' >>> head, iterable = spy(iterable) >>> head ['a'] >>> list(iterable) ['a', 'b', 'c', 'd', 'e', 'f', 'g'] You may use unpacking to retrieve items instead of lists: >>> (head,), iterable = spy('abcdefg') >>> head 'a' >>> (first, second), iterable = spy('abcdefg', 2) >>> first 'a' >>> second 'b' The number of items requested can be larger than the number of items in the iterable: >>> iterable = [1, 2, 3, 4, 5] >>> head, iterable = spy(iterable, 10) >>> head [1, 2, 3, 4, 5] >>> list(iterable) [1, 2, 3, 4, 5] """ it = iter(iterable) head = take(n, it) return head.copy(), chain(head, it) def interleave(*iterables): """Return a new iterable yielding from each iterable in turn, until the shortest is exhausted. >>> list(interleave([1, 2, 3], [4, 5], [6, 7, 8])) [1, 4, 6, 2, 5, 7] For a version that doesn't terminate after the shortest iterable is exhausted, see :func:`interleave_longest`. """ return chain.from_iterable(zip(*iterables)) def interleave_longest(*iterables): """Return a new iterable yielding from each iterable in turn, skipping any that are exhausted. >>> list(interleave_longest([1, 2, 3], [4, 5], [6, 7, 8])) [1, 4, 6, 2, 5, 7, 3, 8] This function produces the same output as :func:`roundrobin`, but may perform better for some inputs (in particular when the number of iterables is large). """ i = chain.from_iterable(zip_longest(*iterables, fillvalue=_marker)) return (x for x in i if x is not _marker) def interleave_evenly(iterables, lengths=None): """ Interleave multiple iterables so that their elements are evenly distributed throughout the output sequence. >>> iterables = [1, 2, 3, 4, 5], ['a', 'b'] >>> list(interleave_evenly(iterables)) [1, 2, 'a', 3, 4, 'b', 5] >>> iterables = [[1, 2, 3], [4, 5], [6, 7, 8]] >>> list(interleave_evenly(iterables)) [1, 6, 4, 2, 7, 3, 8, 5] This function requires iterables of known length. Iterables without ``__len__()`` can be used by manually specifying lengths with *lengths*: >>> from itertools import combinations, repeat >>> iterables = [combinations(range(4), 2), ['a', 'b', 'c']] >>> lengths = [4 * (4 - 1) // 2, 3] >>> list(interleave_evenly(iterables, lengths=lengths)) [(0, 1), (0, 2), 'a', (0, 3), (1, 2), 'b', (1, 3), (2, 3), 'c'] Based on Bresenham's algorithm. """ if lengths is None: try: lengths = [len(it) for it in iterables] except TypeError: raise ValueError( 'Iterable lengths could not be determined automatically. ' 'Specify them with the lengths keyword.' ) elif len(iterables) != len(lengths): raise ValueError('Mismatching number of iterables and lengths.') dims = len(lengths) # sort iterables by length, descending lengths_permute = sorted( range(dims), key=lambda i: lengths[i], reverse=True ) lengths_desc = [lengths[i] for i in lengths_permute] iters_desc = [iter(iterables[i]) for i in lengths_permute] # the longest iterable is the primary one (Bresenham: the longest # distance along an axis) delta_primary, deltas_secondary = lengths_desc[0], lengths_desc[1:] iter_primary, iters_secondary = iters_desc[0], iters_desc[1:] errors = [delta_primary // dims] * len(deltas_secondary) to_yield = sum(lengths) while to_yield: yield next(iter_primary) to_yield -= 1 # update errors for each secondary iterable errors = [e - delta for e, delta in zip(errors, deltas_secondary)] # those iterables for which the error is negative are yielded # ("diagonal step" in Bresenham) for i, e in enumerate(errors): if e < 0: yield next(iters_secondary[i]) to_yield -= 1 errors[i] += delta_primary def collapse(iterable, base_type=None, levels=None): """Flatten an iterable with multiple levels of nesting (e.g., a list of lists of tuples) into non-iterable types. >>> iterable = [(1, 2), ([3, 4], [[5], [6]])] >>> list(collapse(iterable)) [1, 2, 3, 4, 5, 6] Binary and text strings are not considered iterable and will not be collapsed. To avoid collapsing other types, specify *base_type*: >>> iterable = ['ab', ('cd', 'ef'), ['gh', 'ij']] >>> list(collapse(iterable, base_type=tuple)) ['ab', ('cd', 'ef'), 'gh', 'ij'] Specify *levels* to stop flattening after a certain level: >>> iterable = [('a', ['b']), ('c', ['d'])] >>> list(collapse(iterable)) # Fully flattened ['a', 'b', 'c', 'd'] >>> list(collapse(iterable, levels=1)) # Only one level flattened ['a', ['b'], 'c', ['d']] """ def walk(node, level): if ( ((levels is not None) and (level > levels)) or isinstance(node, (str, bytes)) or ((base_type is not None) and isinstance(node, base_type)) ): yield node return try: tree = iter(node) except TypeError: yield node return else: for child in tree: yield from walk(child, level + 1) yield from walk(iterable, 0) def side_effect(func, iterable, chunk_size=None, before=None, after=None): """Invoke *func* on each item in *iterable* (or on each *chunk_size* group of items) before yielding the item. `func` must be a function that takes a single argument. Its return value will be discarded. *before* and *after* are optional functions that take no arguments. They will be executed before iteration starts and after it ends, respectively. `side_effect` can be used for logging, updating progress bars, or anything that is not functionally "pure." Emitting a status message: >>> from more_itertools import consume >>> func = lambda item: print('Received {}'.format(item)) >>> consume(side_effect(func, range(2))) Received 0 Received 1 Operating on chunks of items: >>> pair_sums = [] >>> func = lambda chunk: pair_sums.append(sum(chunk)) >>> list(side_effect(func, [0, 1, 2, 3, 4, 5], 2)) [0, 1, 2, 3, 4, 5] >>> list(pair_sums) [1, 5, 9] Writing to a file-like object: >>> from io import StringIO >>> from more_itertools import consume >>> f = StringIO() >>> func = lambda x: print(x, file=f) >>> before = lambda: print(u'HEADER', file=f) >>> after = f.close >>> it = [u'a', u'b', u'c'] >>> consume(side_effect(func, it, before=before, after=after)) >>> f.closed True """ try: if before is not None: before() if chunk_size is None: for item in iterable: func(item) yield item else: for chunk in chunked(iterable, chunk_size): func(chunk) yield from chunk finally: if after is not None: after() def sliced(seq, n, strict=False): """Yield slices of length *n* from the sequence *seq*. >>> list(sliced((1, 2, 3, 4, 5, 6), 3)) [(1, 2, 3), (4, 5, 6)] By the default, the last yielded slice will have fewer than *n* elements if the length of *seq* is not divisible by *n*: >>> list(sliced((1, 2, 3, 4, 5, 6, 7, 8), 3)) [(1, 2, 3), (4, 5, 6), (7, 8)] If the length of *seq* is not divisible by *n* and *strict* is ``True``, then ``ValueError`` will be raised before the last slice is yielded. This function will only work for iterables that support slicing. For non-sliceable iterables, see :func:`chunked`. """ iterator = takewhile(len, (seq[i : i + n] for i in count(0, n))) if strict: def ret(): for _slice in iterator: if len(_slice) != n: raise ValueError("seq is not divisible by n.") yield _slice return iter(ret()) else: return iterator def split_at(iterable, pred, maxsplit=-1, keep_separator=False): """Yield lists of items from *iterable*, where each list is delimited by an item where callable *pred* returns ``True``. >>> list(split_at('abcdcba', lambda x: x == 'b')) [['a'], ['c', 'd', 'c'], ['a']] >>> list(split_at(range(10), lambda n: n % 2 == 1)) [[0], [2], [4], [6], [8], []] At most *maxsplit* splits are done. If *maxsplit* is not specified or -1, then there is no limit on the number of splits: >>> list(split_at(range(10), lambda n: n % 2 == 1, maxsplit=2)) [[0], [2], [4, 5, 6, 7, 8, 9]] By default, the delimiting items are not included in the output. The include them, set *keep_separator* to ``True``. >>> list(split_at('abcdcba', lambda x: x == 'b', keep_separator=True)) [['a'], ['b'], ['c', 'd', 'c'], ['b'], ['a']] """ if maxsplit == 0: yield list(iterable) return buf = [] it = iter(iterable) for item in it: if pred(item): yield buf if keep_separator: yield [item] if maxsplit == 1: yield list(it) return buf = [] maxsplit -= 1 else: buf.append(item) yield buf def split_before(iterable, pred, maxsplit=-1): """Yield lists of items from *iterable*, where each list ends just before an item for which callable *pred* returns ``True``: >>> list(split_before('OneTwo', lambda s: s.isupper())) [['O', 'n', 'e'], ['T', 'w', 'o']] >>> list(split_before(range(10), lambda n: n % 3 == 0)) [[0, 1, 2], [3, 4, 5], [6, 7, 8], [9]] At most *maxsplit* splits are done. If *maxsplit* is not specified or -1, then there is no limit on the number of splits: >>> list(split_before(range(10), lambda n: n % 3 == 0, maxsplit=2)) [[0, 1, 2], [3, 4, 5], [6, 7, 8, 9]] """ if maxsplit == 0: yield list(iterable) return buf = [] it = iter(iterable) for item in it: if pred(item) and buf: yield buf if maxsplit == 1: yield [item] + list(it) return buf = [] maxsplit -= 1 buf.append(item) if buf: yield buf def split_after(iterable, pred, maxsplit=-1): """Yield lists of items from *iterable*, where each list ends with an item where callable *pred* returns ``True``: >>> list(split_after('one1two2', lambda s: s.isdigit())) [['o', 'n', 'e', '1'], ['t', 'w', 'o', '2']] >>> list(split_after(range(10), lambda n: n % 3 == 0)) [[0], [1, 2, 3], [4, 5, 6], [7, 8, 9]] At most *maxsplit* splits are done. If *maxsplit* is not specified or -1, then there is no limit on the number of splits: >>> list(split_after(range(10), lambda n: n % 3 == 0, maxsplit=2)) [[0], [1, 2, 3], [4, 5, 6, 7, 8, 9]] """ if maxsplit == 0: yield list(iterable) return buf = [] it = iter(iterable) for item in it: buf.append(item) if pred(item) and buf: yield buf if maxsplit == 1: yield list(it) return buf = [] maxsplit -= 1 if buf: yield buf def split_when(iterable, pred, maxsplit=-1): """Split *iterable* into pieces based on the output of *pred*. *pred* should be a function that takes successive pairs of items and returns ``True`` if the iterable should be split in between them. For example, to find runs of increasing numbers, split the iterable when element ``i`` is larger than element ``i + 1``: >>> list(split_when([1, 2, 3, 3, 2, 5, 2, 4, 2], lambda x, y: x > y)) [[1, 2, 3, 3], [2, 5], [2, 4], [2]] At most *maxsplit* splits are done. If *maxsplit* is not specified or -1, then there is no limit on the number of splits: >>> list(split_when([1, 2, 3, 3, 2, 5, 2, 4, 2], ... lambda x, y: x > y, maxsplit=2)) [[1, 2, 3, 3], [2, 5], [2, 4, 2]] """ if maxsplit == 0: yield list(iterable) return it = iter(iterable) try: cur_item = next(it) except StopIteration: return buf = [cur_item] for next_item in it: if pred(cur_item, next_item): yield buf if maxsplit == 1: yield [next_item] + list(it) return buf = [] maxsplit -= 1 buf.append(next_item) cur_item = next_item yield buf def split_into(iterable, sizes): """Yield a list of sequential items from *iterable* of length 'n' for each integer 'n' in *sizes*. >>> list(split_into([1,2,3,4,5,6], [1,2,3])) [[1], [2, 3], [4, 5, 6]] If the sum of *sizes* is smaller than the length of *iterable*, then the remaining items of *iterable* will not be returned. >>> list(split_into([1,2,3,4,5,6], [2,3])) [[1, 2], [3, 4, 5]] If the sum of *sizes* is larger than the length of *iterable*, fewer items will be returned in the iteration that overruns *iterable* and further lists will be empty: >>> list(split_into([1,2,3,4], [1,2,3,4])) [[1], [2, 3], [4], []] When a ``None`` object is encountered in *sizes*, the returned list will contain items up to the end of *iterable* the same way that itertools.slice does: >>> list(split_into([1,2,3,4,5,6,7,8,9,0], [2,3,None])) [[1, 2], [3, 4, 5], [6, 7, 8, 9, 0]] :func:`split_into` can be useful for grouping a series of items where the sizes of the groups are not uniform. An example would be where in a row from a table, multiple columns represent elements of the same feature (e.g. a point represented by x,y,z) but, the format is not the same for all columns. """ # convert the iterable argument into an iterator so its contents can # be consumed by islice in case it is a generator it = iter(iterable) for size in sizes: if size is None: yield list(it) return else: yield list(islice(it, size)) def padded(iterable, fillvalue=None, n=None, next_multiple=False): """Yield the elements from *iterable*, followed by *fillvalue*, such that at least *n* items are emitted. >>> list(padded([1, 2, 3], '?', 5)) [1, 2, 3, '?', '?'] If *next_multiple* is ``True``, *fillvalue* will be emitted until the number of items emitted is a multiple of *n*:: >>> list(padded([1, 2, 3, 4], n=3, next_multiple=True)) [1, 2, 3, 4, None, None] If *n* is ``None``, *fillvalue* will be emitted indefinitely. """ it = iter(iterable) if n is None: yield from chain(it, repeat(fillvalue)) elif n < 1: raise ValueError('n must be at least 1') else: item_count = 0 for item in it: yield item item_count += 1 remaining = (n - item_count) % n if next_multiple else n - item_count for _ in range(remaining): yield fillvalue def repeat_each(iterable, n=2): """Repeat each element in *iterable* *n* times. >>> list(repeat_each('ABC', 3)) ['A', 'A', 'A', 'B', 'B', 'B', 'C', 'C', 'C'] """ return chain.from_iterable(map(repeat, iterable, repeat(n))) def repeat_last(iterable, default=None): """After the *iterable* is exhausted, keep yielding its last element. >>> list(islice(repeat_last(range(3)), 5)) [0, 1, 2, 2, 2] If the iterable is empty, yield *default* forever:: >>> list(islice(repeat_last(range(0), 42), 5)) [42, 42, 42, 42, 42] """ item = _marker for item in iterable: yield item final = default if item is _marker else item yield from repeat(final) def distribute(n, iterable): """Distribute the items from *iterable* among *n* smaller iterables. >>> group_1, group_2 = distribute(2, [1, 2, 3, 4, 5, 6]) >>> list(group_1) [1, 3, 5] >>> list(group_2) [2, 4, 6] If the length of *iterable* is not evenly divisible by *n*, then the length of the returned iterables will not be identical: >>> children = distribute(3, [1, 2, 3, 4, 5, 6, 7]) >>> [list(c) for c in children] [[1, 4, 7], [2, 5], [3, 6]] If the length of *iterable* is smaller than *n*, then the last returned iterables will be empty: >>> children = distribute(5, [1, 2, 3]) >>> [list(c) for c in children] [[1], [2], [3], [], []] This function uses :func:`itertools.tee` and may require significant storage. If you need the order items in the smaller iterables to match the original iterable, see :func:`divide`. """ if n < 1: raise ValueError('n must be at least 1') children = tee(iterable, n) return [islice(it, index, None, n) for index, it in enumerate(children)] def stagger(iterable, offsets=(-1, 0, 1), longest=False, fillvalue=None): """Yield tuples whose elements are offset from *iterable*. The amount by which the `i`-th item in each tuple is offset is given by the `i`-th item in *offsets*. >>> list(stagger([0, 1, 2, 3])) [(None, 0, 1), (0, 1, 2), (1, 2, 3)] >>> list(stagger(range(8), offsets=(0, 2, 4))) [(0, 2, 4), (1, 3, 5), (2, 4, 6), (3, 5, 7)] By default, the sequence will end when the final element of a tuple is the last item in the iterable. To continue until the first element of a tuple is the last item in the iterable, set *longest* to ``True``:: >>> list(stagger([0, 1, 2, 3], longest=True)) [(None, 0, 1), (0, 1, 2), (1, 2, 3), (2, 3, None), (3, None, None)] By default, ``None`` will be used to replace offsets beyond the end of the sequence. Specify *fillvalue* to use some other value. """ children = tee(iterable, len(offsets)) return zip_offset( *children, offsets=offsets, longest=longest, fillvalue=fillvalue ) class UnequalIterablesError(ValueError): def __init__(self, details=None): msg = 'Iterables have different lengths' if details is not None: msg += (': index 0 has length {}; index {} has length {}').format( *details ) super().__init__(msg) def _zip_equal_generator(iterables): for combo in zip_longest(*iterables, fillvalue=_marker): for val in combo: if val is _marker: raise UnequalIterablesError() yield combo def zip_equal(*iterables): """``zip`` the input *iterables* together, but raise ``UnequalIterablesError`` if they aren't all the same length. >>> it_1 = range(3) >>> it_2 = iter('abc') >>> list(zip_equal(it_1, it_2)) [(0, 'a'), (1, 'b'), (2, 'c')] >>> it_1 = range(3) >>> it_2 = iter('abcd') >>> list(zip_equal(it_1, it_2)) # doctest: +IGNORE_EXCEPTION_DETAIL Traceback (most recent call last): ... more_itertools.more.UnequalIterablesError: Iterables have different lengths """ if hexversion >= 0x30A00A6: warnings.warn( ( 'zip_equal will be removed in a future version of ' 'more-itertools. Use the builtin zip function with ' 'strict=True instead.' ), DeprecationWarning, ) # Check whether the iterables are all the same size. try: first_size = len(iterables[0]) for i, it in enumerate(iterables[1:], 1): size = len(it) if size != first_size: break else: # If we didn't break out, we can use the built-in zip. return zip(*iterables) # If we did break out, there was a mismatch. raise UnequalIterablesError(details=(first_size, i, size)) # If any one of the iterables didn't have a length, start reading # them until one runs out. except TypeError: return _zip_equal_generator(iterables) def zip_offset(*iterables, offsets, longest=False, fillvalue=None): """``zip`` the input *iterables* together, but offset the `i`-th iterable by the `i`-th item in *offsets*. >>> list(zip_offset('0123', 'abcdef', offsets=(0, 1))) [('0', 'b'), ('1', 'c'), ('2', 'd'), ('3', 'e')] This can be used as a lightweight alternative to SciPy or pandas to analyze data sets in which some series have a lead or lag relationship. By default, the sequence will end when the shortest iterable is exhausted. To continue until the longest iterable is exhausted, set *longest* to ``True``. >>> list(zip_offset('0123', 'abcdef', offsets=(0, 1), longest=True)) [('0', 'b'), ('1', 'c'), ('2', 'd'), ('3', 'e'), (None, 'f')] By default, ``None`` will be used to replace offsets beyond the end of the sequence. Specify *fillvalue* to use some other value. """ if len(iterables) != len(offsets): raise ValueError("Number of iterables and offsets didn't match") staggered = [] for it, n in zip(iterables, offsets): if n < 0: staggered.append(chain(repeat(fillvalue, -n), it)) elif n > 0: staggered.append(islice(it, n, None)) else: staggered.append(it) if longest: return zip_longest(*staggered, fillvalue=fillvalue) return zip(*staggered) def sort_together(iterables, key_list=(0,), key=None, reverse=False): """Return the input iterables sorted together, with *key_list* as the priority for sorting. All iterables are trimmed to the length of the shortest one. This can be used like the sorting function in a spreadsheet. If each iterable represents a column of data, the key list determines which columns are used for sorting. By default, all iterables are sorted using the ``0``-th iterable:: >>> iterables = [(4, 3, 2, 1), ('a', 'b', 'c', 'd')] >>> sort_together(iterables) [(1, 2, 3, 4), ('d', 'c', 'b', 'a')] Set a different key list to sort according to another iterable. Specifying multiple keys dictates how ties are broken:: >>> iterables = [(3, 1, 2), (0, 1, 0), ('c', 'b', 'a')] >>> sort_together(iterables, key_list=(1, 2)) [(2, 3, 1), (0, 0, 1), ('a', 'c', 'b')] To sort by a function of the elements of the iterable, pass a *key* function. Its arguments are the elements of the iterables corresponding to the key list:: >>> names = ('a', 'b', 'c') >>> lengths = (1, 2, 3) >>> widths = (5, 2, 1) >>> def area(length, width): ... return length * width >>> sort_together([names, lengths, widths], key_list=(1, 2), key=area) [('c', 'b', 'a'), (3, 2, 1), (1, 2, 5)] Set *reverse* to ``True`` to sort in descending order. >>> sort_together([(1, 2, 3), ('c', 'b', 'a')], reverse=True) [(3, 2, 1), ('a', 'b', 'c')] """ if key is None: # if there is no key function, the key argument to sorted is an # itemgetter key_argument = itemgetter(*key_list) else: # if there is a key function, call it with the items at the offsets # specified by the key function as arguments key_list = list(key_list) if len(key_list) == 1: # if key_list contains a single item, pass the item at that offset # as the only argument to the key function key_offset = key_list[0] key_argument = lambda zipped_items: key(zipped_items[key_offset]) else: # if key_list contains multiple items, use itemgetter to return a # tuple of items, which we pass as *args to the key function get_key_items = itemgetter(*key_list) key_argument = lambda zipped_items: key( *get_key_items(zipped_items) ) return list( zip(*sorted(zip(*iterables), key=key_argument, reverse=reverse)) ) def unzip(iterable): """The inverse of :func:`zip`, this function disaggregates the elements of the zipped *iterable*. The ``i``-th iterable contains the ``i``-th element from each element of the zipped iterable. The first element is used to to determine the length of the remaining elements. >>> iterable = [('a', 1), ('b', 2), ('c', 3), ('d', 4)] >>> letters, numbers = unzip(iterable) >>> list(letters) ['a', 'b', 'c', 'd'] >>> list(numbers) [1, 2, 3, 4] This is similar to using ``zip(*iterable)``, but it avoids reading *iterable* into memory. Note, however, that this function uses :func:`itertools.tee` and thus may require significant storage. """ head, iterable = spy(iter(iterable)) if not head: # empty iterable, e.g. zip([], [], []) return () # spy returns a one-length iterable as head head = head[0] iterables = tee(iterable, len(head)) def itemgetter(i): def getter(obj): try: return obj[i] except IndexError: # basically if we have an iterable like # iter([(1, 2, 3), (4, 5), (6,)]) # the second unzipped iterable would fail at the third tuple # since it would try to access tup[1] # same with the third unzipped iterable and the second tuple # to support these "improperly zipped" iterables, # we create a custom itemgetter # which just stops the unzipped iterables # at first length mismatch raise StopIteration return getter return tuple(map(itemgetter(i), it) for i, it in enumerate(iterables)) def divide(n, iterable): """Divide the elements from *iterable* into *n* parts, maintaining order. >>> group_1, group_2 = divide(2, [1, 2, 3, 4, 5, 6]) >>> list(group_1) [1, 2, 3] >>> list(group_2) [4, 5, 6] If the length of *iterable* is not evenly divisible by *n*, then the length of the returned iterables will not be identical: >>> children = divide(3, [1, 2, 3, 4, 5, 6, 7]) >>> [list(c) for c in children] [[1, 2, 3], [4, 5], [6, 7]] If the length of the iterable is smaller than n, then the last returned iterables will be empty: >>> children = divide(5, [1, 2, 3]) >>> [list(c) for c in children] [[1], [2], [3], [], []] This function will exhaust the iterable before returning and may require significant storage. If order is not important, see :func:`distribute`, which does not first pull the iterable into memory. """ if n < 1: raise ValueError('n must be at least 1') try: iterable[:0] except TypeError: seq = tuple(iterable) else: seq = iterable q, r = divmod(len(seq), n) ret = [] stop = 0 for i in range(1, n + 1): start = stop stop += q + 1 if i <= r else q ret.append(iter(seq[start:stop])) return ret def always_iterable(obj, base_type=(str, bytes)): """If *obj* is iterable, return an iterator over its items:: >>> obj = (1, 2, 3) >>> list(always_iterable(obj)) [1, 2, 3] If *obj* is not iterable, return a one-item iterable containing *obj*:: >>> obj = 1 >>> list(always_iterable(obj)) [1] If *obj* is ``None``, return an empty iterable: >>> obj = None >>> list(always_iterable(None)) [] By default, binary and text strings are not considered iterable:: >>> obj = 'foo' >>> list(always_iterable(obj)) ['foo'] If *base_type* is set, objects for which ``isinstance(obj, base_type)`` returns ``True`` won't be considered iterable. >>> obj = {'a': 1} >>> list(always_iterable(obj)) # Iterate over the dict's keys ['a'] >>> list(always_iterable(obj, base_type=dict)) # Treat dicts as a unit [{'a': 1}] Set *base_type* to ``None`` to avoid any special handling and treat objects Python considers iterable as iterable: >>> obj = 'foo' >>> list(always_iterable(obj, base_type=None)) ['f', 'o', 'o'] """ if obj is None: return iter(()) if (base_type is not None) and isinstance(obj, base_type): return iter((obj,)) try: return iter(obj) except TypeError: return iter((obj,)) def adjacent(predicate, iterable, distance=1): """Return an iterable over `(bool, item)` tuples where the `item` is drawn from *iterable* and the `bool` indicates whether that item satisfies the *predicate* or is adjacent to an item that does. For example, to find whether items are adjacent to a ``3``:: >>> list(adjacent(lambda x: x == 3, range(6))) [(False, 0), (False, 1), (True, 2), (True, 3), (True, 4), (False, 5)] Set *distance* to change what counts as adjacent. For example, to find whether items are two places away from a ``3``: >>> list(adjacent(lambda x: x == 3, range(6), distance=2)) [(False, 0), (True, 1), (True, 2), (True, 3), (True, 4), (True, 5)] This is useful for contextualizing the results of a search function. For example, a code comparison tool might want to identify lines that have changed, but also surrounding lines to give the viewer of the diff context. The predicate function will only be called once for each item in the iterable. See also :func:`groupby_transform`, which can be used with this function to group ranges of items with the same `bool` value. """ # Allow distance=0 mainly for testing that it reproduces results with map() if distance < 0: raise ValueError('distance must be at least 0') i1, i2 = tee(iterable) padding = [False] * distance selected = chain(padding, map(predicate, i1), padding) adjacent_to_selected = map(any, windowed(selected, 2 * distance + 1)) return zip(adjacent_to_selected, i2) def groupby_transform(iterable, keyfunc=None, valuefunc=None, reducefunc=None): """An extension of :func:`itertools.groupby` that can apply transformations to the grouped data. * *keyfunc* is a function computing a key value for each item in *iterable* * *valuefunc* is a function that transforms the individual items from *iterable* after grouping * *reducefunc* is a function that transforms each group of items >>> iterable = 'aAAbBBcCC' >>> keyfunc = lambda k: k.upper() >>> valuefunc = lambda v: v.lower() >>> reducefunc = lambda g: ''.join(g) >>> list(groupby_transform(iterable, keyfunc, valuefunc, reducefunc)) [('A', 'aaa'), ('B', 'bbb'), ('C', 'ccc')] Each optional argument defaults to an identity function if not specified. :func:`groupby_transform` is useful when grouping elements of an iterable using a separate iterable as the key. To do this, :func:`zip` the iterables and pass a *keyfunc* that extracts the first element and a *valuefunc* that extracts the second element:: >>> from operator import itemgetter >>> keys = [0, 0, 1, 1, 1, 2, 2, 2, 3] >>> values = 'abcdefghi' >>> iterable = zip(keys, values) >>> grouper = groupby_transform(iterable, itemgetter(0), itemgetter(1)) >>> [(k, ''.join(g)) for k, g in grouper] [(0, 'ab'), (1, 'cde'), (2, 'fgh'), (3, 'i')] Note that the order of items in the iterable is significant. Only adjacent items are grouped together, so if you don't want any duplicate groups, you should sort the iterable by the key function. """ ret = groupby(iterable, keyfunc) if valuefunc: ret = ((k, map(valuefunc, g)) for k, g in ret) if reducefunc: ret = ((k, reducefunc(g)) for k, g in ret) return ret class numeric_range(abc.Sequence, abc.Hashable): """An extension of the built-in ``range()`` function whose arguments can be any orderable numeric type. With only *stop* specified, *start* defaults to ``0`` and *step* defaults to ``1``. The output items will match the type of *stop*: >>> list(numeric_range(3.5)) [0.0, 1.0, 2.0, 3.0] With only *start* and *stop* specified, *step* defaults to ``1``. The output items will match the type of *start*: >>> from decimal import Decimal >>> start = Decimal('2.1') >>> stop = Decimal('5.1') >>> list(numeric_range(start, stop)) [Decimal('2.1'), Decimal('3.1'), Decimal('4.1')] With *start*, *stop*, and *step* specified the output items will match the type of ``start + step``: >>> from fractions import Fraction >>> start = Fraction(1, 2) # Start at 1/2 >>> stop = Fraction(5, 2) # End at 5/2 >>> step = Fraction(1, 2) # Count by 1/2 >>> list(numeric_range(start, stop, step)) [Fraction(1, 2), Fraction(1, 1), Fraction(3, 2), Fraction(2, 1)] If *step* is zero, ``ValueError`` is raised. Negative steps are supported: >>> list(numeric_range(3, -1, -1.0)) [3.0, 2.0, 1.0, 0.0] Be aware of the limitations of floating point numbers; the representation of the yielded numbers may be surprising. ``datetime.datetime`` objects can be used for *start* and *stop*, if *step* is a ``datetime.timedelta`` object: >>> import datetime >>> start = datetime.datetime(2019, 1, 1) >>> stop = datetime.datetime(2019, 1, 3) >>> step = datetime.timedelta(days=1) >>> items = iter(numeric_range(start, stop, step)) >>> next(items) datetime.datetime(2019, 1, 1, 0, 0) >>> next(items) datetime.datetime(2019, 1, 2, 0, 0) """ _EMPTY_HASH = hash(range(0, 0)) def __init__(self, *args): argc = len(args) if argc == 1: (self._stop,) = args self._start = type(self._stop)(0) self._step = type(self._stop - self._start)(1) elif argc == 2: self._start, self._stop = args self._step = type(self._stop - self._start)(1) elif argc == 3: self._start, self._stop, self._step = args elif argc == 0: raise TypeError( 'numeric_range expected at least ' '1 argument, got {}'.format(argc) ) else: raise TypeError( 'numeric_range expected at most ' '3 arguments, got {}'.format(argc) ) self._zero = type(self._step)(0) if self._step == self._zero: raise ValueError('numeric_range() arg 3 must not be zero') self._growing = self._step > self._zero self._init_len() def __bool__(self): if self._growing: return self._start < self._stop else: return self._start > self._stop def __contains__(self, elem): if self._growing: if self._start <= elem < self._stop: return (elem - self._start) % self._step == self._zero else: if self._start >= elem > self._stop: return (self._start - elem) % (-self._step) == self._zero return False def __eq__(self, other): if isinstance(other, numeric_range): empty_self = not bool(self) empty_other = not bool(other) if empty_self or empty_other: return empty_self and empty_other # True if both empty else: return ( self._start == other._start and self._step == other._step and self._get_by_index(-1) == other._get_by_index(-1) ) else: return False def __getitem__(self, key): if isinstance(key, int): return self._get_by_index(key) elif isinstance(key, slice): step = self._step if key.step is None else key.step * self._step if key.start is None or key.start <= -self._len: start = self._start elif key.start >= self._len: start = self._stop else: # -self._len < key.start < self._len start = self._get_by_index(key.start) if key.stop is None or key.stop >= self._len: stop = self._stop elif key.stop <= -self._len: stop = self._start else: # -self._len < key.stop < self._len stop = self._get_by_index(key.stop) return numeric_range(start, stop, step) else: raise TypeError( 'numeric range indices must be ' 'integers or slices, not {}'.format(type(key).__name__) ) def __hash__(self): if self: return hash((self._start, self._get_by_index(-1), self._step)) else: return self._EMPTY_HASH def __iter__(self): values = (self._start + (n * self._step) for n in count()) if self._growing: return takewhile(partial(gt, self._stop), values) else: return takewhile(partial(lt, self._stop), values) def __len__(self): return self._len def _init_len(self): if self._growing: start = self._start stop = self._stop step = self._step else: start = self._stop stop = self._start step = -self._step distance = stop - start if distance <= self._zero: self._len = 0 else: # distance > 0 and step > 0: regular euclidean division q, r = divmod(distance, step) self._len = int(q) + int(r != self._zero) def __reduce__(self): return numeric_range, (self._start, self._stop, self._step) def __repr__(self): if self._step == 1: return "numeric_range({}, {})".format( repr(self._start), repr(self._stop) ) else: return "numeric_range({}, {}, {})".format( repr(self._start), repr(self._stop), repr(self._step) ) def __reversed__(self): return iter( numeric_range( self._get_by_index(-1), self._start - self._step, -self._step ) ) def count(self, value): return int(value in self) def index(self, value): if self._growing: if self._start <= value < self._stop: q, r = divmod(value - self._start, self._step) if r == self._zero: return int(q) else: if self._start >= value > self._stop: q, r = divmod(self._start - value, -self._step) if r == self._zero: return int(q) raise ValueError("{} is not in numeric range".format(value)) def _get_by_index(self, i): if i < 0: i += self._len if i < 0 or i >= self._len: raise IndexError("numeric range object index out of range") return self._start + i * self._step def count_cycle(iterable, n=None): """Cycle through the items from *iterable* up to *n* times, yielding the number of completed cycles along with each item. If *n* is omitted the process repeats indefinitely. >>> list(count_cycle('AB', 3)) [(0, 'A'), (0, 'B'), (1, 'A'), (1, 'B'), (2, 'A'), (2, 'B')] """ iterable = tuple(iterable) if not iterable: return iter(()) counter = count() if n is None else range(n) return ((i, item) for i in counter for item in iterable) def mark_ends(iterable): """Yield 3-tuples of the form ``(is_first, is_last, item)``. >>> list(mark_ends('ABC')) [(True, False, 'A'), (False, False, 'B'), (False, True, 'C')] Use this when looping over an iterable to take special action on its first and/or last items: >>> iterable = ['Header', 100, 200, 'Footer'] >>> total = 0 >>> for is_first, is_last, item in mark_ends(iterable): ... if is_first: ... continue # Skip the header ... if is_last: ... continue # Skip the footer ... total += item >>> print(total) 300 """ it = iter(iterable) try: b = next(it) except StopIteration: return try: for i in count(): a = b b = next(it) yield i == 0, False, a except StopIteration: yield i == 0, True, a def locate(iterable, pred=bool, window_size=None): """Yield the index of each item in *iterable* for which *pred* returns ``True``. *pred* defaults to :func:`bool`, which will select truthy items: >>> list(locate([0, 1, 1, 0, 1, 0, 0])) [1, 2, 4] Set *pred* to a custom function to, e.g., find the indexes for a particular item. >>> list(locate(['a', 'b', 'c', 'b'], lambda x: x == 'b')) [1, 3] If *window_size* is given, then the *pred* function will be called with that many items. This enables searching for sub-sequences: >>> iterable = [0, 1, 2, 3, 0, 1, 2, 3, 0, 1, 2, 3] >>> pred = lambda *args: args == (1, 2, 3) >>> list(locate(iterable, pred=pred, window_size=3)) [1, 5, 9] Use with :func:`seekable` to find indexes and then retrieve the associated items: >>> from itertools import count >>> from more_itertools import seekable >>> source = (3 * n + 1 if (n % 2) else n // 2 for n in count()) >>> it = seekable(source) >>> pred = lambda x: x > 100 >>> indexes = locate(it, pred=pred) >>> i = next(indexes) >>> it.seek(i) >>> next(it) 106 """ if window_size is None: return compress(count(), map(pred, iterable)) if window_size < 1: raise ValueError('window size must be at least 1') it = windowed(iterable, window_size, fillvalue=_marker) return compress(count(), starmap(pred, it)) def lstrip(iterable, pred): """Yield the items from *iterable*, but strip any from the beginning for which *pred* returns ``True``. For example, to remove a set of items from the start of an iterable: >>> iterable = (None, False, None, 1, 2, None, 3, False, None) >>> pred = lambda x: x in {None, False, ''} >>> list(lstrip(iterable, pred)) [1, 2, None, 3, False, None] This function is analogous to to :func:`str.lstrip`, and is essentially an wrapper for :func:`itertools.dropwhile`. """ return dropwhile(pred, iterable) def rstrip(iterable, pred): """Yield the items from *iterable*, but strip any from the end for which *pred* returns ``True``. For example, to remove a set of items from the end of an iterable: >>> iterable = (None, False, None, 1, 2, None, 3, False, None) >>> pred = lambda x: x in {None, False, ''} >>> list(rstrip(iterable, pred)) [None, False, None, 1, 2, None, 3] This function is analogous to :func:`str.rstrip`. """ cache = [] cache_append = cache.append cache_clear = cache.clear for x in iterable: if pred(x): cache_append(x) else: yield from cache cache_clear() yield x def strip(iterable, pred): """Yield the items from *iterable*, but strip any from the beginning and end for which *pred* returns ``True``. For example, to remove a set of items from both ends of an iterable: >>> iterable = (None, False, None, 1, 2, None, 3, False, None) >>> pred = lambda x: x in {None, False, ''} >>> list(strip(iterable, pred)) [1, 2, None, 3] This function is analogous to :func:`str.strip`. """ return rstrip(lstrip(iterable, pred), pred) class islice_extended: """An extension of :func:`itertools.islice` that supports negative values for *stop*, *start*, and *step*. >>> iterable = iter('abcdefgh') >>> list(islice_extended(iterable, -4, -1)) ['e', 'f', 'g'] Slices with negative values require some caching of *iterable*, but this function takes care to minimize the amount of memory required. For example, you can use a negative step with an infinite iterator: >>> from itertools import count >>> list(islice_extended(count(), 110, 99, -2)) [110, 108, 106, 104, 102, 100] You can also use slice notation directly: >>> iterable = map(str, count()) >>> it = islice_extended(iterable)[10:20:2] >>> list(it) ['10', '12', '14', '16', '18'] """ def __init__(self, iterable, *args): it = iter(iterable) if args: self._iterable = _islice_helper(it, slice(*args)) else: self._iterable = it def __iter__(self): return self def __next__(self): return next(self._iterable) def __getitem__(self, key): if isinstance(key, slice): return islice_extended(_islice_helper(self._iterable, key)) raise TypeError('islice_extended.__getitem__ argument must be a slice') def _islice_helper(it, s): start = s.start stop = s.stop if s.step == 0: raise ValueError('step argument must be a non-zero integer or None.') step = s.step or 1 if step > 0: start = 0 if (start is None) else start if start < 0: # Consume all but the last -start items cache = deque(enumerate(it, 1), maxlen=-start) len_iter = cache[-1][0] if cache else 0 # Adjust start to be positive i = max(len_iter + start, 0) # Adjust stop to be positive if stop is None: j = len_iter elif stop >= 0: j = min(stop, len_iter) else: j = max(len_iter + stop, 0) # Slice the cache n = j - i if n <= 0: return for index, item in islice(cache, 0, n, step): yield item elif (stop is not None) and (stop < 0): # Advance to the start position next(islice(it, start, start), None) # When stop is negative, we have to carry -stop items while # iterating cache = deque(islice(it, -stop), maxlen=-stop) for index, item in enumerate(it): cached_item = cache.popleft() if index % step == 0: yield cached_item cache.append(item) else: # When both start and stop are positive we have the normal case yield from islice(it, start, stop, step) else: start = -1 if (start is None) else start if (stop is not None) and (stop < 0): # Consume all but the last items n = -stop - 1 cache = deque(enumerate(it, 1), maxlen=n) len_iter = cache[-1][0] if cache else 0 # If start and stop are both negative they are comparable and # we can just slice. Otherwise we can adjust start to be negative # and then slice. if start < 0: i, j = start, stop else: i, j = min(start - len_iter, -1), None for index, item in list(cache)[i:j:step]: yield item else: # Advance to the stop position if stop is not None: m = stop + 1 next(islice(it, m, m), None) # stop is positive, so if start is negative they are not comparable # and we need the rest of the items. if start < 0: i = start n = None # stop is None and start is positive, so we just need items up to # the start index. elif stop is None: i = None n = start + 1 # Both stop and start are positive, so they are comparable. else: i = None n = start - stop if n <= 0: return cache = list(islice(it, n)) yield from cache[i::step] def always_reversible(iterable): """An extension of :func:`reversed` that supports all iterables, not just those which implement the ``Reversible`` or ``Sequence`` protocols. >>> print(*always_reversible(x for x in range(3))) 2 1 0 If the iterable is already reversible, this function returns the result of :func:`reversed()`. If the iterable is not reversible, this function will cache the remaining items in the iterable and yield them in reverse order, which may require significant storage. """ try: return reversed(iterable) except TypeError: return reversed(list(iterable)) def consecutive_groups(iterable, ordering=lambda x: x): """Yield groups of consecutive items using :func:`itertools.groupby`. The *ordering* function determines whether two items are adjacent by returning their position. By default, the ordering function is the identity function. This is suitable for finding runs of numbers: >>> iterable = [1, 10, 11, 12, 20, 30, 31, 32, 33, 40] >>> for group in consecutive_groups(iterable): ... print(list(group)) [1] [10, 11, 12] [20] [30, 31, 32, 33] [40] For finding runs of adjacent letters, try using the :meth:`index` method of a string of letters: >>> from string import ascii_lowercase >>> iterable = 'abcdfgilmnop' >>> ordering = ascii_lowercase.index >>> for group in consecutive_groups(iterable, ordering): ... print(list(group)) ['a', 'b', 'c', 'd'] ['f', 'g'] ['i'] ['l', 'm', 'n', 'o', 'p'] Each group of consecutive items is an iterator that shares it source with *iterable*. When an an output group is advanced, the previous group is no longer available unless its elements are copied (e.g., into a ``list``). >>> iterable = [1, 2, 11, 12, 21, 22] >>> saved_groups = [] >>> for group in consecutive_groups(iterable): ... saved_groups.append(list(group)) # Copy group elements >>> saved_groups [[1, 2], [11, 12], [21, 22]] """ for k, g in groupby( enumerate(iterable), key=lambda x: x[0] - ordering(x[1]) ): yield map(itemgetter(1), g) def difference(iterable, func=sub, *, initial=None): """This function is the inverse of :func:`itertools.accumulate`. By default it will compute the first difference of *iterable* using :func:`operator.sub`: >>> from itertools import accumulate >>> iterable = accumulate([0, 1, 2, 3, 4]) # produces 0, 1, 3, 6, 10 >>> list(difference(iterable)) [0, 1, 2, 3, 4] *func* defaults to :func:`operator.sub`, but other functions can be specified. They will be applied as follows:: A, B, C, D, ... --> A, func(B, A), func(C, B), func(D, C), ... For example, to do progressive division: >>> iterable = [1, 2, 6, 24, 120] >>> func = lambda x, y: x // y >>> list(difference(iterable, func)) [1, 2, 3, 4, 5] If the *initial* keyword is set, the first element will be skipped when computing successive differences. >>> it = [10, 11, 13, 16] # from accumulate([1, 2, 3], initial=10) >>> list(difference(it, initial=10)) [1, 2, 3] """ a, b = tee(iterable) try: first = [next(b)] except StopIteration: return iter([]) if initial is not None: first = [] return chain(first, starmap(func, zip(b, a))) class SequenceView(Sequence): """Return a read-only view of the sequence object *target*. :class:`SequenceView` objects are analogous to Python's built-in "dictionary view" types. They provide a dynamic view of a sequence's items, meaning that when the sequence updates, so does the view. >>> seq = ['0', '1', '2'] >>> view = SequenceView(seq) >>> view SequenceView(['0', '1', '2']) >>> seq.append('3') >>> view SequenceView(['0', '1', '2', '3']) Sequence views support indexing, slicing, and length queries. They act like the underlying sequence, except they don't allow assignment: >>> view[1] '1' >>> view[1:-1] ['1', '2'] >>> len(view) 4 Sequence views are useful as an alternative to copying, as they don't require (much) extra storage. """ def __init__(self, target): if not isinstance(target, Sequence): raise TypeError self._target = target def __getitem__(self, index): return self._target[index] def __len__(self): return len(self._target) def __repr__(self): return '{}({})'.format(self.__class__.__name__, repr(self._target)) class seekable: """Wrap an iterator to allow for seeking backward and forward. This progressively caches the items in the source iterable so they can be re-visited. Call :meth:`seek` with an index to seek to that position in the source iterable. To "reset" an iterator, seek to ``0``: >>> from itertools import count >>> it = seekable((str(n) for n in count())) >>> next(it), next(it), next(it) ('0', '1', '2') >>> it.seek(0) >>> next(it), next(it), next(it) ('0', '1', '2') >>> next(it) '3' You can also seek forward: >>> it = seekable((str(n) for n in range(20))) >>> it.seek(10) >>> next(it) '10' >>> it.seek(20) # Seeking past the end of the source isn't a problem >>> list(it) [] >>> it.seek(0) # Resetting works even after hitting the end >>> next(it), next(it), next(it) ('0', '1', '2') Call :meth:`peek` to look ahead one item without advancing the iterator: >>> it = seekable('1234') >>> it.peek() '1' >>> list(it) ['1', '2', '3', '4'] >>> it.peek(default='empty') 'empty' Before the iterator is at its end, calling :func:`bool` on it will return ``True``. After it will return ``False``: >>> it = seekable('5678') >>> bool(it) True >>> list(it) ['5', '6', '7', '8'] >>> bool(it) False You may view the contents of the cache with the :meth:`elements` method. That returns a :class:`SequenceView`, a view that updates automatically: >>> it = seekable((str(n) for n in range(10))) >>> next(it), next(it), next(it) ('0', '1', '2') >>> elements = it.elements() >>> elements SequenceView(['0', '1', '2']) >>> next(it) '3' >>> elements SequenceView(['0', '1', '2', '3']) By default, the cache grows as the source iterable progresses, so beware of wrapping very large or infinite iterables. Supply *maxlen* to limit the size of the cache (this of course limits how far back you can seek). >>> from itertools import count >>> it = seekable((str(n) for n in count()), maxlen=2) >>> next(it), next(it), next(it), next(it) ('0', '1', '2', '3') >>> list(it.elements()) ['2', '3'] >>> it.seek(0) >>> next(it), next(it), next(it), next(it) ('2', '3', '4', '5') >>> next(it) '6' """ def __init__(self, iterable, maxlen=None): self._source = iter(iterable) if maxlen is None: self._cache = [] else: self._cache = deque([], maxlen) self._index = None def __iter__(self): return self def __next__(self): if self._index is not None: try: item = self._cache[self._index] except IndexError: self._index = None else: self._index += 1 return item item = next(self._source) self._cache.append(item) return item def __bool__(self): try: self.peek() except StopIteration: return False return True def peek(self, default=_marker): try: peeked = next(self) except StopIteration: if default is _marker: raise return default if self._index is None: self._index = len(self._cache) self._index -= 1 return peeked def elements(self): return SequenceView(self._cache) def seek(self, index): self._index = index remainder = index - len(self._cache) if remainder > 0: consume(self, remainder) class run_length: """ :func:`run_length.encode` compresses an iterable with run-length encoding. It yields groups of repeated items with the count of how many times they were repeated: >>> uncompressed = 'abbcccdddd' >>> list(run_length.encode(uncompressed)) [('a', 1), ('b', 2), ('c', 3), ('d', 4)] :func:`run_length.decode` decompresses an iterable that was previously compressed with run-length encoding. It yields the items of the decompressed iterable: >>> compressed = [('a', 1), ('b', 2), ('c', 3), ('d', 4)] >>> list(run_length.decode(compressed)) ['a', 'b', 'b', 'c', 'c', 'c', 'd', 'd', 'd', 'd'] """ @staticmethod def encode(iterable): return ((k, ilen(g)) for k, g in groupby(iterable)) @staticmethod def decode(iterable): return chain.from_iterable(repeat(k, n) for k, n in iterable) def exactly_n(iterable, n, predicate=bool): """Return ``True`` if exactly ``n`` items in the iterable are ``True`` according to the *predicate* function. >>> exactly_n([True, True, False], 2) True >>> exactly_n([True, True, False], 1) False >>> exactly_n([0, 1, 2, 3, 4, 5], 3, lambda x: x < 3) True The iterable will be advanced until ``n + 1`` truthy items are encountered, so avoid calling it on infinite iterables. """ return len(take(n + 1, filter(predicate, iterable))) == n def circular_shifts(iterable): """Return a list of circular shifts of *iterable*. >>> circular_shifts(range(4)) [(0, 1, 2, 3), (1, 2, 3, 0), (2, 3, 0, 1), (3, 0, 1, 2)] """ lst = list(iterable) return take(len(lst), windowed(cycle(lst), len(lst))) def make_decorator(wrapping_func, result_index=0): """Return a decorator version of *wrapping_func*, which is a function that modifies an iterable. *result_index* is the position in that function's signature where the iterable goes. This lets you use itertools on the "production end," i.e. at function definition. This can augment what the function returns without changing the function's code. For example, to produce a decorator version of :func:`chunked`: >>> from more_itertools import chunked >>> chunker = make_decorator(chunked, result_index=0) >>> @chunker(3) ... def iter_range(n): ... return iter(range(n)) ... >>> list(iter_range(9)) [[0, 1, 2], [3, 4, 5], [6, 7, 8]] To only allow truthy items to be returned: >>> truth_serum = make_decorator(filter, result_index=1) >>> @truth_serum(bool) ... def boolean_test(): ... return [0, 1, '', ' ', False, True] ... >>> list(boolean_test()) [1, ' ', True] The :func:`peekable` and :func:`seekable` wrappers make for practical decorators: >>> from more_itertools import peekable >>> peekable_function = make_decorator(peekable) >>> @peekable_function() ... def str_range(*args): ... return (str(x) for x in range(*args)) ... >>> it = str_range(1, 20, 2) >>> next(it), next(it), next(it) ('1', '3', '5') >>> it.peek() '7' >>> next(it) '7' """ # See https://sites.google.com/site/bbayles/index/decorator_factory for # notes on how this works. def decorator(*wrapping_args, **wrapping_kwargs): def outer_wrapper(f): def inner_wrapper(*args, **kwargs): result = f(*args, **kwargs) wrapping_args_ = list(wrapping_args) wrapping_args_.insert(result_index, result) return wrapping_func(*wrapping_args_, **wrapping_kwargs) return inner_wrapper return outer_wrapper return decorator def map_reduce(iterable, keyfunc, valuefunc=None, reducefunc=None): """Return a dictionary that maps the items in *iterable* to categories defined by *keyfunc*, transforms them with *valuefunc*, and then summarizes them by category with *reducefunc*. *valuefunc* defaults to the identity function if it is unspecified. If *reducefunc* is unspecified, no summarization takes place: >>> keyfunc = lambda x: x.upper() >>> result = map_reduce('abbccc', keyfunc) >>> sorted(result.items()) [('A', ['a']), ('B', ['b', 'b']), ('C', ['c', 'c', 'c'])] Specifying *valuefunc* transforms the categorized items: >>> keyfunc = lambda x: x.upper() >>> valuefunc = lambda x: 1 >>> result = map_reduce('abbccc', keyfunc, valuefunc) >>> sorted(result.items()) [('A', [1]), ('B', [1, 1]), ('C', [1, 1, 1])] Specifying *reducefunc* summarizes the categorized items: >>> keyfunc = lambda x: x.upper() >>> valuefunc = lambda x: 1 >>> reducefunc = sum >>> result = map_reduce('abbccc', keyfunc, valuefunc, reducefunc) >>> sorted(result.items()) [('A', 1), ('B', 2), ('C', 3)] You may want to filter the input iterable before applying the map/reduce procedure: >>> all_items = range(30) >>> items = [x for x in all_items if 10 <= x <= 20] # Filter >>> keyfunc = lambda x: x % 2 # Evens map to 0; odds to 1 >>> categories = map_reduce(items, keyfunc=keyfunc) >>> sorted(categories.items()) [(0, [10, 12, 14, 16, 18, 20]), (1, [11, 13, 15, 17, 19])] >>> summaries = map_reduce(items, keyfunc=keyfunc, reducefunc=sum) >>> sorted(summaries.items()) [(0, 90), (1, 75)] Note that all items in the iterable are gathered into a list before the summarization step, which may require significant storage. The returned object is a :obj:`collections.defaultdict` with the ``default_factory`` set to ``None``, such that it behaves like a normal dictionary. """ valuefunc = (lambda x: x) if (valuefunc is None) else valuefunc ret = defaultdict(list) for item in iterable: key = keyfunc(item) value = valuefunc(item) ret[key].append(value) if reducefunc is not None: for key, value_list in ret.items(): ret[key] = reducefunc(value_list) ret.default_factory = None return ret def rlocate(iterable, pred=bool, window_size=None): """Yield the index of each item in *iterable* for which *pred* returns ``True``, starting from the right and moving left. *pred* defaults to :func:`bool`, which will select truthy items: >>> list(rlocate([0, 1, 1, 0, 1, 0, 0])) # Truthy at 1, 2, and 4 [4, 2, 1] Set *pred* to a custom function to, e.g., find the indexes for a particular item: >>> iterable = iter('abcb') >>> pred = lambda x: x == 'b' >>> list(rlocate(iterable, pred)) [3, 1] If *window_size* is given, then the *pred* function will be called with that many items. This enables searching for sub-sequences: >>> iterable = [0, 1, 2, 3, 0, 1, 2, 3, 0, 1, 2, 3] >>> pred = lambda *args: args == (1, 2, 3) >>> list(rlocate(iterable, pred=pred, window_size=3)) [9, 5, 1] Beware, this function won't return anything for infinite iterables. If *iterable* is reversible, ``rlocate`` will reverse it and search from the right. Otherwise, it will search from the left and return the results in reverse order. See :func:`locate` to for other example applications. """ if window_size is None: try: len_iter = len(iterable) return (len_iter - i - 1 for i in locate(reversed(iterable), pred)) except TypeError: pass return reversed(list(locate(iterable, pred, window_size))) def replace(iterable, pred, substitutes, count=None, window_size=1): """Yield the items from *iterable*, replacing the items for which *pred* returns ``True`` with the items from the iterable *substitutes*. >>> iterable = [1, 1, 0, 1, 1, 0, 1, 1] >>> pred = lambda x: x == 0 >>> substitutes = (2, 3) >>> list(replace(iterable, pred, substitutes)) [1, 1, 2, 3, 1, 1, 2, 3, 1, 1] If *count* is given, the number of replacements will be limited: >>> iterable = [1, 1, 0, 1, 1, 0, 1, 1, 0] >>> pred = lambda x: x == 0 >>> substitutes = [None] >>> list(replace(iterable, pred, substitutes, count=2)) [1, 1, None, 1, 1, None, 1, 1, 0] Use *window_size* to control the number of items passed as arguments to *pred*. This allows for locating and replacing subsequences. >>> iterable = [0, 1, 2, 5, 0, 1, 2, 5] >>> window_size = 3 >>> pred = lambda *args: args == (0, 1, 2) # 3 items passed to pred >>> substitutes = [3, 4] # Splice in these items >>> list(replace(iterable, pred, substitutes, window_size=window_size)) [3, 4, 5, 3, 4, 5] """ if window_size < 1: raise ValueError('window_size must be at least 1') # Save the substitutes iterable, since it's used more than once substitutes = tuple(substitutes) # Add padding such that the number of windows matches the length of the # iterable it = chain(iterable, [_marker] * (window_size - 1)) windows = windowed(it, window_size) n = 0 for w in windows: # If the current window matches our predicate (and we haven't hit # our maximum number of replacements), splice in the substitutes # and then consume the following windows that overlap with this one. # For example, if the iterable is (0, 1, 2, 3, 4...) # and the window size is 2, we have (0, 1), (1, 2), (2, 3)... # If the predicate matches on (0, 1), we need to zap (0, 1) and (1, 2) if pred(*w): if (count is None) or (n < count): n += 1 yield from substitutes consume(windows, window_size - 1) continue # If there was no match (or we've reached the replacement limit), # yield the first item from the window. if w and (w[0] is not _marker): yield w[0] def partitions(iterable): """Yield all possible order-preserving partitions of *iterable*. >>> iterable = 'abc' >>> for part in partitions(iterable): ... print([''.join(p) for p in part]) ['abc'] ['a', 'bc'] ['ab', 'c'] ['a', 'b', 'c'] This is unrelated to :func:`partition`. """ sequence = list(iterable) n = len(sequence) for i in powerset(range(1, n)): yield [sequence[i:j] for i, j in zip((0,) + i, i + (n,))] def set_partitions(iterable, k=None): """ Yield the set partitions of *iterable* into *k* parts. Set partitions are not order-preserving. >>> iterable = 'abc' >>> for part in set_partitions(iterable, 2): ... print([''.join(p) for p in part]) ['a', 'bc'] ['ab', 'c'] ['b', 'ac'] If *k* is not given, every set partition is generated. >>> iterable = 'abc' >>> for part in set_partitions(iterable): ... print([''.join(p) for p in part]) ['abc'] ['a', 'bc'] ['ab', 'c'] ['b', 'ac'] ['a', 'b', 'c'] """ L = list(iterable) n = len(L) if k is not None: if k < 1: raise ValueError( "Can't partition in a negative or zero number of groups" ) elif k > n: return def set_partitions_helper(L, k): n = len(L) if k == 1: yield [L] elif n == k: yield [[s] for s in L] else: e, *M = L for p in set_partitions_helper(M, k - 1): yield [[e], *p] for p in set_partitions_helper(M, k): for i in range(len(p)): yield p[:i] + [[e] + p[i]] + p[i + 1 :] if k is None: for k in range(1, n + 1): yield from set_partitions_helper(L, k) else: yield from set_partitions_helper(L, k) class time_limited: """ Yield items from *iterable* until *limit_seconds* have passed. If the time limit expires before all items have been yielded, the ``timed_out`` parameter will be set to ``True``. >>> from time import sleep >>> def generator(): ... yield 1 ... yield 2 ... sleep(0.2) ... yield 3 >>> iterable = time_limited(0.1, generator()) >>> list(iterable) [1, 2] >>> iterable.timed_out True Note that the time is checked before each item is yielded, and iteration stops if the time elapsed is greater than *limit_seconds*. If your time limit is 1 second, but it takes 2 seconds to generate the first item from the iterable, the function will run for 2 seconds and not yield anything. """ def __init__(self, limit_seconds, iterable): if limit_seconds < 0: raise ValueError('limit_seconds must be positive') self.limit_seconds = limit_seconds self._iterable = iter(iterable) self._start_time = monotonic() self.timed_out = False def __iter__(self): return self def __next__(self): item = next(self._iterable) if monotonic() - self._start_time > self.limit_seconds: self.timed_out = True raise StopIteration return item def only(iterable, default=None, too_long=None): """If *iterable* has only one item, return it. If it has zero items, return *default*. If it has more than one item, raise the exception given by *too_long*, which is ``ValueError`` by default. >>> only([], default='missing') 'missing' >>> only([1]) 1 >>> only([1, 2]) # doctest: +IGNORE_EXCEPTION_DETAIL Traceback (most recent call last): ... ValueError: Expected exactly one item in iterable, but got 1, 2, and perhaps more.' >>> only([1, 2], too_long=TypeError) # doctest: +IGNORE_EXCEPTION_DETAIL Traceback (most recent call last): ... TypeError Note that :func:`only` attempts to advance *iterable* twice to ensure there is only one item. See :func:`spy` or :func:`peekable` to check iterable contents less destructively. """ it = iter(iterable) first_value = next(it, default) try: second_value = next(it) except StopIteration: pass else: msg = ( 'Expected exactly one item in iterable, but got {!r}, {!r}, ' 'and perhaps more.'.format(first_value, second_value) ) raise too_long or ValueError(msg) return first_value def ichunked(iterable, n): """Break *iterable* into sub-iterables with *n* elements each. :func:`ichunked` is like :func:`chunked`, but it yields iterables instead of lists. If the sub-iterables are read in order, the elements of *iterable* won't be stored in memory. If they are read out of order, :func:`itertools.tee` is used to cache elements as necessary. >>> from itertools import count >>> all_chunks = ichunked(count(), 4) >>> c_1, c_2, c_3 = next(all_chunks), next(all_chunks), next(all_chunks) >>> list(c_2) # c_1's elements have been cached; c_3's haven't been [4, 5, 6, 7] >>> list(c_1) [0, 1, 2, 3] >>> list(c_3) [8, 9, 10, 11] """ source = iter(iterable) while True: # Check to see whether we're at the end of the source iterable item = next(source, _marker) if item is _marker: return # Clone the source and yield an n-length slice source, it = tee(chain([item], source)) yield islice(it, n) # Advance the source iterable consume(source, n) def distinct_combinations(iterable, r): """Yield the distinct combinations of *r* items taken from *iterable*. >>> list(distinct_combinations([0, 0, 1], 2)) [(0, 0), (0, 1)] Equivalent to ``set(combinations(iterable))``, except duplicates are not generated and thrown away. For larger input sequences this is much more efficient. """ if r < 0: raise ValueError('r must be non-negative') elif r == 0: yield () return pool = tuple(iterable) generators = [unique_everseen(enumerate(pool), key=itemgetter(1))] current_combo = [None] * r level = 0 while generators: try: cur_idx, p = next(generators[-1]) except StopIteration: generators.pop() level -= 1 continue current_combo[level] = p if level + 1 == r: yield tuple(current_combo) else: generators.append( unique_everseen( enumerate(pool[cur_idx + 1 :], cur_idx + 1), key=itemgetter(1), ) ) level += 1 def filter_except(validator, iterable, *exceptions): """Yield the items from *iterable* for which the *validator* function does not raise one of the specified *exceptions*. *validator* is called for each item in *iterable*. It should be a function that accepts one argument and raises an exception if that item is not valid. >>> iterable = ['1', '2', 'three', '4', None] >>> list(filter_except(int, iterable, ValueError, TypeError)) ['1', '2', '4'] If an exception other than one given by *exceptions* is raised by *validator*, it is raised like normal. """ for item in iterable: try: validator(item) except exceptions: pass else: yield item def map_except(function, iterable, *exceptions): """Transform each item from *iterable* with *function* and yield the result, unless *function* raises one of the specified *exceptions*. *function* is called to transform each item in *iterable*. It should accept one argument. >>> iterable = ['1', '2', 'three', '4', None] >>> list(map_except(int, iterable, ValueError, TypeError)) [1, 2, 4] If an exception other than one given by *exceptions* is raised by *function*, it is raised like normal. """ for item in iterable: try: yield function(item) except exceptions: pass def map_if(iterable, pred, func, func_else=lambda x: x): """Evaluate each item from *iterable* using *pred*. If the result is equivalent to ``True``, transform the item with *func* and yield it. Otherwise, transform the item with *func_else* and yield it. *pred*, *func*, and *func_else* should each be functions that accept one argument. By default, *func_else* is the identity function. >>> from math import sqrt >>> iterable = list(range(-5, 5)) >>> iterable [-5, -4, -3, -2, -1, 0, 1, 2, 3, 4] >>> list(map_if(iterable, lambda x: x > 3, lambda x: 'toobig')) [-5, -4, -3, -2, -1, 0, 1, 2, 3, 'toobig'] >>> list(map_if(iterable, lambda x: x >= 0, ... lambda x: f'{sqrt(x):.2f}', lambda x: None)) [None, None, None, None, None, '0.00', '1.00', '1.41', '1.73', '2.00'] """ for item in iterable: yield func(item) if pred(item) else func_else(item) def _sample_unweighted(iterable, k): # Implementation of "Algorithm L" from the 1994 paper by Kim-Hung Li: # "Reservoir-Sampling Algorithms of Time Complexity O(n(1+log(N/n)))". # Fill up the reservoir (collection of samples) with the first `k` samples reservoir = take(k, iterable) # Generate random number that's the largest in a sample of k U(0,1) numbers # Largest order statistic: https://en.wikipedia.org/wiki/Order_statistic W = exp(log(random()) / k) # The number of elements to skip before changing the reservoir is a random # number with a geometric distribution. Sample it using random() and logs. next_index = k + floor(log(random()) / log(1 - W)) for index, element in enumerate(iterable, k): if index == next_index: reservoir[randrange(k)] = element # The new W is the largest in a sample of k U(0, `old_W`) numbers W *= exp(log(random()) / k) next_index += floor(log(random()) / log(1 - W)) + 1 return reservoir def _sample_weighted(iterable, k, weights): # Implementation of "A-ExpJ" from the 2006 paper by Efraimidis et al. : # "Weighted random sampling with a reservoir". # Log-transform for numerical stability for weights that are small/large weight_keys = (log(random()) / weight for weight in weights) # Fill up the reservoir (collection of samples) with the first `k` # weight-keys and elements, then heapify the list. reservoir = take(k, zip(weight_keys, iterable)) heapify(reservoir) # The number of jumps before changing the reservoir is a random variable # with an exponential distribution. Sample it using random() and logs. smallest_weight_key, _ = reservoir[0] weights_to_skip = log(random()) / smallest_weight_key for weight, element in zip(weights, iterable): if weight >= weights_to_skip: # The notation here is consistent with the paper, but we store # the weight-keys in log-space for better numerical stability. smallest_weight_key, _ = reservoir[0] t_w = exp(weight * smallest_weight_key) r_2 = uniform(t_w, 1) # generate U(t_w, 1) weight_key = log(r_2) / weight heapreplace(reservoir, (weight_key, element)) smallest_weight_key, _ = reservoir[0] weights_to_skip = log(random()) / smallest_weight_key else: weights_to_skip -= weight # Equivalent to [element for weight_key, element in sorted(reservoir)] return [heappop(reservoir)[1] for _ in range(k)] def sample(iterable, k, weights=None): """Return a *k*-length list of elements chosen (without replacement) from the *iterable*. Like :func:`random.sample`, but works on iterables of unknown length. >>> iterable = range(100) >>> sample(iterable, 5) # doctest: +SKIP [81, 60, 96, 16, 4] An iterable with *weights* may also be given: >>> iterable = range(100) >>> weights = (i * i + 1 for i in range(100)) >>> sampled = sample(iterable, 5, weights=weights) # doctest: +SKIP [79, 67, 74, 66, 78] The algorithm can also be used to generate weighted random permutations. The relative weight of each item determines the probability that it appears late in the permutation. >>> data = "abcdefgh" >>> weights = range(1, len(data) + 1) >>> sample(data, k=len(data), weights=weights) # doctest: +SKIP ['c', 'a', 'b', 'e', 'g', 'd', 'h', 'f'] """ if k == 0: return [] iterable = iter(iterable) if weights is None: return _sample_unweighted(iterable, k) else: weights = iter(weights) return _sample_weighted(iterable, k, weights) def is_sorted(iterable, key=None, reverse=False): """Returns ``True`` if the items of iterable are in sorted order, and ``False`` otherwise. *key* and *reverse* have the same meaning that they do in the built-in :func:`sorted` function. >>> is_sorted(['1', '2', '3', '4', '5'], key=int) True >>> is_sorted([5, 4, 3, 1, 2], reverse=True) False The function returns ``False`` after encountering the first out-of-order item. If there are no out-of-order items, the iterable is exhausted. """ compare = lt if reverse else gt it = iterable if (key is None) else map(key, iterable) return not any(starmap(compare, pairwise(it))) class AbortThread(BaseException): pass class callback_iter: """Convert a function that uses callbacks to an iterator. Let *func* be a function that takes a `callback` keyword argument. For example: >>> def func(callback=None): ... for i, c in [(1, 'a'), (2, 'b'), (3, 'c')]: ... if callback: ... callback(i, c) ... return 4 Use ``with callback_iter(func)`` to get an iterator over the parameters that are delivered to the callback. >>> with callback_iter(func) as it: ... for args, kwargs in it: ... print(args) (1, 'a') (2, 'b') (3, 'c') The function will be called in a background thread. The ``done`` property indicates whether it has completed execution. >>> it.done True If it completes successfully, its return value will be available in the ``result`` property. >>> it.result 4 Notes: * If the function uses some keyword argument besides ``callback``, supply *callback_kwd*. * If it finished executing, but raised an exception, accessing the ``result`` property will raise the same exception. * If it hasn't finished executing, accessing the ``result`` property from within the ``with`` block will raise ``RuntimeError``. * If it hasn't finished executing, accessing the ``result`` property from outside the ``with`` block will raise a ``more_itertools.AbortThread`` exception. * Provide *wait_seconds* to adjust how frequently the it is polled for output. """ def __init__(self, func, callback_kwd='callback', wait_seconds=0.1): self._func = func self._callback_kwd = callback_kwd self._aborted = False self._future = None self._wait_seconds = wait_seconds self._executor = ThreadPoolExecutor(max_workers=1) self._iterator = self._reader() def __enter__(self): return self def __exit__(self, exc_type, exc_value, traceback): self._aborted = True self._executor.shutdown() def __iter__(self): return self def __next__(self): return next(self._iterator) @property def done(self): if self._future is None: return False return self._future.done() @property def result(self): if not self.done: raise RuntimeError('Function has not yet completed') return self._future.result() def _reader(self): q = Queue() def callback(*args, **kwargs): if self._aborted: raise AbortThread('canceled by user') q.put((args, kwargs)) self._future = self._executor.submit( self._func, **{self._callback_kwd: callback} ) while True: try: item = q.get(timeout=self._wait_seconds) except Empty: pass else: q.task_done() yield item if self._future.done(): break remaining = [] while True: try: item = q.get_nowait() except Empty: break else: q.task_done() remaining.append(item) q.join() yield from remaining def windowed_complete(iterable, n): """ Yield ``(beginning, middle, end)`` tuples, where: * Each ``middle`` has *n* items from *iterable* * Each ``beginning`` has the items before the ones in ``middle`` * Each ``end`` has the items after the ones in ``middle`` >>> iterable = range(7) >>> n = 3 >>> for beginning, middle, end in windowed_complete(iterable, n): ... print(beginning, middle, end) () (0, 1, 2) (3, 4, 5, 6) (0,) (1, 2, 3) (4, 5, 6) (0, 1) (2, 3, 4) (5, 6) (0, 1, 2) (3, 4, 5) (6,) (0, 1, 2, 3) (4, 5, 6) () Note that *n* must be at least 0 and most equal to the length of *iterable*. This function will exhaust the iterable and may require significant storage. """ if n < 0: raise ValueError('n must be >= 0') seq = tuple(iterable) size = len(seq) if n > size: raise ValueError('n must be <= len(seq)') for i in range(size - n + 1): beginning = seq[:i] middle = seq[i : i + n] end = seq[i + n :] yield beginning, middle, end def all_unique(iterable, key=None): """ Returns ``True`` if all the elements of *iterable* are unique (no two elements are equal). >>> all_unique('ABCB') False If a *key* function is specified, it will be used to make comparisons. >>> all_unique('ABCb') True >>> all_unique('ABCb', str.lower) False The function returns as soon as the first non-unique element is encountered. Iterables with a mix of hashable and unhashable items can be used, but the function will be slower for unhashable items. """ seenset = set() seenset_add = seenset.add seenlist = [] seenlist_add = seenlist.append for element in map(key, iterable) if key else iterable: try: if element in seenset: return False seenset_add(element) except TypeError: if element in seenlist: return False seenlist_add(element) return True def nth_product(index, *args): """Equivalent to ``list(product(*args))[index]``. The products of *args* can be ordered lexicographically. :func:`nth_product` computes the product at sort position *index* without computing the previous products. >>> nth_product(8, range(2), range(2), range(2), range(2)) (1, 0, 0, 0) ``IndexError`` will be raised if the given *index* is invalid. """ pools = list(map(tuple, reversed(args))) ns = list(map(len, pools)) c = reduce(mul, ns) if index < 0: index += c if not 0 <= index < c: raise IndexError result = [] for pool, n in zip(pools, ns): result.append(pool[index % n]) index //= n return tuple(reversed(result)) def nth_permutation(iterable, r, index): """Equivalent to ``list(permutations(iterable, r))[index]``` The subsequences of *iterable* that are of length *r* where order is important can be ordered lexicographically. :func:`nth_permutation` computes the subsequence at sort position *index* directly, without computing the previous subsequences. >>> nth_permutation('ghijk', 2, 5) ('h', 'i') ``ValueError`` will be raised If *r* is negative or greater than the length of *iterable*. ``IndexError`` will be raised if the given *index* is invalid. """ pool = list(iterable) n = len(pool) if r is None or r == n: r, c = n, factorial(n) elif not 0 <= r < n: raise ValueError else: c = factorial(n) // factorial(n - r) if index < 0: index += c if not 0 <= index < c: raise IndexError if c == 0: return tuple() result = [0] * r q = index * factorial(n) // c if r < n else index for d in range(1, n + 1): q, i = divmod(q, d) if 0 <= n - d < r: result[n - d] = i if q == 0: break return tuple(map(pool.pop, result)) def value_chain(*args): """Yield all arguments passed to the function in the same order in which they were passed. If an argument itself is iterable then iterate over its values. >>> list(value_chain(1, 2, 3, [4, 5, 6])) [1, 2, 3, 4, 5, 6] Binary and text strings are not considered iterable and are emitted as-is: >>> list(value_chain('12', '34', ['56', '78'])) ['12', '34', '56', '78'] Multiple levels of nesting are not flattened. """ for value in args: if isinstance(value, (str, bytes)): yield value continue try: yield from value except TypeError: yield value def product_index(element, *args): """Equivalent to ``list(product(*args)).index(element)`` The products of *args* can be ordered lexicographically. :func:`product_index` computes the first index of *element* without computing the previous products. >>> product_index([8, 2], range(10), range(5)) 42 ``ValueError`` will be raised if the given *element* isn't in the product of *args*. """ index = 0 for x, pool in zip_longest(element, args, fillvalue=_marker): if x is _marker or pool is _marker: raise ValueError('element is not a product of args') pool = tuple(pool) index = index * len(pool) + pool.index(x) return index def combination_index(element, iterable): """Equivalent to ``list(combinations(iterable, r)).index(element)`` The subsequences of *iterable* that are of length *r* can be ordered lexicographically. :func:`combination_index` computes the index of the first *element*, without computing the previous combinations. >>> combination_index('adf', 'abcdefg') 10 ``ValueError`` will be raised if the given *element* isn't one of the combinations of *iterable*. """ element = enumerate(element) k, y = next(element, (None, None)) if k is None: return 0 indexes = [] pool = enumerate(iterable) for n, x in pool: if x == y: indexes.append(n) tmp, y = next(element, (None, None)) if tmp is None: break else: k = tmp else: raise ValueError('element is not a combination of iterable') n, _ = last(pool, default=(n, None)) # Python versiosn below 3.8 don't have math.comb index = 1 for i, j in enumerate(reversed(indexes), start=1): j = n - j if i <= j: index += factorial(j) // (factorial(i) * factorial(j - i)) return factorial(n + 1) // (factorial(k + 1) * factorial(n - k)) - index def permutation_index(element, iterable): """Equivalent to ``list(permutations(iterable, r)).index(element)``` The subsequences of *iterable* that are of length *r* where order is important can be ordered lexicographically. :func:`permutation_index` computes the index of the first *element* directly, without computing the previous permutations. >>> permutation_index([1, 3, 2], range(5)) 19 ``ValueError`` will be raised if the given *element* isn't one of the permutations of *iterable*. """ index = 0 pool = list(iterable) for i, x in zip(range(len(pool), -1, -1), element): r = pool.index(x) index = index * i + r del pool[r] return index class countable: """Wrap *iterable* and keep a count of how many items have been consumed. The ``items_seen`` attribute starts at ``0`` and increments as the iterable is consumed: >>> iterable = map(str, range(10)) >>> it = countable(iterable) >>> it.items_seen 0 >>> next(it), next(it) ('0', '1') >>> list(it) ['2', '3', '4', '5', '6', '7', '8', '9'] >>> it.items_seen 10 """ def __init__(self, iterable): self._it = iter(iterable) self.items_seen = 0 def __iter__(self): return self def __next__(self): item = next(self._it) self.items_seen += 1 return item def chunked_even(iterable, n): """Break *iterable* into lists of approximately length *n*. Items are distributed such the lengths of the lists differ by at most 1 item. >>> iterable = [1, 2, 3, 4, 5, 6, 7] >>> n = 3 >>> list(chunked_even(iterable, n)) # List lengths: 3, 2, 2 [[1, 2, 3], [4, 5], [6, 7]] >>> list(chunked(iterable, n)) # List lengths: 3, 3, 1 [[1, 2, 3], [4, 5, 6], [7]] """ len_method = getattr(iterable, '__len__', None) if len_method is None: return _chunked_even_online(iterable, n) else: return _chunked_even_finite(iterable, len_method(), n) def _chunked_even_online(iterable, n): buffer = [] maxbuf = n + (n - 2) * (n - 1) for x in iterable: buffer.append(x) if len(buffer) == maxbuf: yield buffer[:n] buffer = buffer[n:] yield from _chunked_even_finite(buffer, len(buffer), n) def _chunked_even_finite(iterable, N, n): if N < 1: return # Lists are either size `full_size <= n` or `partial_size = full_size - 1` q, r = divmod(N, n) num_lists = q + (1 if r > 0 else 0) q, r = divmod(N, num_lists) full_size = q + (1 if r > 0 else 0) partial_size = full_size - 1 num_full = N - partial_size * num_lists num_partial = num_lists - num_full buffer = [] iterator = iter(iterable) # Yield num_full lists of full_size for x in iterator: buffer.append(x) if len(buffer) == full_size: yield buffer buffer = [] num_full -= 1 if num_full <= 0: break # Yield num_partial lists of partial_size for x in iterator: buffer.append(x) if len(buffer) == partial_size: yield buffer buffer = [] num_partial -= 1 def zip_broadcast(*objects, scalar_types=(str, bytes), strict=False): """A version of :func:`zip` that "broadcasts" any scalar (i.e., non-iterable) items into output tuples. >>> iterable_1 = [1, 2, 3] >>> iterable_2 = ['a', 'b', 'c'] >>> scalar = '_' >>> list(zip_broadcast(iterable_1, iterable_2, scalar)) [(1, 'a', '_'), (2, 'b', '_'), (3, 'c', '_')] The *scalar_types* keyword argument determines what types are considered scalar. It is set to ``(str, bytes)`` by default. Set it to ``None`` to treat strings and byte strings as iterable: >>> list(zip_broadcast('abc', 0, 'xyz', scalar_types=None)) [('a', 0, 'x'), ('b', 0, 'y'), ('c', 0, 'z')] If the *strict* keyword argument is ``True``, then ``UnequalIterablesError`` will be raised if any of the iterables have different lengths. """ if not objects: return iterables = [] all_scalar = True for obj in objects: # If the object is one of our scalar types, turn it into an iterable # by wrapping it with itertools.repeat if scalar_types and isinstance(obj, scalar_types): iterables.append((repeat(obj), False)) # Otherwise, test to see whether the object is iterable. # If it is, collect it. If it's not, treat it as a scalar. else: try: iterables.append((iter(obj), True)) except TypeError: iterables.append((repeat(obj), False)) else: all_scalar = False # If all the objects were scalar, we just emit them as a tuple. # Otherwise we zip the collected iterable objects. if all_scalar: yield tuple(objects) else: yield from zip(*(it for it, is_it in iterables)) # For strict mode, we ensure that all the iterable objects have been # exhausted. if strict: for it, is_it in filter(itemgetter(1), iterables): if next(it, _marker) is not _marker: raise UnequalIterablesError ././@PaxHeader0000000000000000000000000000002600000000000011453 xustar000000000000000022 mtime=1630669869.0 more-itertools-8.10.0/more_itertools/more.pyi0000664000175000017500000004115500000000000020352 0ustar00bobo00000000000000"""Stubs for more_itertools.more""" from typing import ( Any, Callable, Container, Dict, Generic, Hashable, Iterable, Iterator, List, Optional, Reversible, Sequence, Sized, Tuple, Union, TypeVar, type_check_only, ) from types import TracebackType from typing_extensions import ContextManager, Protocol, Type, overload # Type and type variable definitions _T = TypeVar('_T') _T1 = TypeVar('_T1') _T2 = TypeVar('_T2') _U = TypeVar('_U') _V = TypeVar('_V') _W = TypeVar('_W') _T_co = TypeVar('_T_co', covariant=True) _GenFn = TypeVar('_GenFn', bound=Callable[..., Iterator[object]]) _Raisable = Union[BaseException, 'Type[BaseException]'] @type_check_only class _SizedIterable(Protocol[_T_co], Sized, Iterable[_T_co]): ... @type_check_only class _SizedReversible(Protocol[_T_co], Sized, Reversible[_T_co]): ... def chunked( iterable: Iterable[_T], n: Optional[int], strict: bool = ... ) -> Iterator[List[_T]]: ... @overload def first(iterable: Iterable[_T]) -> _T: ... @overload def first(iterable: Iterable[_T], default: _U) -> Union[_T, _U]: ... @overload def last(iterable: Iterable[_T]) -> _T: ... @overload def last(iterable: Iterable[_T], default: _U) -> Union[_T, _U]: ... @overload def nth_or_last(iterable: Iterable[_T], n: int) -> _T: ... @overload def nth_or_last( iterable: Iterable[_T], n: int, default: _U ) -> Union[_T, _U]: ... class peekable(Generic[_T], Iterator[_T]): def __init__(self, iterable: Iterable[_T]) -> None: ... def __iter__(self) -> peekable[_T]: ... def __bool__(self) -> bool: ... @overload def peek(self) -> _T: ... @overload def peek(self, default: _U) -> Union[_T, _U]: ... def prepend(self, *items: _T) -> None: ... def __next__(self) -> _T: ... @overload def __getitem__(self, index: int) -> _T: ... @overload def __getitem__(self, index: slice) -> List[_T]: ... def collate(*iterables: Iterable[_T], **kwargs: Any) -> Iterable[_T]: ... def consumer(func: _GenFn) -> _GenFn: ... def ilen(iterable: Iterable[object]) -> int: ... def iterate(func: Callable[[_T], _T], start: _T) -> Iterator[_T]: ... def with_iter( context_manager: ContextManager[Iterable[_T]], ) -> Iterator[_T]: ... def one( iterable: Iterable[_T], too_short: Optional[_Raisable] = ..., too_long: Optional[_Raisable] = ..., ) -> _T: ... def distinct_permutations( iterable: Iterable[_T], r: Optional[int] = ... ) -> Iterator[Tuple[_T, ...]]: ... def intersperse( e: _U, iterable: Iterable[_T], n: int = ... ) -> Iterator[Union[_T, _U]]: ... def unique_to_each(*iterables: Iterable[_T]) -> List[List[_T]]: ... @overload def windowed( seq: Iterable[_T], n: int, *, step: int = ... ) -> Iterator[Tuple[Optional[_T], ...]]: ... @overload def windowed( seq: Iterable[_T], n: int, fillvalue: _U, step: int = ... ) -> Iterator[Tuple[Union[_T, _U], ...]]: ... def substrings(iterable: Iterable[_T]) -> Iterator[Tuple[_T, ...]]: ... def substrings_indexes( seq: Sequence[_T], reverse: bool = ... ) -> Iterator[Tuple[Sequence[_T], int, int]]: ... class bucket(Generic[_T, _U], Container[_U]): def __init__( self, iterable: Iterable[_T], key: Callable[[_T], _U], validator: Optional[Callable[[object], object]] = ..., ) -> None: ... def __contains__(self, value: object) -> bool: ... def __iter__(self) -> Iterator[_U]: ... def __getitem__(self, value: object) -> Iterator[_T]: ... def spy( iterable: Iterable[_T], n: int = ... ) -> Tuple[List[_T], Iterator[_T]]: ... def interleave(*iterables: Iterable[_T]) -> Iterator[_T]: ... def interleave_longest(*iterables: Iterable[_T]) -> Iterator[_T]: ... def interleave_evenly( iterables: List[Iterable[_T]], lengths: Optional[List[int]] = ... ) -> Iterator[_T]: ... def collapse( iterable: Iterable[Any], base_type: Optional[type] = ..., levels: Optional[int] = ..., ) -> Iterator[Any]: ... @overload def side_effect( func: Callable[[_T], object], iterable: Iterable[_T], chunk_size: None = ..., before: Optional[Callable[[], object]] = ..., after: Optional[Callable[[], object]] = ..., ) -> Iterator[_T]: ... @overload def side_effect( func: Callable[[List[_T]], object], iterable: Iterable[_T], chunk_size: int, before: Optional[Callable[[], object]] = ..., after: Optional[Callable[[], object]] = ..., ) -> Iterator[_T]: ... def sliced( seq: Sequence[_T], n: int, strict: bool = ... ) -> Iterator[Sequence[_T]]: ... def split_at( iterable: Iterable[_T], pred: Callable[[_T], object], maxsplit: int = ..., keep_separator: bool = ..., ) -> Iterator[List[_T]]: ... def split_before( iterable: Iterable[_T], pred: Callable[[_T], object], maxsplit: int = ... ) -> Iterator[List[_T]]: ... def split_after( iterable: Iterable[_T], pred: Callable[[_T], object], maxsplit: int = ... ) -> Iterator[List[_T]]: ... def split_when( iterable: Iterable[_T], pred: Callable[[_T, _T], object], maxsplit: int = ..., ) -> Iterator[List[_T]]: ... def split_into( iterable: Iterable[_T], sizes: Iterable[Optional[int]] ) -> Iterator[List[_T]]: ... @overload def padded( iterable: Iterable[_T], *, n: Optional[int] = ..., next_multiple: bool = ... ) -> Iterator[Optional[_T]]: ... @overload def padded( iterable: Iterable[_T], fillvalue: _U, n: Optional[int] = ..., next_multiple: bool = ..., ) -> Iterator[Union[_T, _U]]: ... @overload def repeat_last(iterable: Iterable[_T]) -> Iterator[_T]: ... @overload def repeat_last( iterable: Iterable[_T], default: _U ) -> Iterator[Union[_T, _U]]: ... def distribute(n: int, iterable: Iterable[_T]) -> List[Iterator[_T]]: ... @overload def stagger( iterable: Iterable[_T], offsets: _SizedIterable[int] = ..., longest: bool = ..., ) -> Iterator[Tuple[Optional[_T], ...]]: ... @overload def stagger( iterable: Iterable[_T], offsets: _SizedIterable[int] = ..., longest: bool = ..., fillvalue: _U = ..., ) -> Iterator[Tuple[Union[_T, _U], ...]]: ... class UnequalIterablesError(ValueError): def __init__( self, details: Optional[Tuple[int, int, int]] = ... ) -> None: ... @overload def zip_equal(__iter1: Iterable[_T1]) -> Iterator[Tuple[_T1]]: ... @overload def zip_equal( __iter1: Iterable[_T1], __iter2: Iterable[_T2] ) -> Iterator[Tuple[_T1, _T2]]: ... @overload def zip_equal( __iter1: Iterable[_T], __iter2: Iterable[_T], __iter3: Iterable[_T], *iterables: Iterable[_T] ) -> Iterator[Tuple[_T, ...]]: ... @overload def zip_offset( __iter1: Iterable[_T1], *, offsets: _SizedIterable[int], longest: bool = ..., fillvalue: None = None ) -> Iterator[Tuple[Optional[_T1]]]: ... @overload def zip_offset( __iter1: Iterable[_T1], __iter2: Iterable[_T2], *, offsets: _SizedIterable[int], longest: bool = ..., fillvalue: None = None ) -> Iterator[Tuple[Optional[_T1], Optional[_T2]]]: ... @overload def zip_offset( __iter1: Iterable[_T], __iter2: Iterable[_T], __iter3: Iterable[_T], *iterables: Iterable[_T], offsets: _SizedIterable[int], longest: bool = ..., fillvalue: None = None ) -> Iterator[Tuple[Optional[_T], ...]]: ... @overload def zip_offset( __iter1: Iterable[_T1], *, offsets: _SizedIterable[int], longest: bool = ..., fillvalue: _U, ) -> Iterator[Tuple[Union[_T1, _U]]]: ... @overload def zip_offset( __iter1: Iterable[_T1], __iter2: Iterable[_T2], *, offsets: _SizedIterable[int], longest: bool = ..., fillvalue: _U, ) -> Iterator[Tuple[Union[_T1, _U], Union[_T2, _U]]]: ... @overload def zip_offset( __iter1: Iterable[_T], __iter2: Iterable[_T], __iter3: Iterable[_T], *iterables: Iterable[_T], offsets: _SizedIterable[int], longest: bool = ..., fillvalue: _U, ) -> Iterator[Tuple[Union[_T, _U], ...]]: ... def sort_together( iterables: Iterable[Iterable[_T]], key_list: Iterable[int] = ..., key: Optional[Callable[..., Any]] = ..., reverse: bool = ..., ) -> List[Tuple[_T, ...]]: ... def unzip(iterable: Iterable[Sequence[_T]]) -> Tuple[Iterator[_T], ...]: ... def divide(n: int, iterable: Iterable[_T]) -> List[Iterator[_T]]: ... def always_iterable( obj: object, base_type: Union[ type, Tuple[Union[type, Tuple[Any, ...]], ...], None ] = ..., ) -> Iterator[Any]: ... def adjacent( predicate: Callable[[_T], bool], iterable: Iterable[_T], distance: int = ..., ) -> Iterator[Tuple[bool, _T]]: ... def groupby_transform( iterable: Iterable[_T], keyfunc: Optional[Callable[[_T], _U]] = ..., valuefunc: Optional[Callable[[_T], _V]] = ..., reducefunc: Optional[Callable[..., _W]] = ..., ) -> Iterator[Tuple[_T, _W]]: ... class numeric_range(Generic[_T, _U], Sequence[_T], Hashable, Reversible[_T]): @overload def __init__(self, __stop: _T) -> None: ... @overload def __init__(self, __start: _T, __stop: _T) -> None: ... @overload def __init__(self, __start: _T, __stop: _T, __step: _U) -> None: ... def __bool__(self) -> bool: ... def __contains__(self, elem: object) -> bool: ... def __eq__(self, other: object) -> bool: ... @overload def __getitem__(self, key: int) -> _T: ... @overload def __getitem__(self, key: slice) -> numeric_range[_T, _U]: ... def __hash__(self) -> int: ... def __iter__(self) -> Iterator[_T]: ... def __len__(self) -> int: ... def __reduce__( self, ) -> Tuple[Type[numeric_range[_T, _U]], Tuple[_T, _T, _U]]: ... def __repr__(self) -> str: ... def __reversed__(self) -> Iterator[_T]: ... def count(self, value: _T) -> int: ... def index(self, value: _T) -> int: ... # type: ignore def count_cycle( iterable: Iterable[_T], n: Optional[int] = ... ) -> Iterable[Tuple[int, _T]]: ... def mark_ends( iterable: Iterable[_T], ) -> Iterable[Tuple[bool, bool, _T]]: ... def locate( iterable: Iterable[object], pred: Callable[..., Any] = ..., window_size: Optional[int] = ..., ) -> Iterator[int]: ... def lstrip( iterable: Iterable[_T], pred: Callable[[_T], object] ) -> Iterator[_T]: ... def rstrip( iterable: Iterable[_T], pred: Callable[[_T], object] ) -> Iterator[_T]: ... def strip( iterable: Iterable[_T], pred: Callable[[_T], object] ) -> Iterator[_T]: ... class islice_extended(Generic[_T], Iterator[_T]): def __init__( self, iterable: Iterable[_T], *args: Optional[int] ) -> None: ... def __iter__(self) -> islice_extended[_T]: ... def __next__(self) -> _T: ... def __getitem__(self, index: slice) -> islice_extended[_T]: ... def always_reversible(iterable: Iterable[_T]) -> Iterator[_T]: ... def consecutive_groups( iterable: Iterable[_T], ordering: Callable[[_T], int] = ... ) -> Iterator[Iterator[_T]]: ... @overload def difference( iterable: Iterable[_T], func: Callable[[_T, _T], _U] = ..., *, initial: None = ... ) -> Iterator[Union[_T, _U]]: ... @overload def difference( iterable: Iterable[_T], func: Callable[[_T, _T], _U] = ..., *, initial: _U ) -> Iterator[_U]: ... class SequenceView(Generic[_T], Sequence[_T]): def __init__(self, target: Sequence[_T]) -> None: ... @overload def __getitem__(self, index: int) -> _T: ... @overload def __getitem__(self, index: slice) -> Sequence[_T]: ... def __len__(self) -> int: ... class seekable(Generic[_T], Iterator[_T]): def __init__( self, iterable: Iterable[_T], maxlen: Optional[int] = ... ) -> None: ... def __iter__(self) -> seekable[_T]: ... def __next__(self) -> _T: ... def __bool__(self) -> bool: ... @overload def peek(self) -> _T: ... @overload def peek(self, default: _U) -> Union[_T, _U]: ... def elements(self) -> SequenceView[_T]: ... def seek(self, index: int) -> None: ... class run_length: @staticmethod def encode(iterable: Iterable[_T]) -> Iterator[Tuple[_T, int]]: ... @staticmethod def decode(iterable: Iterable[Tuple[_T, int]]) -> Iterator[_T]: ... def exactly_n( iterable: Iterable[_T], n: int, predicate: Callable[[_T], object] = ... ) -> bool: ... def circular_shifts(iterable: Iterable[_T]) -> List[Tuple[_T, ...]]: ... def make_decorator( wrapping_func: Callable[..., _U], result_index: int = ... ) -> Callable[..., Callable[[Callable[..., Any]], Callable[..., _U]]]: ... @overload def map_reduce( iterable: Iterable[_T], keyfunc: Callable[[_T], _U], valuefunc: None = ..., reducefunc: None = ..., ) -> Dict[_U, List[_T]]: ... @overload def map_reduce( iterable: Iterable[_T], keyfunc: Callable[[_T], _U], valuefunc: Callable[[_T], _V], reducefunc: None = ..., ) -> Dict[_U, List[_V]]: ... @overload def map_reduce( iterable: Iterable[_T], keyfunc: Callable[[_T], _U], valuefunc: None = ..., reducefunc: Callable[[List[_T]], _W] = ..., ) -> Dict[_U, _W]: ... @overload def map_reduce( iterable: Iterable[_T], keyfunc: Callable[[_T], _U], valuefunc: Callable[[_T], _V], reducefunc: Callable[[List[_V]], _W], ) -> Dict[_U, _W]: ... def rlocate( iterable: Iterable[_T], pred: Callable[..., object] = ..., window_size: Optional[int] = ..., ) -> Iterator[int]: ... def replace( iterable: Iterable[_T], pred: Callable[..., object], substitutes: Iterable[_U], count: Optional[int] = ..., window_size: int = ..., ) -> Iterator[Union[_T, _U]]: ... def partitions(iterable: Iterable[_T]) -> Iterator[List[List[_T]]]: ... def set_partitions( iterable: Iterable[_T], k: Optional[int] = ... ) -> Iterator[List[List[_T]]]: ... class time_limited(Generic[_T], Iterator[_T]): def __init__( self, limit_seconds: float, iterable: Iterable[_T] ) -> None: ... def __iter__(self) -> islice_extended[_T]: ... def __next__(self) -> _T: ... @overload def only( iterable: Iterable[_T], *, too_long: Optional[_Raisable] = ... ) -> Optional[_T]: ... @overload def only( iterable: Iterable[_T], default: _U, too_long: Optional[_Raisable] = ... ) -> Union[_T, _U]: ... def ichunked(iterable: Iterable[_T], n: int) -> Iterator[Iterator[_T]]: ... def distinct_combinations( iterable: Iterable[_T], r: int ) -> Iterator[Tuple[_T, ...]]: ... def filter_except( validator: Callable[[Any], object], iterable: Iterable[_T], *exceptions: Type[BaseException] ) -> Iterator[_T]: ... def map_except( function: Callable[[Any], _U], iterable: Iterable[_T], *exceptions: Type[BaseException] ) -> Iterator[_U]: ... def map_if( iterable: Iterable[Any], pred: Callable[[Any], bool], func: Callable[[Any], Any], func_else: Optional[Callable[[Any], Any]] = ..., ) -> Iterator[Any]: ... def sample( iterable: Iterable[_T], k: int, weights: Optional[Iterable[float]] = ..., ) -> List[_T]: ... def is_sorted( iterable: Iterable[_T], key: Optional[Callable[[_T], _U]] = ..., reverse: bool = False, ) -> bool: ... class AbortThread(BaseException): pass class callback_iter(Generic[_T], Iterator[_T]): def __init__( self, func: Callable[..., Any], callback_kwd: str = ..., wait_seconds: float = ..., ) -> None: ... def __enter__(self) -> callback_iter[_T]: ... def __exit__( self, exc_type: Optional[Type[BaseException]], exc_value: Optional[BaseException], traceback: Optional[TracebackType], ) -> Optional[bool]: ... def __iter__(self) -> callback_iter[_T]: ... def __next__(self) -> _T: ... def _reader(self) -> Iterator[_T]: ... @property def done(self) -> bool: ... @property def result(self) -> Any: ... def windowed_complete( iterable: Iterable[_T], n: int ) -> Iterator[Tuple[_T, ...]]: ... def all_unique( iterable: Iterable[_T], key: Optional[Callable[[_T], _U]] = ... ) -> bool: ... def nth_product(index: int, *args: Iterable[_T]) -> Tuple[_T, ...]: ... def nth_permutation( iterable: Iterable[_T], r: int, index: int ) -> Tuple[_T, ...]: ... def value_chain(*args: Union[_T, Iterable[_T]]) -> Iterable[_T]: ... def product_index(element: Iterable[_T], *args: Iterable[_T]) -> int: ... def combination_index( element: Iterable[_T], iterable: Iterable[_T] ) -> int: ... def permutation_index( element: Iterable[_T], iterable: Iterable[_T] ) -> int: ... def repeat_each(iterable: Iterable[_T], n: int = ...) -> Iterator[_T]: ... class countable(Generic[_T], Iterator[_T]): def __init__(self, iterable: Iterable[_T]) -> None: ... def __iter__(self) -> countable[_T]: ... def __next__(self) -> _T: ... def chunked_even(iterable: Iterable[_T], n: int) -> Iterator[List[_T]]: ... def zip_broadcast( *objects: Union[_T, Iterable[_T]], scalar_types: Union[ type, Tuple[Union[type, Tuple[Any, ...]], ...], None ] = ..., strict: bool = ... ) -> Iterable[Tuple[_T, ...]]: ... ././@PaxHeader0000000000000000000000000000002600000000000011453 xustar000000000000000022 mtime=1571189756.0 more-itertools-8.10.0/more_itertools/py.typed0000644000175000017500000000000000000000000020342 0ustar00bobo00000000000000././@PaxHeader0000000000000000000000000000002600000000000011453 xustar000000000000000022 mtime=1631273684.0 more-itertools-8.10.0/more_itertools/recipes.py0000664000175000017500000004040100000000000020662 0ustar00bobo00000000000000"""Imported from the recipes section of the itertools documentation. All functions taken from the recipes section of the itertools library docs [1]_. Some backward-compatible usability improvements have been made. .. [1] http://docs.python.org/library/itertools.html#recipes """ import warnings from collections import deque from itertools import ( chain, combinations, count, cycle, groupby, islice, repeat, starmap, tee, zip_longest, ) import operator from random import randrange, sample, choice __all__ = [ 'all_equal', 'consume', 'convolve', 'dotproduct', 'first_true', 'flatten', 'grouper', 'iter_except', 'ncycles', 'nth', 'nth_combination', 'padnone', 'pad_none', 'pairwise', 'partition', 'powerset', 'prepend', 'quantify', 'random_combination_with_replacement', 'random_combination', 'random_permutation', 'random_product', 'repeatfunc', 'roundrobin', 'tabulate', 'tail', 'take', 'unique_everseen', 'unique_justseen', ] def take(n, iterable): """Return first *n* items of the iterable as a list. >>> take(3, range(10)) [0, 1, 2] If there are fewer than *n* items in the iterable, all of them are returned. >>> take(10, range(3)) [0, 1, 2] """ return list(islice(iterable, n)) def tabulate(function, start=0): """Return an iterator over the results of ``func(start)``, ``func(start + 1)``, ``func(start + 2)``... *func* should be a function that accepts one integer argument. If *start* is not specified it defaults to 0. It will be incremented each time the iterator is advanced. >>> square = lambda x: x ** 2 >>> iterator = tabulate(square, -3) >>> take(4, iterator) [9, 4, 1, 0] """ return map(function, count(start)) def tail(n, iterable): """Return an iterator over the last *n* items of *iterable*. >>> t = tail(3, 'ABCDEFG') >>> list(t) ['E', 'F', 'G'] """ return iter(deque(iterable, maxlen=n)) def consume(iterator, n=None): """Advance *iterable* by *n* steps. If *n* is ``None``, consume it entirely. Efficiently exhausts an iterator without returning values. Defaults to consuming the whole iterator, but an optional second argument may be provided to limit consumption. >>> i = (x for x in range(10)) >>> next(i) 0 >>> consume(i, 3) >>> next(i) 4 >>> consume(i) >>> next(i) Traceback (most recent call last): File "", line 1, in StopIteration If the iterator has fewer items remaining than the provided limit, the whole iterator will be consumed. >>> i = (x for x in range(3)) >>> consume(i, 5) >>> next(i) Traceback (most recent call last): File "", line 1, in StopIteration """ # Use functions that consume iterators at C speed. if n is None: # feed the entire iterator into a zero-length deque deque(iterator, maxlen=0) else: # advance to the empty slice starting at position n next(islice(iterator, n, n), None) def nth(iterable, n, default=None): """Returns the nth item or a default value. >>> l = range(10) >>> nth(l, 3) 3 >>> nth(l, 20, "zebra") 'zebra' """ return next(islice(iterable, n, None), default) def all_equal(iterable): """ Returns ``True`` if all the elements are equal to each other. >>> all_equal('aaaa') True >>> all_equal('aaab') False """ g = groupby(iterable) return next(g, True) and not next(g, False) def quantify(iterable, pred=bool): """Return the how many times the predicate is true. >>> quantify([True, False, True]) 2 """ return sum(map(pred, iterable)) def pad_none(iterable): """Returns the sequence of elements and then returns ``None`` indefinitely. >>> take(5, pad_none(range(3))) [0, 1, 2, None, None] Useful for emulating the behavior of the built-in :func:`map` function. See also :func:`padded`. """ return chain(iterable, repeat(None)) padnone = pad_none def ncycles(iterable, n): """Returns the sequence elements *n* times >>> list(ncycles(["a", "b"], 3)) ['a', 'b', 'a', 'b', 'a', 'b'] """ return chain.from_iterable(repeat(tuple(iterable), n)) def dotproduct(vec1, vec2): """Returns the dot product of the two iterables. >>> dotproduct([10, 10], [20, 20]) 400 """ return sum(map(operator.mul, vec1, vec2)) def flatten(listOfLists): """Return an iterator flattening one level of nesting in a list of lists. >>> list(flatten([[0, 1], [2, 3]])) [0, 1, 2, 3] See also :func:`collapse`, which can flatten multiple levels of nesting. """ return chain.from_iterable(listOfLists) def repeatfunc(func, times=None, *args): """Call *func* with *args* repeatedly, returning an iterable over the results. If *times* is specified, the iterable will terminate after that many repetitions: >>> from operator import add >>> times = 4 >>> args = 3, 5 >>> list(repeatfunc(add, times, *args)) [8, 8, 8, 8] If *times* is ``None`` the iterable will not terminate: >>> from random import randrange >>> times = None >>> args = 1, 11 >>> take(6, repeatfunc(randrange, times, *args)) # doctest:+SKIP [2, 4, 8, 1, 8, 4] """ if times is None: return starmap(func, repeat(args)) return starmap(func, repeat(args, times)) def _pairwise(iterable): """Returns an iterator of paired items, overlapping, from the original >>> take(4, pairwise(count())) [(0, 1), (1, 2), (2, 3), (3, 4)] On Python 3.10 and above, this is an alias for :func:`itertools.pairwise`. """ a, b = tee(iterable) next(b, None) yield from zip(a, b) try: from itertools import pairwise as itertools_pairwise except ImportError: pairwise = _pairwise else: def pairwise(iterable): yield from itertools_pairwise(iterable) pairwise.__doc__ = _pairwise.__doc__ def grouper(iterable, n, fillvalue=None): """Collect data into fixed-length chunks or blocks. >>> list(grouper('ABCDEFG', 3, 'x')) [('A', 'B', 'C'), ('D', 'E', 'F'), ('G', 'x', 'x')] """ if isinstance(iterable, int): warnings.warn( "grouper expects iterable as first parameter", DeprecationWarning ) n, iterable = iterable, n args = [iter(iterable)] * n return zip_longest(fillvalue=fillvalue, *args) def roundrobin(*iterables): """Yields an item from each iterable, alternating between them. >>> list(roundrobin('ABC', 'D', 'EF')) ['A', 'D', 'E', 'B', 'F', 'C'] This function produces the same output as :func:`interleave_longest`, but may perform better for some inputs (in particular when the number of iterables is small). """ # Recipe credited to George Sakkis pending = len(iterables) nexts = cycle(iter(it).__next__ for it in iterables) while pending: try: for next in nexts: yield next() except StopIteration: pending -= 1 nexts = cycle(islice(nexts, pending)) def partition(pred, iterable): """ Returns a 2-tuple of iterables derived from the input iterable. The first yields the items that have ``pred(item) == False``. The second yields the items that have ``pred(item) == True``. >>> is_odd = lambda x: x % 2 != 0 >>> iterable = range(10) >>> even_items, odd_items = partition(is_odd, iterable) >>> list(even_items), list(odd_items) ([0, 2, 4, 6, 8], [1, 3, 5, 7, 9]) If *pred* is None, :func:`bool` is used. >>> iterable = [0, 1, False, True, '', ' '] >>> false_items, true_items = partition(None, iterable) >>> list(false_items), list(true_items) ([0, False, ''], [1, True, ' ']) """ if pred is None: pred = bool evaluations = ((pred(x), x) for x in iterable) t1, t2 = tee(evaluations) return ( (x for (cond, x) in t1 if not cond), (x for (cond, x) in t2 if cond), ) def powerset(iterable): """Yields all possible subsets of the iterable. >>> list(powerset([1, 2, 3])) [(), (1,), (2,), (3,), (1, 2), (1, 3), (2, 3), (1, 2, 3)] :func:`powerset` will operate on iterables that aren't :class:`set` instances, so repeated elements in the input will produce repeated elements in the output. Use :func:`unique_everseen` on the input to avoid generating duplicates: >>> seq = [1, 1, 0] >>> list(powerset(seq)) [(), (1,), (1,), (0,), (1, 1), (1, 0), (1, 0), (1, 1, 0)] >>> from more_itertools import unique_everseen >>> list(powerset(unique_everseen(seq))) [(), (1,), (0,), (1, 0)] """ s = list(iterable) return chain.from_iterable(combinations(s, r) for r in range(len(s) + 1)) def unique_everseen(iterable, key=None): """ Yield unique elements, preserving order. >>> list(unique_everseen('AAAABBBCCDAABBB')) ['A', 'B', 'C', 'D'] >>> list(unique_everseen('ABBCcAD', str.lower)) ['A', 'B', 'C', 'D'] Sequences with a mix of hashable and unhashable items can be used. The function will be slower (i.e., `O(n^2)`) for unhashable items. Remember that ``list`` objects are unhashable - you can use the *key* parameter to transform the list to a tuple (which is hashable) to avoid a slowdown. >>> iterable = ([1, 2], [2, 3], [1, 2]) >>> list(unique_everseen(iterable)) # Slow [[1, 2], [2, 3]] >>> list(unique_everseen(iterable, key=tuple)) # Faster [[1, 2], [2, 3]] Similary, you may want to convert unhashable ``set`` objects with ``key=frozenset``. For ``dict`` objects, ``key=lambda x: frozenset(x.items())`` can be used. """ seenset = set() seenset_add = seenset.add seenlist = [] seenlist_add = seenlist.append use_key = key is not None for element in iterable: k = key(element) if use_key else element try: if k not in seenset: seenset_add(k) yield element except TypeError: if k not in seenlist: seenlist_add(k) yield element def unique_justseen(iterable, key=None): """Yields elements in order, ignoring serial duplicates >>> list(unique_justseen('AAAABBBCCDAABBB')) ['A', 'B', 'C', 'D', 'A', 'B'] >>> list(unique_justseen('ABBCcAD', str.lower)) ['A', 'B', 'C', 'A', 'D'] """ return map(next, map(operator.itemgetter(1), groupby(iterable, key))) def iter_except(func, exception, first=None): """Yields results from a function repeatedly until an exception is raised. Converts a call-until-exception interface to an iterator interface. Like ``iter(func, sentinel)``, but uses an exception instead of a sentinel to end the loop. >>> l = [0, 1, 2] >>> list(iter_except(l.pop, IndexError)) [2, 1, 0] Multiple exceptions can be specified as a stopping condition: >>> l = [1, 2, 3, '...', 4, 5, 6] >>> list(iter_except(lambda: 1 + l.pop(), (IndexError, TypeError))) [7, 6, 5] >>> list(iter_except(lambda: 1 + l.pop(), (IndexError, TypeError))) [4, 3, 2] >>> list(iter_except(lambda: 1 + l.pop(), (IndexError, TypeError))) [] """ try: if first is not None: yield first() while 1: yield func() except exception: pass def first_true(iterable, default=None, pred=None): """ Returns the first true value in the iterable. If no true value is found, returns *default* If *pred* is not None, returns the first item for which ``pred(item) == True`` . >>> first_true(range(10)) 1 >>> first_true(range(10), pred=lambda x: x > 5) 6 >>> first_true(range(10), default='missing', pred=lambda x: x > 9) 'missing' """ return next(filter(pred, iterable), default) def random_product(*args, repeat=1): """Draw an item at random from each of the input iterables. >>> random_product('abc', range(4), 'XYZ') # doctest:+SKIP ('c', 3, 'Z') If *repeat* is provided as a keyword argument, that many items will be drawn from each iterable. >>> random_product('abcd', range(4), repeat=2) # doctest:+SKIP ('a', 2, 'd', 3) This equivalent to taking a random selection from ``itertools.product(*args, **kwarg)``. """ pools = [tuple(pool) for pool in args] * repeat return tuple(choice(pool) for pool in pools) def random_permutation(iterable, r=None): """Return a random *r* length permutation of the elements in *iterable*. If *r* is not specified or is ``None``, then *r* defaults to the length of *iterable*. >>> random_permutation(range(5)) # doctest:+SKIP (3, 4, 0, 1, 2) This equivalent to taking a random selection from ``itertools.permutations(iterable, r)``. """ pool = tuple(iterable) r = len(pool) if r is None else r return tuple(sample(pool, r)) def random_combination(iterable, r): """Return a random *r* length subsequence of the elements in *iterable*. >>> random_combination(range(5), 3) # doctest:+SKIP (2, 3, 4) This equivalent to taking a random selection from ``itertools.combinations(iterable, r)``. """ pool = tuple(iterable) n = len(pool) indices = sorted(sample(range(n), r)) return tuple(pool[i] for i in indices) def random_combination_with_replacement(iterable, r): """Return a random *r* length subsequence of elements in *iterable*, allowing individual elements to be repeated. >>> random_combination_with_replacement(range(3), 5) # doctest:+SKIP (0, 0, 1, 2, 2) This equivalent to taking a random selection from ``itertools.combinations_with_replacement(iterable, r)``. """ pool = tuple(iterable) n = len(pool) indices = sorted(randrange(n) for i in range(r)) return tuple(pool[i] for i in indices) def nth_combination(iterable, r, index): """Equivalent to ``list(combinations(iterable, r))[index]``. The subsequences of *iterable* that are of length *r* can be ordered lexicographically. :func:`nth_combination` computes the subsequence at sort position *index* directly, without computing the previous subsequences. >>> nth_combination(range(5), 3, 5) (0, 3, 4) ``ValueError`` will be raised If *r* is negative or greater than the length of *iterable*. ``IndexError`` will be raised if the given *index* is invalid. """ pool = tuple(iterable) n = len(pool) if (r < 0) or (r > n): raise ValueError c = 1 k = min(r, n - r) for i in range(1, k + 1): c = c * (n - k + i) // i if index < 0: index += c if (index < 0) or (index >= c): raise IndexError result = [] while r: c, n, r = c * r // n, n - 1, r - 1 while index >= c: index -= c c, n = c * (n - r) // n, n - 1 result.append(pool[-1 - n]) return tuple(result) def prepend(value, iterator): """Yield *value*, followed by the elements in *iterator*. >>> value = '0' >>> iterator = ['1', '2', '3'] >>> list(prepend(value, iterator)) ['0', '1', '2', '3'] To prepend multiple values, see :func:`itertools.chain` or :func:`value_chain`. """ return chain([value], iterator) def convolve(signal, kernel): """Convolve the iterable *signal* with the iterable *kernel*. >>> signal = (1, 2, 3, 4, 5) >>> kernel = [3, 2, 1] >>> list(convolve(signal, kernel)) [3, 8, 14, 20, 26, 14, 5] Note: the input arguments are not interchangeable, as the *kernel* is immediately consumed and stored. """ kernel = tuple(kernel)[::-1] n = len(kernel) window = deque([0], maxlen=n) * n for x in chain(signal, repeat(0, n - 1)): window.append(x) yield sum(map(operator.mul, kernel, window)) ././@PaxHeader0000000000000000000000000000002600000000000011453 xustar000000000000000022 mtime=1631273505.0 more-itertools-8.10.0/more_itertools/recipes.pyi0000664000175000017500000000707000000000000021040 0ustar00bobo00000000000000"""Stubs for more_itertools.recipes""" from typing import ( Any, Callable, Iterable, Iterator, List, Optional, Tuple, TypeVar, Union, ) from typing_extensions import overload, Type # Type and type variable definitions _T = TypeVar('_T') _U = TypeVar('_U') def take(n: int, iterable: Iterable[_T]) -> List[_T]: ... def tabulate( function: Callable[[int], _T], start: int = ... ) -> Iterator[_T]: ... def tail(n: int, iterable: Iterable[_T]) -> Iterator[_T]: ... def consume(iterator: Iterable[object], n: Optional[int] = ...) -> None: ... @overload def nth(iterable: Iterable[_T], n: int) -> Optional[_T]: ... @overload def nth(iterable: Iterable[_T], n: int, default: _U) -> Union[_T, _U]: ... def all_equal(iterable: Iterable[object]) -> bool: ... def quantify( iterable: Iterable[_T], pred: Callable[[_T], bool] = ... ) -> int: ... def pad_none(iterable: Iterable[_T]) -> Iterator[Optional[_T]]: ... def padnone(iterable: Iterable[_T]) -> Iterator[Optional[_T]]: ... def ncycles(iterable: Iterable[_T], n: int) -> Iterator[_T]: ... def dotproduct(vec1: Iterable[object], vec2: Iterable[object]) -> object: ... def flatten(listOfLists: Iterable[Iterable[_T]]) -> Iterator[_T]: ... def repeatfunc( func: Callable[..., _U], times: Optional[int] = ..., *args: Any ) -> Iterator[_U]: ... def pairwise(iterable: Iterable[_T]) -> Iterator[Tuple[_T, _T]]: ... @overload def grouper( iterable: Iterable[_T], n: int ) -> Iterator[Tuple[Optional[_T], ...]]: ... @overload def grouper( iterable: Iterable[_T], n: int, fillvalue: _U ) -> Iterator[Tuple[Union[_T, _U], ...]]: ... @overload def grouper( # Deprecated interface iterable: int, n: Iterable[_T] ) -> Iterator[Tuple[Optional[_T], ...]]: ... @overload def grouper( # Deprecated interface iterable: int, n: Iterable[_T], fillvalue: _U ) -> Iterator[Tuple[Union[_T, _U], ...]]: ... def roundrobin(*iterables: Iterable[_T]) -> Iterator[_T]: ... def partition( pred: Optional[Callable[[_T], object]], iterable: Iterable[_T] ) -> Tuple[Iterator[_T], Iterator[_T]]: ... def powerset(iterable: Iterable[_T]) -> Iterator[Tuple[_T, ...]]: ... def unique_everseen( iterable: Iterable[_T], key: Optional[Callable[[_T], _U]] = ... ) -> Iterator[_T]: ... def unique_justseen( iterable: Iterable[_T], key: Optional[Callable[[_T], object]] = ... ) -> Iterator[_T]: ... @overload def iter_except( func: Callable[[], _T], exception: Union[Type[BaseException], Tuple[Type[BaseException], ...]], first: None = ..., ) -> Iterator[_T]: ... @overload def iter_except( func: Callable[[], _T], exception: Union[Type[BaseException], Tuple[Type[BaseException], ...]], first: Callable[[], _U], ) -> Iterator[Union[_T, _U]]: ... @overload def first_true( iterable: Iterable[_T], *, pred: Optional[Callable[[_T], object]] = ... ) -> Optional[_T]: ... @overload def first_true( iterable: Iterable[_T], default: _U, pred: Optional[Callable[[_T], object]] = ..., ) -> Union[_T, _U]: ... def random_product( *args: Iterable[_T], repeat: int = ... ) -> Tuple[_T, ...]: ... def random_permutation( iterable: Iterable[_T], r: Optional[int] = ... ) -> Tuple[_T, ...]: ... def random_combination(iterable: Iterable[_T], r: int) -> Tuple[_T, ...]: ... def random_combination_with_replacement( iterable: Iterable[_T], r: int ) -> Tuple[_T, ...]: ... def nth_combination( iterable: Iterable[_T], r: int, index: int ) -> Tuple[_T, ...]: ... def prepend(value: _T, iterator: Iterable[_U]) -> Iterator[Union[_T, _U]]: ... def convolve(signal: Iterable[_T], kernel: Iterable[_T]) -> Iterator[_T]: ... ././@PaxHeader0000000000000000000000000000003400000000000011452 xustar000000000000000028 mtime=1631883775.1376212 more-itertools-8.10.0/more_itertools.egg-info/0000775000175000017500000000000000000000000020351 5ustar00bobo00000000000000././@PaxHeader0000000000000000000000000000002600000000000011453 xustar000000000000000022 mtime=1631883775.0 more-itertools-8.10.0/more_itertools.egg-info/PKG-INFO0000664000175000017500000010776400000000000021465 0ustar00bobo00000000000000Metadata-Version: 2.1 Name: more-itertools Version: 8.10.0 Summary: More routines for operating on iterables, beyond itertools Home-page: https://github.com/more-itertools/more-itertools Author: Erik Rose Author-email: erikrose@grinchcentral.com License: MIT Keywords: itertools,iterator,iteration,filter,peek,peekable,collate,chunk,chunked Platform: UNKNOWN Classifier: Development Status :: 5 - Production/Stable Classifier: Intended Audience :: Developers Classifier: Natural Language :: English Classifier: License :: OSI Approved :: MIT License Classifier: Programming Language :: Python :: 3 Classifier: Programming Language :: Python :: 3.6 Classifier: Programming Language :: Python :: 3.7 Classifier: Programming Language :: Python :: 3.8 Classifier: Programming Language :: Python :: 3.9 Classifier: Programming Language :: Python :: 3 :: Only Classifier: Programming Language :: Python :: Implementation :: CPython Classifier: Programming Language :: Python :: Implementation :: PyPy Classifier: Topic :: Software Development :: Libraries Requires-Python: >=3.5 Description-Content-Type: text/x-rst License-File: LICENSE ============== More Itertools ============== .. image:: https://readthedocs.org/projects/more-itertools/badge/?version=latest :target: https://more-itertools.readthedocs.io/en/stable/ Python's ``itertools`` library is a gem - you can compose elegant solutions for a variety of problems with the functions it provides. In ``more-itertools`` we collect additional building blocks, recipes, and routines for working with Python iterables. +------------------------+-----------------------------------------------------------------------------------------------------------------------------------------------------------------------------+ | Grouping | `chunked `_, | | | `ichunked `_, | | | `sliced `_, | | | `distribute `_, | | | `divide `_, | | | `split_at `_, | | | `split_before `_, | | | `split_after `_, | | | `split_into `_, | | | `split_when `_, | | | `bucket `_, | | | `unzip `_, | | | `grouper `_, | | | `partition `_ | +------------------------+-----------------------------------------------------------------------------------------------------------------------------------------------------------------------------+ | Lookahead and lookback | `spy `_, | | | `peekable `_, | | | `seekable `_ | +------------------------+-----------------------------------------------------------------------------------------------------------------------------------------------------------------------------+ | Windowing | `windowed `_, | | | `substrings `_, | | | `substrings_indexes `_, | | | `stagger `_, | | | `windowed_complete `_, | | | `pairwise `_ | +------------------------+-----------------------------------------------------------------------------------------------------------------------------------------------------------------------------+ | Augmenting | `count_cycle `_, | | | `intersperse `_, | | | `padded `_, | | | `mark_ends `_, | | | `repeat_last `_, | | | `adjacent `_, | | | `groupby_transform `_, | | | `pad_none `_, | | | `ncycles `_ | +------------------------+-----------------------------------------------------------------------------------------------------------------------------------------------------------------------------+ | Combining | `collapse `_, | | | `sort_together `_, | | | `interleave `_, | | | `interleave_longest `_, | | | `interleave_evenly `_, | | | `zip_offset `_, | | | `zip_equal `_, | | | `zip_broadcast `_, | | | `dotproduct `_, | | | `convolve `_, | | | `flatten `_, | | | `roundrobin `_, | | | `prepend `_, | | | `value_chain `_ | +------------------------+-----------------------------------------------------------------------------------------------------------------------------------------------------------------------------+ | Summarizing | `ilen `_, | | | `unique_to_each `_, | | | `sample `_, | | | `consecutive_groups `_, | | | `run_length `_, | | | `map_reduce `_, | | | `exactly_n `_, | | | `is_sorted `_, | | | `all_equal `_, | | | `all_unique `_, | | | `first_true `_, | | | `quantify `_ | +------------------------+-----------------------------------------------------------------------------------------------------------------------------------------------------------------------------+ | Selecting | `islice_extended `_, | | | `first `_, | | | `last `_, | | | `one `_, | | | `only `_, | | | `strip `_, | | | `lstrip `_, | | | `rstrip `_, | | | `filter_except `_ | | | `map_except `_ | | | `nth_or_last `_, | | | `nth `_, | | | `take `_, | | | `tail `_, | | | `unique_everseen `_, | | | `unique_justseen `_ | +------------------------+-----------------------------------------------------------------------------------------------------------------------------------------------------------------------------+ | Combinatorics | `distinct_permutations `_, | | | `distinct_combinations `_, | | | `circular_shifts `_, | | | `partitions `_, | | | `set_partitions `_, | | | `product_index `_, | | | `combination_index `_, | | | `permutation_index `_, | | | `powerset `_, | | | `random_product `_, | | | `random_permutation `_, | | | `random_combination `_, | | | `random_combination_with_replacement `_, | | | `nth_product `_ | | | `nth_permutation `_ | | | `nth_combination `_ | +------------------------+-----------------------------------------------------------------------------------------------------------------------------------------------------------------------------+ | Wrapping | `always_iterable `_, | | | `always_reversible `_, | | | `countable `_, | | | `consumer `_, | | | `with_iter `_, | | | `iter_except `_ | +------------------------+-----------------------------------------------------------------------------------------------------------------------------------------------------------------------------+ | Others | `locate `_, | | | `rlocate `_, | | | `replace `_, | | | `numeric_range `_, | | | `side_effect `_, | | | `iterate `_, | | | `difference `_, | | | `make_decorator `_, | | | `SequenceView `_, | | | `time_limited `_, | | | `consume `_, | | | `tabulate `_, | | | `repeatfunc `_ | +------------------------+-----------------------------------------------------------------------------------------------------------------------------------------------------------------------------+ Getting started =============== To get started, install the library with `pip `_: .. code-block:: shell pip install more-itertools The recipes from the `itertools docs `_ are included in the top-level package: .. code-block:: python >>> from more_itertools import flatten >>> iterable = [(0, 1), (2, 3)] >>> list(flatten(iterable)) [0, 1, 2, 3] Several new recipes are available as well: .. code-block:: python >>> from more_itertools import chunked >>> iterable = [0, 1, 2, 3, 4, 5, 6, 7, 8] >>> list(chunked(iterable, 3)) [[0, 1, 2], [3, 4, 5], [6, 7, 8]] >>> from more_itertools import spy >>> iterable = (x * x for x in range(1, 6)) >>> head, iterable = spy(iterable, n=3) >>> list(head) [1, 4, 9] >>> list(iterable) [1, 4, 9, 16, 25] For the full listing of functions, see the `API documentation `_. Links elsewhere =============== Blog posts about ``more-itertools``: * `Yo, I heard you like decorators `__ * `Tour of Python Itertools `__ (`Alternate `__) Development =========== ``more-itertools`` is maintained by `@erikrose `_ and `@bbayles `_, with help from `many others `_. If you have a problem or suggestion, please file a bug or pull request in this repository. Thanks for contributing! Version History =============== :noindex: 8.10.0 ------ * Changes to existing functions * The type stub for iter_except was improved (thanks to MarcinKonowalczyk) * Other changes: * Type stubs now ship with the source release (thanks to saaketp) * The Sphinx docs were improved (thanks to MarcinKonowalczyk) 8.9.0 ----- * New functions * interleave_evenly (thanks to mbugert) * repeat_each (thanks to FinalSh4re) * chunked_even (thanks to valtron) * map_if (thanks to sassbalint) * zip_broadcast (thanks to kalekundert) * Changes to existing functions * The type stub for chunked was improved (thanks to PhilMacKay) * The type stubs for zip_equal and `zip_offset` were improved (thanks to maffoo) * Building Sphinx docs locally was improved (thanks to MarcinKonowalczyk) 8.8.0 ----- * New functions * countable (thanks to krzysieq) * Changes to existing functions * split_before was updated to handle empy collections (thanks to TiunovNN) * unique_everseen got a performance boost (thanks to Numerlor) * The type hint for value_chain was corrected (thanks to vr2262) 8.7.0 ----- * New functions * convolve (from the Python itertools docs) * product_index, combination_index, and permutation_index (thanks to N8Brooks) * value_chain (thanks to jenstroeger) * Changes to existing functions * distinct_combinations now uses a non-recursive algorithm (thanks to knutdrand) * pad_none is now the preferred name for padnone, though the latter remains available. * pairwise will now use the Python standard library implementation on Python 3.10+ * sort_together now accepts a ``key`` argument (thanks to brianmaissy) * seekable now has a ``peek`` method, and can indicate whether the iterator it's wrapping is exhausted (thanks to gsakkis) * time_limited can now indicate whether its iterator has expired (thanks to roysmith) * The implementation of unique_everseen was improved (thanks to plammens) * Other changes: * Various documentation updates (thanks to cthoyt, Evantm, and cyphase) 8.6.0 ----- * New itertools * all_unique (thanks to brianmaissy) * nth_product and nth_permutation (thanks to N8Brooks) * Changes to existing itertools * chunked and sliced now accept a ``strict`` parameter (thanks to shlomif and jtwool) * Other changes * Python 3.5 has reached its end of life and is no longer supported. * Python 3.9 is officially supported. * Various documentation fixes (thanks to timgates42) 8.5.0 ----- * New itertools * windowed_complete (thanks to MarcinKonowalczyk) * Changes to existing itertools: * The is_sorted implementation was improved (thanks to cool-RR) * The groupby_transform now accepts a ``reducefunc`` parameter. * The last implementation was improved (thanks to brianmaissy) * Other changes * Various documentation fixes (thanks to craigrosie, samuelstjean, PiCT0) * The tests for distinct_combinations were improved (thanks to Minabsapi) * Automated tests now run on GitHub Actions. All commits now check: * That unit tests pass * That the examples in docstrings work * That test coverage remains high (using `coverage`) * For linting errors (using `flake8`) * For consistent style (using `black`) * That the type stubs work (using `mypy`) * That the docs build correctly (using `sphinx`) * That packages build correctly (using `twine`) 8.4.0 ----- * New itertools * mark_ends (thanks to kalekundert) * is_sorted * Changes to existing itertools: * islice_extended can now be used with real slices (thanks to cool-RR) * The implementations for filter_except and map_except were improved (thanks to SergBobrovsky) * Other changes * Automated tests now enforce code style (using `black `__) * The various signatures of islice_extended and numeric_range now appear in the docs (thanks to dsfulf) * The test configuration for mypy was updated (thanks to blueyed) 8.3.0 ----- * New itertools * zip_equal (thanks to frankier and alexmojaki) * Changes to existing itertools: * split_at, split_before, split_after, and split_when all got a ``maxsplit`` paramter (thanks to jferard and ilai-deutel) * split_at now accepts a ``keep_separator`` parameter (thanks to jferard) * distinct_permutations can now generate ``r``-length permutations (thanks to SergBobrovsky and ilai-deutel) * The windowed implementation was improved (thanks to SergBobrovsky) * The spy implementation was improved (thanks to has2k1) * Other changes * Type stubs are now tested with ``stubtest`` (thanks to ilai-deutel) * Tests now run with ``python -m unittest`` instead of ``python setup.py test`` (thanks to jdufresne) 8.2.0 ----- * Bug fixes * The .pyi files for typing were updated. (thanks to blueyed and ilai-deutel) * Changes to existing itertools: * numeric_range now behaves more like the built-in range. (thanks to jferard) * bucket now allows for enumerating keys. (thanks to alexchandel) * sliced now should now work for numpy arrays. (thanks to sswingle) * seekable now has a ``maxlen`` parameter. 8.1.0 ----- * Bug fixes * partition works with ``pred=None`` again. (thanks to MSeifert04) * New itertools * sample (thanks to tommyod) * nth_or_last (thanks to d-ryzhikov) * Changes to existing itertools: * The implementation for divide was improved. (thanks to jferard) 8.0.2 ----- * Bug fixes * The type stub files are now part of the wheel distribution (thanks to keisheiled) 8.0.1 ----- * Bug fixes * The type stub files now work for functions imported from the root package (thanks to keisheiled) 8.0.0 ----- * New itertools and other additions * This library now ships type hints for use with mypy. (thanks to ilai-deutel for the implementation, and to gabbard and fmagin for assistance) * split_when (thanks to jferard) * repeat_last (thanks to d-ryzhikov) * Changes to existing itertools: * The implementation for set_partitions was improved. (thanks to jferard) * partition was optimized for expensive predicates. (thanks to stevecj) * unique_everseen and groupby_transform were re-factored. (thanks to SergBobrovsky) * The implementation for difference was improved. (thanks to Jabbey92) * Other changes * Python 3.4 has reached its end of life and is no longer supported. * Python 3.8 is officially supported. (thanks to jdufresne) * The ``collate`` function has been deprecated. It raises a ``DeprecationWarning`` if used, and will be removed in a future release. * one and only now provide more informative error messages. (thanks to gabbard) * Unit tests were moved outside of the main package (thanks to jdufresne) * Various documentation fixes (thanks to kriomant, gabbard, jdufresne) 7.2.0 ----- * New itertools * distinct_combinations * set_partitions (thanks to kbarrett) * filter_except * map_except 7.1.0 ----- * New itertools * ichunked (thanks davebelais and youtux) * only (thanks jaraco) * Changes to existing itertools: * numeric_range now supports ranges specified by ``datetime.datetime`` and ``datetime.timedelta`` objects (thanks to MSeifert04 for tests). * difference now supports an *initial* keyword argument. * Other changes * Various documentation fixes (thanks raimon49, pylang) 7.0.0 ----- * New itertools: * time_limited * partitions (thanks to rominf and Saluev) * substrings_indexes (thanks to rominf) * Changes to existing itertools: * collapse now treats ``bytes`` objects the same as ``str`` objects. (thanks to Sweenpet) The major version update is due to the change in the default behavior of collapse. It now treats ``bytes`` objects the same as ``str`` objects. This aligns its behavior with always_iterable. .. code-block:: python >>> from more_itertools import collapse >>> iterable = [[1, 2], b'345', [6]] >>> print(list(collapse(iterable))) [1, 2, b'345', 6] 6.0.0 ----- * Major changes: * Python 2.7 is no longer supported. The 5.0.0 release will be the last version targeting Python 2.7. * All future releases will target the active versions of Python 3. As of 2019, those are Python 3.4 and above. * The ``six`` library is no longer a dependency. * The accumulate function is no longer part of this library. You may import a better version from the standard ``itertools`` module. * Changes to existing itertools: * The order of the parameters in grouper have changed to match the latest recipe in the itertools documentation. Use of the old order will be supported in this release, but emit a ``DeprecationWarning``. The legacy behavior will be dropped in a future release. (thanks to jaraco) * distinct_permutations was improved (thanks to jferard - see also `permutations with unique values `_ at StackOverflow.) * An unused parameter was removed from substrings. (thanks to pylang) * Other changes: * The docs for unique_everseen were improved. (thanks to jferard and MSeifert04) * Several Python 2-isms were removed. (thanks to jaraco, MSeifert04, and hugovk) ././@PaxHeader0000000000000000000000000000002600000000000011453 xustar000000000000000022 mtime=1631883775.0 more-itertools-8.10.0/more_itertools.egg-info/SOURCES.txt0000664000175000017500000000115000000000000022232 0ustar00bobo00000000000000LICENSE MANIFEST.in README.rst pyproject.toml setup.cfg setup.py tox.ini docs/Makefile docs/api.rst docs/conf.py docs/index.rst docs/license.rst docs/make.bat docs/testing.rst docs/versions.rst docs/_static/theme_overrides.css more_itertools/__init__.py more_itertools/__init__.pyi more_itertools/more.py more_itertools/more.pyi more_itertools/py.typed more_itertools/recipes.py more_itertools/recipes.pyi more_itertools.egg-info/PKG-INFO more_itertools.egg-info/SOURCES.txt more_itertools.egg-info/dependency_links.txt more_itertools.egg-info/top_level.txt tests/__init__.py tests/test_more.py tests/test_recipes.py././@PaxHeader0000000000000000000000000000002600000000000011453 xustar000000000000000022 mtime=1631883775.0 more-itertools-8.10.0/more_itertools.egg-info/dependency_links.txt0000664000175000017500000000000100000000000024417 0ustar00bobo00000000000000 ././@PaxHeader0000000000000000000000000000002600000000000011453 xustar000000000000000022 mtime=1631883775.0 more-itertools-8.10.0/more_itertools.egg-info/top_level.txt0000664000175000017500000000001700000000000023101 0ustar00bobo00000000000000more_itertools ././@PaxHeader0000000000000000000000000000002600000000000011453 xustar000000000000000022 mtime=1590956674.0 more-itertools-8.10.0/pyproject.toml0000664000175000017500000000013100000000000016520 0ustar00bobo00000000000000[tool.black] line-length = 79 target-version = ['py35'] skip-string-normalization = true ././@PaxHeader0000000000000000000000000000003400000000000011452 xustar000000000000000028 mtime=1631883775.1376212 more-itertools-8.10.0/setup.cfg0000664000175000017500000000132100000000000015427 0ustar00bobo00000000000000[bumpversion] current_version = 8.10.0 commit = True tag = False files = more_itertools/__init__.py [flake8] exclude = ./docs/conf.py, .eggs/ ignore = E203, E731, E741, F999, W503 [mypy] check_untyped_defs = true disallow_any_generics = true disallow_incomplete_defs = true disallow_subclassing_any = true disallow_untyped_calls = true disallow_untyped_decorators = true disallow_untyped_defs = true ignore_missing_imports = true no_implicit_optional = true show_error_codes = true strict_equality = true warn_redundant_casts = true warn_return_any = true warn_unreachable = true warn_unused_configs = true warn_unused_ignores = true [mypy-tests.*] disallow_untyped_defs = false [egg_info] tag_build = tag_date = 0 ././@PaxHeader0000000000000000000000000000002600000000000011453 xustar000000000000000022 mtime=1631795515.0 more-itertools-8.10.0/setup.py0000664000175000017500000000405300000000000015325 0ustar00bobo00000000000000from re import sub from setuptools import setup from more_itertools import __version__ def get_long_description(): # Fix display issues on PyPI caused by RST markup readme = open('README.rst').read() version_lines = [] with open('docs/versions.rst') as infile: next(infile) for line in infile: line = line.rstrip().replace('.. automodule:: more_itertools', '') if line == '5.0.0': break version_lines.append(line) version_history = '\n'.join(version_lines) version_history = sub(r':func:`([a-zA-Z0-9._]+)`', r'\1', version_history) ret = readme + '\n\n' + version_history return ret setup( name='more-itertools', version=__version__, description='More routines for operating on iterables, beyond itertools', long_description=get_long_description(), long_description_content_type='text/x-rst', author='Erik Rose', author_email='erikrose@grinchcentral.com', license='MIT', packages=['more_itertools'], package_data={'more_itertools': ['py.typed', '*.pyi']}, python_requires='>=3.5', url='https://github.com/more-itertools/more-itertools', classifiers=[ 'Development Status :: 5 - Production/Stable', 'Intended Audience :: Developers', 'Natural Language :: English', 'License :: OSI Approved :: MIT License', 'Programming Language :: Python :: 3', 'Programming Language :: Python :: 3.6', 'Programming Language :: Python :: 3.7', 'Programming Language :: Python :: 3.8', 'Programming Language :: Python :: 3.9', 'Programming Language :: Python :: 3 :: Only', 'Programming Language :: Python :: Implementation :: CPython', 'Programming Language :: Python :: Implementation :: PyPy', 'Topic :: Software Development :: Libraries', ], keywords=[ 'itertools', 'iterator', 'iteration', 'filter', 'peek', 'peekable', 'collate', 'chunk', 'chunked', ], ) ././@PaxHeader0000000000000000000000000000003400000000000011452 xustar000000000000000028 mtime=1631883775.1376212 more-itertools-8.10.0/tests/0000775000175000017500000000000000000000000014753 5ustar00bobo00000000000000././@PaxHeader0000000000000000000000000000002600000000000011453 xustar000000000000000022 mtime=1573524212.0 more-itertools-8.10.0/tests/__init__.py0000644000175000017500000000000000000000000017050 0ustar00bobo00000000000000././@PaxHeader0000000000000000000000000000002600000000000011453 xustar000000000000000022 mtime=1630669869.0 more-itertools-8.10.0/tests/test_more.py0000664000175000017500000046633000000000000017342 0ustar00bobo00000000000000import warnings from collections import Counter, abc from collections.abc import Set from datetime import datetime, timedelta from decimal import Decimal from doctest import DocTestSuite from fractions import Fraction from functools import partial, reduce from heapq import merge from io import StringIO from itertools import ( accumulate, chain, combinations, count, cycle, groupby, islice, permutations, product, repeat, ) from operator import add, mul, itemgetter from pickle import loads, dumps from random import seed, Random from statistics import mean from string import ascii_letters from sys import version_info from time import sleep from traceback import format_exc from unittest import skipIf, TestCase import more_itertools as mi def load_tests(loader, tests, ignore): # Add the doctests tests.addTests(DocTestSuite('more_itertools.more')) return tests class CollateTests(TestCase): """Unit tests for ``collate()``""" # Also accidentally tests peekable, though that could use its own tests def test_default(self): """Test with the default `key` function.""" iterables = [range(4), range(7), range(3, 6)] self.assertEqual( sorted(reduce(list.__add__, [list(it) for it in iterables])), list(mi.collate(*iterables)), ) def test_key(self): """Test using a custom `key` function.""" iterables = [range(5, 0, -1), range(4, 0, -1)] actual = sorted( reduce(list.__add__, [list(it) for it in iterables]), reverse=True ) expected = list(mi.collate(*iterables, key=lambda x: -x)) self.assertEqual(actual, expected) def test_empty(self): """Be nice if passed an empty list of iterables.""" self.assertEqual([], list(mi.collate())) def test_one(self): """Work when only 1 iterable is passed.""" self.assertEqual([0, 1], list(mi.collate(range(2)))) def test_reverse(self): """Test the `reverse` kwarg.""" iterables = [range(4, 0, -1), range(7, 0, -1), range(3, 6, -1)] actual = sorted( reduce(list.__add__, [list(it) for it in iterables]), reverse=True ) expected = list(mi.collate(*iterables, reverse=True)) self.assertEqual(actual, expected) def test_alias(self): self.assertNotEqual(merge.__doc__, mi.collate.__doc__) self.assertNotEqual(partial.__doc__, mi.collate.__doc__) class ChunkedTests(TestCase): """Tests for ``chunked()``""" def test_even(self): """Test when ``n`` divides evenly into the length of the iterable.""" self.assertEqual( list(mi.chunked('ABCDEF', 3)), [['A', 'B', 'C'], ['D', 'E', 'F']] ) def test_odd(self): """Test when ``n`` does not divide evenly into the length of the iterable. """ self.assertEqual( list(mi.chunked('ABCDE', 3)), [['A', 'B', 'C'], ['D', 'E']] ) def test_none(self): """Test when ``n`` has the value ``None``.""" self.assertEqual( list(mi.chunked('ABCDE', None)), [['A', 'B', 'C', 'D', 'E']] ) def test_strict_false(self): """Test when ``n`` does not divide evenly into the length of the iterable and strict is false. """ self.assertEqual( list(mi.chunked('ABCDE', 3, strict=False)), [['A', 'B', 'C'], ['D', 'E']], ) def test_strict_being_true(self): """Test when ``n`` does not divide evenly into the length of the iterable and strict is True (raising an exception). """ def f(): return list(mi.chunked('ABCDE', 3, strict=True)) self.assertRaisesRegex(ValueError, "iterable is not divisible by n", f) self.assertEqual( list(mi.chunked('ABCDEF', 3, strict=True)), [['A', 'B', 'C'], ['D', 'E', 'F']], ) def test_strict_being_true_with_size_none(self): """Test when ``n`` has value ``None`` and the keyword strict is True (raising an exception). """ def f(): return list(mi.chunked('ABCDE', None, strict=True)) self.assertRaisesRegex( ValueError, "n must not be None when using strict mode.", f ) class FirstTests(TestCase): def test_many(self): # Also try it on a generator expression to make sure it works on # whatever those return, across Python versions. self.assertEqual(mi.first(x for x in range(4)), 0) def test_one(self): self.assertEqual(mi.first([3]), 3) def test_empty_stop_iteration(self): try: mi.first([]) except ValueError: formatted_exc = format_exc() self.assertIn('StopIteration', formatted_exc) self.assertIn( 'The above exception was the direct cause', formatted_exc ) else: self.fail() def test_default(self): self.assertEqual(mi.first([], 'boo'), 'boo') class IterOnlyRange: """User-defined iterable class which only support __iter__. >>> r = IterOnlyRange(5) >>> r[0] AttributeError: IterOnlyRange instance has no attribute '__getitem__' Note: In Python 3, ``TypeError`` will be raised because ``object`` is inherited implicitly by default. >>> r[0] TypeError: 'IterOnlyRange' object does not support indexing """ def __init__(self, n): """Set the length of the range.""" self.n = n def __iter__(self): """Works same as range().""" return iter(range(self.n)) class LastTests(TestCase): def test_basic(self): cases = [ (range(4), 3), (iter(range(4)), 3), (range(1), 0), (iter(range(1)), 0), (IterOnlyRange(5), 4), ({n: str(n) for n in range(5)}, 4), ] # Versions below 3.6.0 don't have ordered dicts if version_info >= (3, 6, 0): cases.append(({0: '0', -1: '-1', 2: '-2'}, 2)) for iterable, expected in cases: with self.subTest(iterable=iterable): self.assertEqual(mi.last(iterable), expected) def test_default(self): for iterable, default, expected in [ (range(1), None, 0), ([], None, None), ({}, None, None), (iter([]), None, None), ]: with self.subTest(args=(iterable, default)): self.assertEqual(mi.last(iterable, default=default), expected) def test_empty(self): for iterable in ([], iter(range(0))): with self.subTest(iterable=iterable): with self.assertRaises(ValueError): mi.last(iterable) class NthOrLastTests(TestCase): """Tests for ``nth_or_last()``""" def test_basic(self): self.assertEqual(mi.nth_or_last(range(3), 1), 1) self.assertEqual(mi.nth_or_last(range(3), 3), 2) def test_default_value(self): default = 42 self.assertEqual(mi.nth_or_last(range(0), 3, default), default) def test_empty_iterable_no_default(self): self.assertRaises(ValueError, lambda: mi.nth_or_last(range(0), 0)) class PeekableMixinTests: """Common tests for ``peekable()`` and ``seekable()`` behavior""" cls = None def test_passthrough(self): """Iterating a peekable without using ``peek()`` or ``prepend()`` should just give the underlying iterable's elements (a trivial test but useful to set a baseline in case something goes wrong)""" expected = [1, 2, 3, 4, 5] actual = list(self.cls(expected)) self.assertEqual(actual, expected) def test_peek_default(self): """Make sure passing a default into ``peek()`` works.""" p = self.cls([]) self.assertEqual(p.peek(7), 7) def test_truthiness(self): """Make sure a ``peekable`` tests true iff there are items remaining in the iterable. """ p = self.cls([]) self.assertFalse(p) p = self.cls(range(3)) self.assertTrue(p) def test_simple_peeking(self): """Make sure ``next`` and ``peek`` advance and don't advance the iterator, respectively. """ p = self.cls(range(10)) self.assertEqual(next(p), 0) self.assertEqual(p.peek(), 1) self.assertEqual(p.peek(), 1) self.assertEqual(next(p), 1) class PeekableTests(PeekableMixinTests, TestCase): """Tests for ``peekable()`` behavior not incidentally covered by testing ``collate()`` """ cls = mi.peekable def test_indexing(self): """ Indexing into the peekable shouldn't advance the iterator. """ p = mi.peekable('abcdefghijkl') # The 0th index is what ``next()`` will return self.assertEqual(p[0], 'a') self.assertEqual(next(p), 'a') # Indexing further into the peekable shouldn't advance the itertor self.assertEqual(p[2], 'd') self.assertEqual(next(p), 'b') # The 0th index moves up with the iterator; the last index follows self.assertEqual(p[0], 'c') self.assertEqual(p[9], 'l') self.assertEqual(next(p), 'c') self.assertEqual(p[8], 'l') # Negative indexing should work too self.assertEqual(p[-2], 'k') self.assertEqual(p[-9], 'd') self.assertRaises(IndexError, lambda: p[-10]) def test_slicing(self): """Slicing the peekable shouldn't advance the iterator.""" seq = list('abcdefghijkl') p = mi.peekable(seq) # Slicing the peekable should just be like slicing a re-iterable self.assertEqual(p[1:4], seq[1:4]) # Advancing the iterator moves the slices up also self.assertEqual(next(p), 'a') self.assertEqual(p[1:4], seq[1:][1:4]) # Implicit starts and stop should work self.assertEqual(p[:5], seq[1:][:5]) self.assertEqual(p[:], seq[1:][:]) # Indexing past the end should work self.assertEqual(p[:100], seq[1:][:100]) # Steps should work, including negative self.assertEqual(p[::2], seq[1:][::2]) self.assertEqual(p[::-1], seq[1:][::-1]) def test_slicing_reset(self): """Test slicing on a fresh iterable each time""" iterable = ['0', '1', '2', '3', '4', '5'] indexes = list(range(-4, len(iterable) + 4)) + [None] steps = [1, 2, 3, 4, -1, -2, -3, 4] for slice_args in product(indexes, indexes, steps): it = iter(iterable) p = mi.peekable(it) next(p) index = slice(*slice_args) actual = p[index] expected = iterable[1:][index] self.assertEqual(actual, expected, slice_args) def test_slicing_error(self): iterable = '01234567' p = mi.peekable(iter(iterable)) # Prime the cache p.peek() old_cache = list(p._cache) # Illegal slice with self.assertRaises(ValueError): p[1:-1:0] # Neither the cache nor the iteration should be affected self.assertEqual(old_cache, list(p._cache)) self.assertEqual(list(p), list(iterable)) # prepend() behavior tests def test_prepend(self): """Tests intersperesed ``prepend()`` and ``next()`` calls""" it = mi.peekable(range(2)) actual = [] # Test prepend() before next() it.prepend(10) actual += [next(it), next(it)] # Test prepend() between next()s it.prepend(11) actual += [next(it), next(it)] # Test prepend() after source iterable is consumed it.prepend(12) actual += [next(it)] expected = [10, 0, 11, 1, 12] self.assertEqual(actual, expected) def test_multi_prepend(self): """Tests prepending multiple items and getting them in proper order""" it = mi.peekable(range(5)) actual = [next(it), next(it)] it.prepend(10, 11, 12) it.prepend(20, 21) actual += list(it) expected = [0, 1, 20, 21, 10, 11, 12, 2, 3, 4] self.assertEqual(actual, expected) def test_empty(self): """Tests prepending in front of an empty iterable""" it = mi.peekable([]) it.prepend(10) actual = list(it) expected = [10] self.assertEqual(actual, expected) def test_prepend_truthiness(self): """Tests that ``__bool__()`` or ``__nonzero__()`` works properly with ``prepend()``""" it = mi.peekable(range(5)) self.assertTrue(it) actual = list(it) self.assertFalse(it) it.prepend(10) self.assertTrue(it) actual += [next(it)] self.assertFalse(it) expected = [0, 1, 2, 3, 4, 10] self.assertEqual(actual, expected) def test_multi_prepend_peek(self): """Tests prepending multiple elements and getting them in reverse order while peeking""" it = mi.peekable(range(5)) actual = [next(it), next(it)] self.assertEqual(it.peek(), 2) it.prepend(10, 11, 12) self.assertEqual(it.peek(), 10) it.prepend(20, 21) self.assertEqual(it.peek(), 20) actual += list(it) self.assertFalse(it) expected = [0, 1, 20, 21, 10, 11, 12, 2, 3, 4] self.assertEqual(actual, expected) def test_prepend_after_stop(self): """Test resuming iteration after a previous exhaustion""" it = mi.peekable(range(3)) self.assertEqual(list(it), [0, 1, 2]) self.assertRaises(StopIteration, lambda: next(it)) it.prepend(10) self.assertEqual(next(it), 10) self.assertRaises(StopIteration, lambda: next(it)) def test_prepend_slicing(self): """Tests interaction between prepending and slicing""" seq = list(range(20)) p = mi.peekable(seq) p.prepend(30, 40, 50) pseq = [30, 40, 50] + seq # pseq for prepended_seq # adapt the specific tests from test_slicing self.assertEqual(p[0], 30) self.assertEqual(p[1:8], pseq[1:8]) self.assertEqual(p[1:], pseq[1:]) self.assertEqual(p[:5], pseq[:5]) self.assertEqual(p[:], pseq[:]) self.assertEqual(p[:100], pseq[:100]) self.assertEqual(p[::2], pseq[::2]) self.assertEqual(p[::-1], pseq[::-1]) def test_prepend_indexing(self): """Tests interaction between prepending and indexing""" seq = list(range(20)) p = mi.peekable(seq) p.prepend(30, 40, 50) self.assertEqual(p[0], 30) self.assertEqual(next(p), 30) self.assertEqual(p[2], 0) self.assertEqual(next(p), 40) self.assertEqual(p[0], 50) self.assertEqual(p[9], 8) self.assertEqual(next(p), 50) self.assertEqual(p[8], 8) self.assertEqual(p[-2], 18) self.assertEqual(p[-9], 11) self.assertRaises(IndexError, lambda: p[-21]) def test_prepend_iterable(self): """Tests prepending from an iterable""" it = mi.peekable(range(5)) # Don't directly use the range() object to avoid any range-specific # optimizations it.prepend(*(x for x in range(5))) actual = list(it) expected = list(chain(range(5), range(5))) self.assertEqual(actual, expected) def test_prepend_many(self): """Tests that prepending a huge number of elements works""" it = mi.peekable(range(5)) # Don't directly use the range() object to avoid any range-specific # optimizations it.prepend(*(x for x in range(20000))) actual = list(it) expected = list(chain(range(20000), range(5))) self.assertEqual(actual, expected) def test_prepend_reversed(self): """Tests prepending from a reversed iterable""" it = mi.peekable(range(3)) it.prepend(*reversed((10, 11, 12))) actual = list(it) expected = [12, 11, 10, 0, 1, 2] self.assertEqual(actual, expected) class ConsumerTests(TestCase): """Tests for ``consumer()``""" def test_consumer(self): @mi.consumer def eater(): while True: x = yield # noqa e = eater() e.send('hi') # without @consumer, would raise TypeError class DistinctPermutationsTests(TestCase): def test_distinct_permutations(self): """Make sure the output for ``distinct_permutations()`` is the same as set(permutations(it)). """ iterable = ['z', 'a', 'a', 'q', 'q', 'q', 'y'] test_output = sorted(mi.distinct_permutations(iterable)) ref_output = sorted(set(permutations(iterable))) self.assertEqual(test_output, ref_output) def test_other_iterables(self): """Make sure ``distinct_permutations()`` accepts a different type of iterables. """ # a generator iterable = (c for c in ['z', 'a', 'a', 'q', 'q', 'q', 'y']) test_output = sorted(mi.distinct_permutations(iterable)) # "reload" it iterable = (c for c in ['z', 'a', 'a', 'q', 'q', 'q', 'y']) ref_output = sorted(set(permutations(iterable))) self.assertEqual(test_output, ref_output) # an iterator iterable = iter(['z', 'a', 'a', 'q', 'q', 'q', 'y']) test_output = sorted(mi.distinct_permutations(iterable)) # "reload" it iterable = iter(['z', 'a', 'a', 'q', 'q', 'q', 'y']) ref_output = sorted(set(permutations(iterable))) self.assertEqual(test_output, ref_output) def test_r(self): for iterable, r in ( ('mississippi', 0), ('mississippi', 1), ('mississippi', 6), ('mississippi', 7), ('mississippi', 12), ([0, 1, 1, 0], 0), ([0, 1, 1, 0], 1), ([0, 1, 1, 0], 2), ([0, 1, 1, 0], 3), ([0, 1, 1, 0], 4), (['a'], 0), (['a'], 1), (['a'], 5), ([], 0), ([], 1), ([], 4), ): with self.subTest(iterable=iterable, r=r): expected = sorted(set(permutations(iterable, r))) actual = sorted(mi.distinct_permutations(iter(iterable), r)) self.assertEqual(actual, expected) class IlenTests(TestCase): def test_ilen(self): """Sanity-checks for ``ilen()``.""" # Non-empty self.assertEqual( mi.ilen(filter(lambda x: x % 10 == 0, range(101))), 11 ) # Empty self.assertEqual(mi.ilen(x for x in range(0)), 0) # Iterable with __len__ self.assertEqual(mi.ilen(list(range(6))), 6) class WithIterTests(TestCase): def test_with_iter(self): s = StringIO('One fish\nTwo fish') initial_words = [line.split()[0] for line in mi.with_iter(s)] # Iterable's items should be faithfully represented self.assertEqual(initial_words, ['One', 'Two']) # The file object should be closed self.assertTrue(s.closed) class OneTests(TestCase): def test_basic(self): it = iter(['item']) self.assertEqual(mi.one(it), 'item') def test_too_short(self): it = iter([]) for too_short, exc_type in [ (None, ValueError), (IndexError, IndexError), ]: with self.subTest(too_short=too_short): try: mi.one(it, too_short=too_short) except exc_type: formatted_exc = format_exc() self.assertIn('StopIteration', formatted_exc) self.assertIn( 'The above exception was the direct cause', formatted_exc, ) else: self.fail() def test_too_long(self): it = count() self.assertRaises(ValueError, lambda: mi.one(it)) # burn 0 and 1 self.assertEqual(next(it), 2) self.assertRaises( OverflowError, lambda: mi.one(it, too_long=OverflowError) ) def test_too_long_default_message(self): it = count() self.assertRaisesRegex( ValueError, "Expected exactly one item in " "iterable, but got 0, 1, and " "perhaps more.", lambda: mi.one(it), ) class IntersperseTest(TestCase): """Tests for intersperse()""" def test_even(self): iterable = (x for x in '01') self.assertEqual( list(mi.intersperse(None, iterable)), ['0', None, '1'] ) def test_odd(self): iterable = (x for x in '012') self.assertEqual( list(mi.intersperse(None, iterable)), ['0', None, '1', None, '2'] ) def test_nested(self): element = ('a', 'b') iterable = (x for x in '012') actual = list(mi.intersperse(element, iterable)) expected = ['0', ('a', 'b'), '1', ('a', 'b'), '2'] self.assertEqual(actual, expected) def test_not_iterable(self): self.assertRaises(TypeError, lambda: mi.intersperse('x', 1)) def test_n(self): for n, element, expected in [ (1, '_', ['0', '_', '1', '_', '2', '_', '3', '_', '4', '_', '5']), (2, '_', ['0', '1', '_', '2', '3', '_', '4', '5']), (3, '_', ['0', '1', '2', '_', '3', '4', '5']), (4, '_', ['0', '1', '2', '3', '_', '4', '5']), (5, '_', ['0', '1', '2', '3', '4', '_', '5']), (6, '_', ['0', '1', '2', '3', '4', '5']), (7, '_', ['0', '1', '2', '3', '4', '5']), (3, ['a', 'b'], ['0', '1', '2', ['a', 'b'], '3', '4', '5']), ]: iterable = (x for x in '012345') actual = list(mi.intersperse(element, iterable, n=n)) self.assertEqual(actual, expected) def test_n_zero(self): self.assertRaises( ValueError, lambda: list(mi.intersperse('x', '012', n=0)) ) class UniqueToEachTests(TestCase): """Tests for ``unique_to_each()``""" def test_all_unique(self): """When all the input iterables are unique the output should match the input.""" iterables = [[1, 2], [3, 4, 5], [6, 7, 8]] self.assertEqual(mi.unique_to_each(*iterables), iterables) def test_duplicates(self): """When there are duplicates in any of the input iterables that aren't in the rest, those duplicates should be emitted.""" iterables = ["mississippi", "missouri"] self.assertEqual( mi.unique_to_each(*iterables), [['p', 'p'], ['o', 'u', 'r']] ) def test_mixed(self): """When the input iterables contain different types the function should still behave properly""" iterables = ['x', (i for i in range(3)), [1, 2, 3], tuple()] self.assertEqual(mi.unique_to_each(*iterables), [['x'], [0], [3], []]) class WindowedTests(TestCase): """Tests for ``windowed()``""" def test_basic(self): actual = list(mi.windowed([1, 2, 3, 4, 5], 3)) expected = [(1, 2, 3), (2, 3, 4), (3, 4, 5)] self.assertEqual(actual, expected) def test_large_size(self): """ When the window size is larger than the iterable, and no fill value is given,``None`` should be filled in. """ actual = list(mi.windowed([1, 2, 3, 4, 5], 6)) expected = [(1, 2, 3, 4, 5, None)] self.assertEqual(actual, expected) def test_fillvalue(self): """ When sizes don't match evenly, the given fill value should be used. """ iterable = [1, 2, 3, 4, 5] for n, kwargs, expected in [ (6, {}, [(1, 2, 3, 4, 5, '!')]), # n > len(iterable) (3, {'step': 3}, [(1, 2, 3), (4, 5, '!')]), # using ``step`` ]: actual = list(mi.windowed(iterable, n, fillvalue='!', **kwargs)) self.assertEqual(actual, expected) def test_zero(self): """When the window size is zero, an empty tuple should be emitted.""" actual = list(mi.windowed([1, 2, 3, 4, 5], 0)) expected = [tuple()] self.assertEqual(actual, expected) def test_negative(self): """When the window size is negative, ValueError should be raised.""" with self.assertRaises(ValueError): list(mi.windowed([1, 2, 3, 4, 5], -1)) def test_step(self): """The window should advance by the number of steps provided""" iterable = [1, 2, 3, 4, 5, 6, 7] for n, step, expected in [ (3, 2, [(1, 2, 3), (3, 4, 5), (5, 6, 7)]), # n > step (3, 3, [(1, 2, 3), (4, 5, 6), (7, None, None)]), # n == step (3, 4, [(1, 2, 3), (5, 6, 7)]), # line up nicely (3, 5, [(1, 2, 3), (6, 7, None)]), # off by one (3, 6, [(1, 2, 3), (7, None, None)]), # off by two (3, 7, [(1, 2, 3)]), # step past the end (7, 8, [(1, 2, 3, 4, 5, 6, 7)]), # step > len(iterable) ]: actual = list(mi.windowed(iterable, n, step=step)) self.assertEqual(actual, expected) # Step must be greater than or equal to 1 with self.assertRaises(ValueError): list(mi.windowed(iterable, 3, step=0)) class SubstringsTests(TestCase): def test_basic(self): iterable = (x for x in range(4)) actual = list(mi.substrings(iterable)) expected = [ (0,), (1,), (2,), (3,), (0, 1), (1, 2), (2, 3), (0, 1, 2), (1, 2, 3), (0, 1, 2, 3), ] self.assertEqual(actual, expected) def test_strings(self): iterable = 'abc' actual = list(mi.substrings(iterable)) expected = [ ('a',), ('b',), ('c',), ('a', 'b'), ('b', 'c'), ('a', 'b', 'c'), ] self.assertEqual(actual, expected) def test_empty(self): iterable = iter([]) actual = list(mi.substrings(iterable)) expected = [] self.assertEqual(actual, expected) def test_order(self): iterable = [2, 0, 1] actual = list(mi.substrings(iterable)) expected = [(2,), (0,), (1,), (2, 0), (0, 1), (2, 0, 1)] self.assertEqual(actual, expected) class SubstringsIndexesTests(TestCase): def test_basic(self): sequence = [x for x in range(4)] actual = list(mi.substrings_indexes(sequence)) expected = [ ([0], 0, 1), ([1], 1, 2), ([2], 2, 3), ([3], 3, 4), ([0, 1], 0, 2), ([1, 2], 1, 3), ([2, 3], 2, 4), ([0, 1, 2], 0, 3), ([1, 2, 3], 1, 4), ([0, 1, 2, 3], 0, 4), ] self.assertEqual(actual, expected) def test_strings(self): sequence = 'abc' actual = list(mi.substrings_indexes(sequence)) expected = [ ('a', 0, 1), ('b', 1, 2), ('c', 2, 3), ('ab', 0, 2), ('bc', 1, 3), ('abc', 0, 3), ] self.assertEqual(actual, expected) def test_empty(self): sequence = [] actual = list(mi.substrings_indexes(sequence)) expected = [] self.assertEqual(actual, expected) def test_order(self): sequence = [2, 0, 1] actual = list(mi.substrings_indexes(sequence)) expected = [ ([2], 0, 1), ([0], 1, 2), ([1], 2, 3), ([2, 0], 0, 2), ([0, 1], 1, 3), ([2, 0, 1], 0, 3), ] self.assertEqual(actual, expected) def test_reverse(self): sequence = [2, 0, 1] actual = list(mi.substrings_indexes(sequence, reverse=True)) expected = [ ([2, 0, 1], 0, 3), ([2, 0], 0, 2), ([0, 1], 1, 3), ([2], 0, 1), ([0], 1, 2), ([1], 2, 3), ] self.assertEqual(actual, expected) class BucketTests(TestCase): def test_basic(self): iterable = [10, 20, 30, 11, 21, 31, 12, 22, 23, 33] D = mi.bucket(iterable, key=lambda x: 10 * (x // 10)) # In-order access self.assertEqual(list(D[10]), [10, 11, 12]) # Out of order access self.assertEqual(list(D[30]), [30, 31, 33]) self.assertEqual(list(D[20]), [20, 21, 22, 23]) self.assertEqual(list(D[40]), []) # Nothing in here! def test_in(self): iterable = [10, 20, 30, 11, 21, 31, 12, 22, 23, 33] D = mi.bucket(iterable, key=lambda x: 10 * (x // 10)) self.assertIn(10, D) self.assertNotIn(40, D) self.assertIn(20, D) self.assertNotIn(21, D) # Checking in-ness shouldn't advance the iterator self.assertEqual(next(D[10]), 10) def test_validator(self): iterable = count(0) key = lambda x: int(str(x)[0]) # First digit of each number validator = lambda x: 0 < x < 10 # No leading zeros D = mi.bucket(iterable, key, validator=validator) self.assertEqual(mi.take(3, D[1]), [1, 10, 11]) self.assertNotIn(0, D) # Non-valid entries don't return True self.assertNotIn(0, D._cache) # Don't store non-valid entries self.assertEqual(list(D[0]), []) def test_list(self): iterable = [10, 20, 30, 11, 21, 31, 12, 22, 23, 33] D = mi.bucket(iterable, key=lambda x: 10 * (x // 10)) self.assertEqual(list(D[10]), [10, 11, 12]) self.assertEqual(list(D[20]), [20, 21, 22, 23]) self.assertEqual(list(D[30]), [30, 31, 33]) self.assertEqual(set(D), {10, 20, 30}) def test_list_validator(self): iterable = [10, 20, 30, 11, 21, 31, 12, 22, 23, 33] key = lambda x: 10 * (x // 10) validator = lambda x: x != 20 D = mi.bucket(iterable, key, validator=validator) self.assertEqual(set(D), {10, 30}) self.assertEqual(list(D[10]), [10, 11, 12]) self.assertEqual(list(D[20]), []) self.assertEqual(list(D[30]), [30, 31, 33]) class SpyTests(TestCase): """Tests for ``spy()``""" def test_basic(self): original_iterable = iter('abcdefg') head, new_iterable = mi.spy(original_iterable) self.assertEqual(head, ['a']) self.assertEqual( list(new_iterable), ['a', 'b', 'c', 'd', 'e', 'f', 'g'] ) def test_unpacking(self): original_iterable = iter('abcdefg') (first, second, third), new_iterable = mi.spy(original_iterable, 3) self.assertEqual(first, 'a') self.assertEqual(second, 'b') self.assertEqual(third, 'c') self.assertEqual( list(new_iterable), ['a', 'b', 'c', 'd', 'e', 'f', 'g'] ) def test_too_many(self): original_iterable = iter('abc') head, new_iterable = mi.spy(original_iterable, 4) self.assertEqual(head, ['a', 'b', 'c']) self.assertEqual(list(new_iterable), ['a', 'b', 'c']) def test_zero(self): original_iterable = iter('abc') head, new_iterable = mi.spy(original_iterable, 0) self.assertEqual(head, []) self.assertEqual(list(new_iterable), ['a', 'b', 'c']) def test_immutable(self): original_iterable = iter('abcdefg') head, new_iterable = mi.spy(original_iterable, 3) head[0] = 'A' self.assertEqual(head, ['A', 'b', 'c']) self.assertEqual( list(new_iterable), ['a', 'b', 'c', 'd', 'e', 'f', 'g'] ) class InterleaveTests(TestCase): def test_even(self): actual = list(mi.interleave([1, 4, 7], [2, 5, 8], [3, 6, 9])) expected = [1, 2, 3, 4, 5, 6, 7, 8, 9] self.assertEqual(actual, expected) def test_short(self): actual = list(mi.interleave([1, 4], [2, 5, 7], [3, 6, 8])) expected = [1, 2, 3, 4, 5, 6] self.assertEqual(actual, expected) def test_mixed_types(self): it_list = ['a', 'b', 'c', 'd'] it_str = '12345' it_inf = count() actual = list(mi.interleave(it_list, it_str, it_inf)) expected = ['a', '1', 0, 'b', '2', 1, 'c', '3', 2, 'd', '4', 3] self.assertEqual(actual, expected) class InterleaveLongestTests(TestCase): def test_even(self): actual = list(mi.interleave_longest([1, 4, 7], [2, 5, 8], [3, 6, 9])) expected = [1, 2, 3, 4, 5, 6, 7, 8, 9] self.assertEqual(actual, expected) def test_short(self): actual = list(mi.interleave_longest([1, 4], [2, 5, 7], [3, 6, 8])) expected = [1, 2, 3, 4, 5, 6, 7, 8] self.assertEqual(actual, expected) def test_mixed_types(self): it_list = ['a', 'b', 'c', 'd'] it_str = '12345' it_gen = (x for x in range(3)) actual = list(mi.interleave_longest(it_list, it_str, it_gen)) expected = ['a', '1', 0, 'b', '2', 1, 'c', '3', 2, 'd', '4', '5'] self.assertEqual(actual, expected) class InterleaveEvenlyTests(TestCase): def test_equal_lengths(self): # when lengths are equal, the relative order shouldn't change a = [1, 2, 3] b = [5, 6, 7] actual = list(mi.interleave_evenly([a, b])) expected = [1, 5, 2, 6, 3, 7] self.assertEqual(actual, expected) def test_proportional(self): # easy case where the iterables have proportional length a = [1, 2, 3, 4] b = [5, 6] actual = list(mi.interleave_evenly([a, b])) expected = [1, 2, 5, 3, 4, 6] self.assertEqual(actual, expected) # swapping a and b should yield the same result actual_swapped = list(mi.interleave_evenly([b, a])) self.assertEqual(actual_swapped, expected) def test_not_proportional(self): a = [1, 2, 3, 4, 5, 6, 7] b = [8, 9, 10] expected = [1, 2, 8, 3, 4, 9, 5, 6, 10, 7] actual = list(mi.interleave_evenly([a, b])) self.assertEqual(actual, expected) def test_degenerate_one(self): a = [0, 1, 2, 3, 4] b = [5] expected = [0, 1, 2, 5, 3, 4] actual = list(mi.interleave_evenly([a, b])) self.assertEqual(actual, expected) def test_degenerate_empty(self): a = [1, 2, 3] b = [] expected = [1, 2, 3] actual = list(mi.interleave_evenly([a, b])) self.assertEqual(actual, expected) def test_three_iters(self): a = ["a1", "a2", "a3", "a4", "a5"] b = ["b1", "b2", "b3"] c = ["c1"] actual = list(mi.interleave_evenly([a, b, c])) expected = ["a1", "b1", "a2", "c1", "a3", "b2", "a4", "b3", "a5"] self.assertEqual(actual, expected) def test_many_iters(self): # smoke test with many iterables: create iterables with a random # number of elements starting with a character ("a0", "a1", ...) rng = Random(0) iterables = [] for ch in ascii_letters: length = rng.randint(0, 100) iterable = [f"{ch}{i}" for i in range(length)] iterables.append(iterable) interleaved = list(mi.interleave_evenly(iterables)) # for each iterable, check that the result contains all its items for iterable, ch_expect in zip(iterables, ascii_letters): interleaved_actual = [ e for e in interleaved if e.startswith(ch_expect) ] assert len(set(interleaved_actual)) == len(iterable) def test_manual_lengths(self): a = combinations(range(4), 2) len_a = 4 * (4 - 1) // 2 # == 6 b = combinations(range(4), 3) len_b = 4 expected = [ (0, 1), (0, 1, 2), (0, 2), (0, 3), (0, 1, 3), (1, 2), (0, 2, 3), (1, 3), (2, 3), (1, 2, 3), ] actual = list(mi.interleave_evenly([a, b], lengths=[len_a, len_b])) self.assertEqual(expected, actual) def test_no_length_raises(self): # combinations doesn't have __len__, should trigger ValueError iterables = [range(5), combinations(range(5), 2)] with self.assertRaises(ValueError): list(mi.interleave_evenly(iterables)) def test_argument_mismatch_raises(self): # pass mismatching number of iterables and lengths iterables = [range(3)] lengths = [3, 4] with self.assertRaises(ValueError): list(mi.interleave_evenly(iterables, lengths=lengths)) class TestCollapse(TestCase): """Tests for ``collapse()``""" def test_collapse(self): l = [[1], 2, [[3], 4], [[[5]]]] self.assertEqual(list(mi.collapse(l)), [1, 2, 3, 4, 5]) def test_collapse_to_string(self): l = [["s1"], "s2", [["s3"], "s4"], [[["s5"]]]] self.assertEqual(list(mi.collapse(l)), ["s1", "s2", "s3", "s4", "s5"]) def test_collapse_to_bytes(self): l = [[b"s1"], b"s2", [[b"s3"], b"s4"], [[[b"s5"]]]] self.assertEqual( list(mi.collapse(l)), [b"s1", b"s2", b"s3", b"s4", b"s5"] ) def test_collapse_flatten(self): l = [[1], [2], [[3], 4], [[[5]]]] self.assertEqual(list(mi.collapse(l, levels=1)), list(mi.flatten(l))) def test_collapse_to_level(self): l = [[1], 2, [[3], 4], [[[5]]]] self.assertEqual(list(mi.collapse(l, levels=2)), [1, 2, 3, 4, [5]]) self.assertEqual( list(mi.collapse(mi.collapse(l, levels=1), levels=1)), list(mi.collapse(l, levels=2)), ) def test_collapse_to_list(self): l = (1, [2], (3, [4, (5,)], 'ab')) actual = list(mi.collapse(l, base_type=list)) expected = [1, [2], 3, [4, (5,)], 'ab'] self.assertEqual(actual, expected) class SideEffectTests(TestCase): """Tests for ``side_effect()``""" def test_individual(self): # The function increments the counter for each call counter = [0] def func(arg): counter[0] += 1 result = list(mi.side_effect(func, range(10))) self.assertEqual(result, list(range(10))) self.assertEqual(counter[0], 10) def test_chunked(self): # The function increments the counter for each call counter = [0] def func(arg): counter[0] += 1 result = list(mi.side_effect(func, range(10), 2)) self.assertEqual(result, list(range(10))) self.assertEqual(counter[0], 5) def test_before_after(self): f = StringIO() collector = [] def func(item): print(item, file=f) collector.append(f.getvalue()) def it(): yield 'a' yield 'b' raise RuntimeError('kaboom') before = lambda: print('HEADER', file=f) after = f.close try: mi.consume(mi.side_effect(func, it(), before=before, after=after)) except RuntimeError: pass # The iterable should have been written to the file self.assertEqual(collector, ['HEADER\na\n', 'HEADER\na\nb\n']) # The file should be closed even though something bad happened self.assertTrue(f.closed) def test_before_fails(self): f = StringIO() func = lambda x: print(x, file=f) def before(): raise RuntimeError('ouch') try: mi.consume( mi.side_effect(func, 'abc', before=before, after=f.close) ) except RuntimeError: pass # The file should be closed even though something bad happened in the # before function self.assertTrue(f.closed) class SlicedTests(TestCase): """Tests for ``sliced()``""" def test_even(self): """Test when the length of the sequence is divisible by *n*""" seq = 'ABCDEFGHI' self.assertEqual(list(mi.sliced(seq, 3)), ['ABC', 'DEF', 'GHI']) def test_odd(self): """Test when the length of the sequence is not divisible by *n*""" seq = 'ABCDEFGHI' self.assertEqual(list(mi.sliced(seq, 4)), ['ABCD', 'EFGH', 'I']) def test_not_sliceable(self): seq = (x for x in 'ABCDEFGHI') with self.assertRaises(TypeError): list(mi.sliced(seq, 3)) def test_odd_and_strict(self): seq = [x for x in 'ABCDEFGHI'] with self.assertRaises(ValueError): list(mi.sliced(seq, 4, strict=True)) def test_numpy_like_array(self): # Numpy arrays don't behave like Python lists - calling bool() # on them doesn't return False for empty lists and True for non-empty # ones. Emulate that behavior. class FalseList(list): def __getitem__(self, key): ret = super().__getitem__(key) if isinstance(key, slice): return FalseList(ret) return ret def __bool__(self): return False seq = FalseList(range(9)) actual = list(mi.sliced(seq, 3)) expected = [[0, 1, 2], [3, 4, 5], [6, 7, 8]] self.assertEqual(actual, expected) class SplitAtTests(TestCase): def test_basic(self): for iterable, separator in [ ('a,bb,ccc,dddd', ','), (',a,bb,ccc,dddd', ','), ('a,bb,ccc,dddd,', ','), ('a,bb,ccc,,dddd', ','), ('', ','), (',', ','), ('a,bb,ccc,dddd', ';'), ]: with self.subTest(iterable=iterable, separator=separator): it = iter(iterable) pred = lambda x: x == separator actual = [''.join(x) for x in mi.split_at(it, pred)] expected = iterable.split(separator) self.assertEqual(actual, expected) def test_maxsplit(self): iterable = 'a,bb,ccc,dddd' separator = ',' pred = lambda x: x == separator for maxsplit in range(-1, 4): with self.subTest(maxsplit=maxsplit): it = iter(iterable) result = mi.split_at(it, pred, maxsplit=maxsplit) actual = [''.join(x) for x in result] expected = iterable.split(separator, maxsplit) self.assertEqual(actual, expected) def test_keep_separator(self): separator = ',' pred = lambda x: x == separator for iterable, expected in [ ('a,bb,ccc', ['a', ',', 'bb', ',', 'ccc']), (',a,bb,ccc', ['', ',', 'a', ',', 'bb', ',', 'ccc']), ('a,bb,ccc,', ['a', ',', 'bb', ',', 'ccc', ',', '']), ]: with self.subTest(iterable=iterable): it = iter(iterable) result = mi.split_at(it, pred, keep_separator=True) actual = [''.join(x) for x in result] self.assertEqual(actual, expected) def test_combination(self): iterable = [1, 2, 3, 4, 5, 6, 7, 8, 9, 10] pred = lambda x: x % 3 == 0 actual = list( mi.split_at(iterable, pred, maxsplit=2, keep_separator=True) ) expected = [[1, 2], [3], [4, 5], [6], [7, 8, 9, 10]] self.assertEqual(actual, expected) class SplitBeforeTest(TestCase): """Tests for ``split_before()``""" def test_starts_with_sep(self): actual = list(mi.split_before('xooxoo', lambda c: c == 'x')) expected = [['x', 'o', 'o'], ['x', 'o', 'o']] self.assertEqual(actual, expected) def test_ends_with_sep(self): actual = list(mi.split_before('ooxoox', lambda c: c == 'x')) expected = [['o', 'o'], ['x', 'o', 'o'], ['x']] self.assertEqual(actual, expected) def test_no_sep(self): actual = list(mi.split_before('ooo', lambda c: c == 'x')) expected = [['o', 'o', 'o']] self.assertEqual(actual, expected) def test_empty_collection(self): actual = list(mi.split_before([], lambda c: bool(c))) expected = [] self.assertEqual(actual, expected) def test_max_split(self): for args, expected in [ ( ('a,b,c,d', lambda c: c == ',', -1), [['a'], [',', 'b'], [',', 'c'], [',', 'd']], ), ( ('a,b,c,d', lambda c: c == ',', 0), [['a', ',', 'b', ',', 'c', ',', 'd']], ), ( ('a,b,c,d', lambda c: c == ',', 1), [['a'], [',', 'b', ',', 'c', ',', 'd']], ), ( ('a,b,c,d', lambda c: c == ',', 2), [['a'], [',', 'b'], [',', 'c', ',', 'd']], ), ( ('a,b,c,d', lambda c: c == ',', 10), [['a'], [',', 'b'], [',', 'c'], [',', 'd']], ), ( ('a,b,c,d', lambda c: c == '@', 2), [['a', ',', 'b', ',', 'c', ',', 'd']], ), ( ('a,b,c,d', lambda c: c != ',', 2), [['a', ','], ['b', ','], ['c', ',', 'd']], ), ]: actual = list(mi.split_before(*args)) self.assertEqual(actual, expected) class SplitAfterTest(TestCase): """Tests for ``split_after()``""" def test_starts_with_sep(self): actual = list(mi.split_after('xooxoo', lambda c: c == 'x')) expected = [['x'], ['o', 'o', 'x'], ['o', 'o']] self.assertEqual(actual, expected) def test_ends_with_sep(self): actual = list(mi.split_after('ooxoox', lambda c: c == 'x')) expected = [['o', 'o', 'x'], ['o', 'o', 'x']] self.assertEqual(actual, expected) def test_no_sep(self): actual = list(mi.split_after('ooo', lambda c: c == 'x')) expected = [['o', 'o', 'o']] self.assertEqual(actual, expected) def test_max_split(self): for args, expected in [ ( ('a,b,c,d', lambda c: c == ',', -1), [['a', ','], ['b', ','], ['c', ','], ['d']], ), ( ('a,b,c,d', lambda c: c == ',', 0), [['a', ',', 'b', ',', 'c', ',', 'd']], ), ( ('a,b,c,d', lambda c: c == ',', 1), [['a', ','], ['b', ',', 'c', ',', 'd']], ), ( ('a,b,c,d', lambda c: c == ',', 2), [['a', ','], ['b', ','], ['c', ',', 'd']], ), ( ('a,b,c,d', lambda c: c == ',', 10), [['a', ','], ['b', ','], ['c', ','], ['d']], ), ( ('a,b,c,d', lambda c: c == '@', 2), [['a', ',', 'b', ',', 'c', ',', 'd']], ), ( ('a,b,c,d', lambda c: c != ',', 2), [['a'], [',', 'b'], [',', 'c', ',', 'd']], ), ]: actual = list(mi.split_after(*args)) self.assertEqual(actual, expected) class SplitWhenTests(TestCase): """Tests for ``split_when()``""" @staticmethod def _split_when_before(iterable, pred): return mi.split_when(iterable, lambda _, c: pred(c)) @staticmethod def _split_when_after(iterable, pred): return mi.split_when(iterable, lambda c, _: pred(c)) # split_before emulation def test_before_emulation_starts_with_sep(self): actual = list(self._split_when_before('xooxoo', lambda c: c == 'x')) expected = [['x', 'o', 'o'], ['x', 'o', 'o']] self.assertEqual(actual, expected) def test_before_emulation_ends_with_sep(self): actual = list(self._split_when_before('ooxoox', lambda c: c == 'x')) expected = [['o', 'o'], ['x', 'o', 'o'], ['x']] self.assertEqual(actual, expected) def test_before_emulation_no_sep(self): actual = list(self._split_when_before('ooo', lambda c: c == 'x')) expected = [['o', 'o', 'o']] self.assertEqual(actual, expected) # split_after emulation def test_after_emulation_starts_with_sep(self): actual = list(self._split_when_after('xooxoo', lambda c: c == 'x')) expected = [['x'], ['o', 'o', 'x'], ['o', 'o']] self.assertEqual(actual, expected) def test_after_emulation_ends_with_sep(self): actual = list(self._split_when_after('ooxoox', lambda c: c == 'x')) expected = [['o', 'o', 'x'], ['o', 'o', 'x']] self.assertEqual(actual, expected) def test_after_emulation_no_sep(self): actual = list(self._split_when_after('ooo', lambda c: c == 'x')) expected = [['o', 'o', 'o']] self.assertEqual(actual, expected) # edge cases def test_empty_iterable(self): actual = list(mi.split_when('', lambda a, b: a != b)) expected = [] self.assertEqual(actual, expected) def test_one_element(self): actual = list(mi.split_when('o', lambda a, b: a == b)) expected = [['o']] self.assertEqual(actual, expected) def test_one_element_is_second_item(self): actual = list(self._split_when_before('x', lambda c: c == 'x')) expected = [['x']] self.assertEqual(actual, expected) def test_one_element_is_first_item(self): actual = list(self._split_when_after('x', lambda c: c == 'x')) expected = [['x']] self.assertEqual(actual, expected) def test_max_split(self): for args, expected in [ ( ('a,b,c,d', lambda a, _: a == ',', -1), [['a', ','], ['b', ','], ['c', ','], ['d']], ), ( ('a,b,c,d', lambda a, _: a == ',', 0), [['a', ',', 'b', ',', 'c', ',', 'd']], ), ( ('a,b,c,d', lambda _, b: b == ',', 1), [['a'], [',', 'b', ',', 'c', ',', 'd']], ), ( ('a,b,c,d', lambda a, _: a == ',', 2), [['a', ','], ['b', ','], ['c', ',', 'd']], ), ( ('0124376', lambda a, b: a > b, -1), [['0', '1', '2', '4'], ['3', '7'], ['6']], ), ( ('0124376', lambda a, b: a > b, 0), [['0', '1', '2', '4', '3', '7', '6']], ), ( ('0124376', lambda a, b: a > b, 1), [['0', '1', '2', '4'], ['3', '7', '6']], ), ( ('0124376', lambda a, b: a > b, 2), [['0', '1', '2', '4'], ['3', '7'], ['6']], ), ]: actual = list(mi.split_when(*args)) self.assertEqual(actual, expected, str(args)) class SplitIntoTests(TestCase): """Tests for ``split_into()``""" def test_iterable_just_right(self): """Size of ``iterable`` equals the sum of ``sizes``.""" iterable = [1, 2, 3, 4, 5, 6, 7, 8, 9] sizes = [2, 3, 4] expected = [[1, 2], [3, 4, 5], [6, 7, 8, 9]] actual = list(mi.split_into(iterable, sizes)) self.assertEqual(actual, expected) def test_iterable_too_small(self): """Size of ``iterable`` is smaller than sum of ``sizes``. Last return list is shorter as a result.""" iterable = [1, 2, 3, 4, 5, 6, 7] sizes = [2, 3, 4] expected = [[1, 2], [3, 4, 5], [6, 7]] actual = list(mi.split_into(iterable, sizes)) self.assertEqual(actual, expected) def test_iterable_too_small_extra(self): """Size of ``iterable`` is smaller than sum of ``sizes``. Second last return list is shorter and last return list is empty as a result.""" iterable = [1, 2, 3, 4, 5, 6, 7] sizes = [2, 3, 4, 5] expected = [[1, 2], [3, 4, 5], [6, 7], []] actual = list(mi.split_into(iterable, sizes)) self.assertEqual(actual, expected) def test_iterable_too_large(self): """Size of ``iterable`` is larger than sum of ``sizes``. Not all items of iterable are returned.""" iterable = [1, 2, 3, 4, 5, 6, 7, 8, 9] sizes = [2, 3, 2] expected = [[1, 2], [3, 4, 5], [6, 7]] actual = list(mi.split_into(iterable, sizes)) self.assertEqual(actual, expected) def test_using_none_with_leftover(self): """Last item of ``sizes`` is None when items still remain in ``iterable``. Last list returned stretches to fit all remaining items of ``iterable``.""" iterable = [1, 2, 3, 4, 5, 6, 7, 8, 9] sizes = [2, 3, None] expected = [[1, 2], [3, 4, 5], [6, 7, 8, 9]] actual = list(mi.split_into(iterable, sizes)) self.assertEqual(actual, expected) def test_using_none_without_leftover(self): """Last item of ``sizes`` is None when no items remain in ``iterable``. Last list returned is empty.""" iterable = [1, 2, 3, 4, 5, 6, 7, 8, 9] sizes = [2, 3, 4, None] expected = [[1, 2], [3, 4, 5], [6, 7, 8, 9], []] actual = list(mi.split_into(iterable, sizes)) self.assertEqual(actual, expected) def test_using_none_mid_sizes(self): """None is present in ``sizes`` but is not the last item. Last list returned stretches to fit all remaining items of ``iterable`` but all items in ``sizes`` after None are ignored.""" iterable = [1, 2, 3, 4, 5, 6, 7, 8, 9] sizes = [2, 3, None, 4] expected = [[1, 2], [3, 4, 5], [6, 7, 8, 9]] actual = list(mi.split_into(iterable, sizes)) self.assertEqual(actual, expected) def test_iterable_empty(self): """``iterable`` argument is empty but ``sizes`` is not. An empty list is returned for each item in ``sizes``.""" iterable = [] sizes = [2, 4, 2] expected = [[], [], []] actual = list(mi.split_into(iterable, sizes)) self.assertEqual(actual, expected) def test_iterable_empty_using_none(self): """``iterable`` argument is empty but ``sizes`` is not. An empty list is returned for each item in ``sizes`` that is not after a None item.""" iterable = [] sizes = [2, 4, None, 2] expected = [[], [], []] actual = list(mi.split_into(iterable, sizes)) self.assertEqual(actual, expected) def test_sizes_empty(self): """``sizes`` argument is empty but ``iterable`` is not. An empty generator is returned.""" iterable = [1, 2, 3, 4, 5, 6, 7, 8, 9] sizes = [] expected = [] actual = list(mi.split_into(iterable, sizes)) self.assertEqual(actual, expected) def test_both_empty(self): """Both ``sizes`` and ``iterable`` arguments are empty. An empty generator is returned.""" iterable = [] sizes = [] expected = [] actual = list(mi.split_into(iterable, sizes)) self.assertEqual(actual, expected) def test_bool_in_sizes(self): """A bool object is present in ``sizes`` is treated as a 1 or 0 for ``True`` or ``False`` due to bool being an instance of int.""" iterable = [1, 2, 3, 4, 5, 6, 7, 8, 9] sizes = [3, True, 2, False] expected = [[1, 2, 3], [4], [5, 6], []] actual = list(mi.split_into(iterable, sizes)) self.assertEqual(actual, expected) def test_invalid_in_sizes(self): """A ValueError is raised if an object in ``sizes`` is neither ``None`` or an integer.""" iterable = [1, 2, 3, 4, 5, 6, 7, 8, 9] sizes = [1, [], 3] with self.assertRaises(ValueError): list(mi.split_into(iterable, sizes)) def test_invalid_in_sizes_after_none(self): """A item in ``sizes`` that is invalid will not raise a TypeError if it comes after a ``None`` item.""" iterable = [1, 2, 3, 4, 5, 6, 7, 8, 9] sizes = [3, 4, None, []] expected = [[1, 2, 3], [4, 5, 6, 7], [8, 9]] actual = list(mi.split_into(iterable, sizes)) self.assertEqual(actual, expected) def test_generator_iterable_integrity(self): """Check that if ``iterable`` is an iterator, it is consumed only by as many items as the sum of ``sizes``.""" iterable = (i for i in range(10)) sizes = [2, 3] expected = [[0, 1], [2, 3, 4]] actual = list(mi.split_into(iterable, sizes)) self.assertEqual(actual, expected) iterable_expected = [5, 6, 7, 8, 9] iterable_actual = list(iterable) self.assertEqual(iterable_actual, iterable_expected) def test_generator_sizes_integrity(self): """Check that if ``sizes`` is an iterator, it is consumed only until a ``None`` item is reached""" iterable = [1, 2, 3, 4, 5, 6, 7, 8, 9] sizes = (i for i in [1, 2, None, 3, 4]) expected = [[1], [2, 3], [4, 5, 6, 7, 8, 9]] actual = list(mi.split_into(iterable, sizes)) self.assertEqual(actual, expected) sizes_expected = [3, 4] sizes_actual = list(sizes) self.assertEqual(sizes_actual, sizes_expected) class PaddedTest(TestCase): """Tests for ``padded()``""" def test_no_n(self): seq = [1, 2, 3] # No fillvalue self.assertEqual(mi.take(5, mi.padded(seq)), [1, 2, 3, None, None]) # With fillvalue self.assertEqual( mi.take(5, mi.padded(seq, fillvalue='')), [1, 2, 3, '', ''] ) def test_invalid_n(self): self.assertRaises(ValueError, lambda: list(mi.padded([1, 2, 3], n=-1))) self.assertRaises(ValueError, lambda: list(mi.padded([1, 2, 3], n=0))) def test_valid_n(self): seq = [1, 2, 3, 4, 5] # No need for padding: len(seq) <= n self.assertEqual(list(mi.padded(seq, n=4)), [1, 2, 3, 4, 5]) self.assertEqual(list(mi.padded(seq, n=5)), [1, 2, 3, 4, 5]) # No fillvalue self.assertEqual( list(mi.padded(seq, n=7)), [1, 2, 3, 4, 5, None, None] ) # With fillvalue self.assertEqual( list(mi.padded(seq, fillvalue='', n=7)), [1, 2, 3, 4, 5, '', ''] ) def test_next_multiple(self): seq = [1, 2, 3, 4, 5, 6] # No need for padding: len(seq) % n == 0 self.assertEqual( list(mi.padded(seq, n=3, next_multiple=True)), [1, 2, 3, 4, 5, 6] ) # Padding needed: len(seq) < n self.assertEqual( list(mi.padded(seq, n=8, next_multiple=True)), [1, 2, 3, 4, 5, 6, None, None], ) # No padding needed: len(seq) == n self.assertEqual( list(mi.padded(seq, n=6, next_multiple=True)), [1, 2, 3, 4, 5, 6] ) # Padding needed: len(seq) > n self.assertEqual( list(mi.padded(seq, n=4, next_multiple=True)), [1, 2, 3, 4, 5, 6, None, None], ) # With fillvalue self.assertEqual( list(mi.padded(seq, fillvalue='', n=4, next_multiple=True)), [1, 2, 3, 4, 5, 6, '', ''], ) class RepeatEachTests(TestCase): """Tests for repeat_each()""" def test_default(self): actual = list(mi.repeat_each('ABC')) expected = ['A', 'A', 'B', 'B', 'C', 'C'] self.assertEqual(actual, expected) def test_basic(self): actual = list(mi.repeat_each('ABC', 3)) expected = ['A', 'A', 'A', 'B', 'B', 'B', 'C', 'C', 'C'] self.assertEqual(actual, expected) def test_empty(self): actual = list(mi.repeat_each('')) expected = [] self.assertEqual(actual, expected) def test_no_repeat(self): actual = list(mi.repeat_each('ABC', 0)) expected = [] self.assertEqual(actual, expected) def test_negative_repeat(self): actual = list(mi.repeat_each('ABC', -1)) expected = [] self.assertEqual(actual, expected) def test_infinite_input(self): repeater = mi.repeat_each(cycle('AB')) actual = mi.take(6, repeater) expected = ['A', 'A', 'B', 'B', 'A', 'A'] self.assertEqual(actual, expected) class RepeatLastTests(TestCase): def test_empty_iterable(self): slice_length = 3 iterable = iter([]) actual = mi.take(slice_length, mi.repeat_last(iterable)) expected = [None] * slice_length self.assertEqual(actual, expected) def test_default_value(self): slice_length = 3 iterable = iter([]) default = '3' actual = mi.take(slice_length, mi.repeat_last(iterable, default)) expected = ['3'] * slice_length self.assertEqual(actual, expected) def test_basic(self): slice_length = 10 iterable = (str(x) for x in range(5)) actual = mi.take(slice_length, mi.repeat_last(iterable)) expected = ['0', '1', '2', '3', '4', '4', '4', '4', '4', '4'] self.assertEqual(actual, expected) class DistributeTest(TestCase): """Tests for distribute()""" def test_invalid_n(self): self.assertRaises(ValueError, lambda: mi.distribute(-1, [1, 2, 3])) self.assertRaises(ValueError, lambda: mi.distribute(0, [1, 2, 3])) def test_basic(self): iterable = [1, 2, 3, 4, 5, 6, 7, 8, 9, 10] for n, expected in [ (1, [iterable]), (2, [[1, 3, 5, 7, 9], [2, 4, 6, 8, 10]]), (3, [[1, 4, 7, 10], [2, 5, 8], [3, 6, 9]]), (10, [[n] for n in range(1, 10 + 1)]), ]: self.assertEqual( [list(x) for x in mi.distribute(n, iterable)], expected ) def test_large_n(self): iterable = [1, 2, 3, 4] self.assertEqual( [list(x) for x in mi.distribute(6, iterable)], [[1], [2], [3], [4], [], []], ) class StaggerTest(TestCase): """Tests for ``stagger()``""" def test_default(self): iterable = [0, 1, 2, 3] actual = list(mi.stagger(iterable)) expected = [(None, 0, 1), (0, 1, 2), (1, 2, 3)] self.assertEqual(actual, expected) def test_offsets(self): iterable = [0, 1, 2, 3] for offsets, expected in [ ((-2, 0, 2), [('', 0, 2), ('', 1, 3)]), ((-2, -1), [('', ''), ('', 0), (0, 1), (1, 2), (2, 3)]), ((1, 2), [(1, 2), (2, 3)]), ]: all_groups = mi.stagger(iterable, offsets=offsets, fillvalue='') self.assertEqual(list(all_groups), expected) def test_longest(self): iterable = [0, 1, 2, 3] for offsets, expected in [ ( (-1, 0, 1), [('', 0, 1), (0, 1, 2), (1, 2, 3), (2, 3, ''), (3, '', '')], ), ((-2, -1), [('', ''), ('', 0), (0, 1), (1, 2), (2, 3), (3, '')]), ((1, 2), [(1, 2), (2, 3), (3, '')]), ]: all_groups = mi.stagger( iterable, offsets=offsets, fillvalue='', longest=True ) self.assertEqual(list(all_groups), expected) class ZipEqualTest(TestCase): @skipIf(version_info[:2] < (3, 10), 'zip_equal deprecated for 3.10+') def test_deprecation(self): with warnings.catch_warnings(record=True) as caught: warnings.simplefilter('always') self.assertEqual( list(mi.zip_equal([1, 2], [3, 4])), [(1, 3), (2, 4)] ) (warning,) = caught assert warning.category == DeprecationWarning def test_equal(self): lists = [0, 1, 2], [2, 3, 4] for iterables in [lists, map(iter, lists)]: actual = list(mi.zip_equal(*iterables)) expected = [(0, 2), (1, 3), (2, 4)] self.assertEqual(actual, expected) def test_unequal_lists(self): two_items = [0, 1] three_items = [2, 3, 4] four_items = [5, 6, 7, 8] # the mismatch is at index 1 try: list(mi.zip_equal(two_items, three_items, four_items)) except mi.UnequalIterablesError as e: self.assertEqual( e.args[0], ( 'Iterables have different lengths: ' 'index 0 has length 2; index 1 has length 3' ), ) # the mismatch is at index 2 try: list(mi.zip_equal(two_items, two_items, four_items, four_items)) except mi.UnequalIterablesError as e: self.assertEqual( e.args[0], ( 'Iterables have different lengths: ' 'index 0 has length 2; index 2 has length 4' ), ) # One without length: delegate to _zip_equal_generator try: list(mi.zip_equal(two_items, iter(two_items), three_items)) except mi.UnequalIterablesError as e: self.assertEqual(e.args[0], 'Iterables have different lengths') class ZipOffsetTest(TestCase): """Tests for ``zip_offset()``""" def test_shortest(self): a_1 = [0, 1, 2, 3] a_2 = [0, 1, 2, 3, 4, 5] a_3 = [0, 1, 2, 3, 4, 5, 6, 7] actual = list( mi.zip_offset(a_1, a_2, a_3, offsets=(-1, 0, 1), fillvalue='') ) expected = [('', 0, 1), (0, 1, 2), (1, 2, 3), (2, 3, 4), (3, 4, 5)] self.assertEqual(actual, expected) def test_longest(self): a_1 = [0, 1, 2, 3] a_2 = [0, 1, 2, 3, 4, 5] a_3 = [0, 1, 2, 3, 4, 5, 6, 7] actual = list( mi.zip_offset(a_1, a_2, a_3, offsets=(-1, 0, 1), longest=True) ) expected = [ (None, 0, 1), (0, 1, 2), (1, 2, 3), (2, 3, 4), (3, 4, 5), (None, 5, 6), (None, None, 7), ] self.assertEqual(actual, expected) def test_mismatch(self): iterables = [0, 1, 2], [2, 3, 4] offsets = (-1, 0, 1) self.assertRaises( ValueError, lambda: list(mi.zip_offset(*iterables, offsets=offsets)), ) class UnzipTests(TestCase): """Tests for unzip()""" def test_empty_iterable(self): self.assertEqual(list(mi.unzip([])), []) # in reality zip([], [], []) is equivalent to iter([]) # but it doesn't hurt to test both self.assertEqual(list(mi.unzip(zip([], [], []))), []) def test_length_one_iterable(self): xs, ys, zs = mi.unzip(zip([1], [2], [3])) self.assertEqual(list(xs), [1]) self.assertEqual(list(ys), [2]) self.assertEqual(list(zs), [3]) def test_normal_case(self): xs, ys, zs = range(10), range(1, 11), range(2, 12) zipped = zip(xs, ys, zs) xs, ys, zs = mi.unzip(zipped) self.assertEqual(list(xs), list(range(10))) self.assertEqual(list(ys), list(range(1, 11))) self.assertEqual(list(zs), list(range(2, 12))) def test_improperly_zipped(self): zipped = iter([(1, 2, 3), (4, 5), (6,)]) xs, ys, zs = mi.unzip(zipped) self.assertEqual(list(xs), [1, 4, 6]) self.assertEqual(list(ys), [2, 5]) self.assertEqual(list(zs), [3]) def test_increasingly_zipped(self): zipped = iter([(1, 2), (3, 4, 5), (6, 7, 8, 9)]) unzipped = mi.unzip(zipped) # from the docstring: # len(first tuple) is the number of iterables zipped self.assertEqual(len(unzipped), 2) xs, ys = unzipped self.assertEqual(list(xs), [1, 3, 6]) self.assertEqual(list(ys), [2, 4, 7]) class SortTogetherTest(TestCase): """Tests for sort_together()""" def test_key_list(self): """tests `key_list` including default, iterables include duplicates""" iterables = [ ['GA', 'GA', 'GA', 'CT', 'CT', 'CT'], ['May', 'Aug.', 'May', 'June', 'July', 'July'], [97, 20, 100, 70, 100, 20], ] self.assertEqual( mi.sort_together(iterables), [ ('CT', 'CT', 'CT', 'GA', 'GA', 'GA'), ('June', 'July', 'July', 'May', 'Aug.', 'May'), (70, 100, 20, 97, 20, 100), ], ) self.assertEqual( mi.sort_together(iterables, key_list=(0, 1)), [ ('CT', 'CT', 'CT', 'GA', 'GA', 'GA'), ('July', 'July', 'June', 'Aug.', 'May', 'May'), (100, 20, 70, 20, 97, 100), ], ) self.assertEqual( mi.sort_together(iterables, key_list=(0, 1, 2)), [ ('CT', 'CT', 'CT', 'GA', 'GA', 'GA'), ('July', 'July', 'June', 'Aug.', 'May', 'May'), (20, 100, 70, 20, 97, 100), ], ) self.assertEqual( mi.sort_together(iterables, key_list=(2,)), [ ('GA', 'CT', 'CT', 'GA', 'GA', 'CT'), ('Aug.', 'July', 'June', 'May', 'May', 'July'), (20, 20, 70, 97, 100, 100), ], ) def test_invalid_key_list(self): """tests `key_list` for indexes not available in `iterables`""" iterables = [ ['GA', 'GA', 'GA', 'CT', 'CT', 'CT'], ['May', 'Aug.', 'May', 'June', 'July', 'July'], [97, 20, 100, 70, 100, 20], ] self.assertRaises( IndexError, lambda: mi.sort_together(iterables, key_list=(5,)) ) def test_key_function(self): """tests `key` function, including interaction with `key_list`""" iterables = [ ['GA', 'GA', 'GA', 'CT', 'CT', 'CT'], ['May', 'Aug.', 'May', 'June', 'July', 'July'], [97, 20, 100, 70, 100, 20], ] self.assertEqual( mi.sort_together(iterables, key=lambda x: x), [ ('CT', 'CT', 'CT', 'GA', 'GA', 'GA'), ('June', 'July', 'July', 'May', 'Aug.', 'May'), (70, 100, 20, 97, 20, 100), ], ) self.assertEqual( mi.sort_together(iterables, key=lambda x: x[::-1]), [ ('GA', 'GA', 'GA', 'CT', 'CT', 'CT'), ('May', 'Aug.', 'May', 'June', 'July', 'July'), (97, 20, 100, 70, 100, 20), ], ) self.assertEqual( mi.sort_together( iterables, key_list=(0, 2), key=lambda state, number: number if state == 'CT' else 2 * number, ), [ ('CT', 'GA', 'CT', 'CT', 'GA', 'GA'), ('July', 'Aug.', 'June', 'July', 'May', 'May'), (20, 20, 70, 100, 97, 100), ], ) def test_reverse(self): """tests `reverse` to ensure a reverse sort for `key_list` iterables""" iterables = [ ['GA', 'GA', 'GA', 'CT', 'CT', 'CT'], ['May', 'Aug.', 'May', 'June', 'July', 'July'], [97, 20, 100, 70, 100, 20], ] self.assertEqual( mi.sort_together(iterables, key_list=(0, 1, 2), reverse=True), [ ('GA', 'GA', 'GA', 'CT', 'CT', 'CT'), ('May', 'May', 'Aug.', 'June', 'July', 'July'), (100, 97, 20, 70, 100, 20), ], ) def test_uneven_iterables(self): """tests trimming of iterables to the shortest length before sorting""" iterables = [ ['GA', 'GA', 'GA', 'CT', 'CT', 'CT', 'MA'], ['May', 'Aug.', 'May', 'June', 'July', 'July'], [97, 20, 100, 70, 100, 20, 0], ] self.assertEqual( mi.sort_together(iterables), [ ('CT', 'CT', 'CT', 'GA', 'GA', 'GA'), ('June', 'July', 'July', 'May', 'Aug.', 'May'), (70, 100, 20, 97, 20, 100), ], ) class DivideTest(TestCase): """Tests for divide()""" def test_invalid_n(self): self.assertRaises(ValueError, lambda: mi.divide(-1, [1, 2, 3])) self.assertRaises(ValueError, lambda: mi.divide(0, [1, 2, 3])) def test_basic(self): iterable = [1, 2, 3, 4, 5, 6, 7, 8, 9, 10] for n, expected in [ (1, [iterable]), (2, [[1, 2, 3, 4, 5], [6, 7, 8, 9, 10]]), (3, [[1, 2, 3, 4], [5, 6, 7], [8, 9, 10]]), (10, [[n] for n in range(1, 10 + 1)]), ]: self.assertEqual( [list(x) for x in mi.divide(n, iterable)], expected ) def test_large_n(self): self.assertEqual( [list(x) for x in mi.divide(6, iter(range(1, 4 + 1)))], [[1], [2], [3], [4], [], []], ) class TestAlwaysIterable(TestCase): """Tests for always_iterable()""" def test_single(self): self.assertEqual(list(mi.always_iterable(1)), [1]) def test_strings(self): for obj in ['foo', b'bar', 'baz']: actual = list(mi.always_iterable(obj)) expected = [obj] self.assertEqual(actual, expected) def test_base_type(self): dict_obj = {'a': 1, 'b': 2} str_obj = '123' # Default: dicts are iterable like they normally are default_actual = list(mi.always_iterable(dict_obj)) default_expected = list(dict_obj) self.assertEqual(default_actual, default_expected) # Unitary types set: dicts are not iterable custom_actual = list(mi.always_iterable(dict_obj, base_type=dict)) custom_expected = [dict_obj] self.assertEqual(custom_actual, custom_expected) # With unitary types set, strings are iterable str_actual = list(mi.always_iterable(str_obj, base_type=None)) str_expected = list(str_obj) self.assertEqual(str_actual, str_expected) # base_type handles nested tuple (via isinstance). base_type = ((dict,),) custom_actual = list(mi.always_iterable(dict_obj, base_type=base_type)) custom_expected = [dict_obj] self.assertEqual(custom_actual, custom_expected) def test_iterables(self): self.assertEqual(list(mi.always_iterable([0, 1])), [0, 1]) self.assertEqual( list(mi.always_iterable([0, 1], base_type=list)), [[0, 1]] ) self.assertEqual( list(mi.always_iterable(iter('foo'))), ['f', 'o', 'o'] ) self.assertEqual(list(mi.always_iterable([])), []) def test_none(self): self.assertEqual(list(mi.always_iterable(None)), []) def test_generator(self): def _gen(): yield 0 yield 1 self.assertEqual(list(mi.always_iterable(_gen())), [0, 1]) class AdjacentTests(TestCase): def test_typical(self): actual = list(mi.adjacent(lambda x: x % 5 == 0, range(10))) expected = [ (True, 0), (True, 1), (False, 2), (False, 3), (True, 4), (True, 5), (True, 6), (False, 7), (False, 8), (False, 9), ] self.assertEqual(actual, expected) def test_empty_iterable(self): actual = list(mi.adjacent(lambda x: x % 5 == 0, [])) expected = [] self.assertEqual(actual, expected) def test_length_one(self): actual = list(mi.adjacent(lambda x: x % 5 == 0, [0])) expected = [(True, 0)] self.assertEqual(actual, expected) actual = list(mi.adjacent(lambda x: x % 5 == 0, [1])) expected = [(False, 1)] self.assertEqual(actual, expected) def test_consecutive_true(self): """Test that when the predicate matches multiple consecutive elements it doesn't repeat elements in the output""" actual = list(mi.adjacent(lambda x: x % 5 < 2, range(10))) expected = [ (True, 0), (True, 1), (True, 2), (False, 3), (True, 4), (True, 5), (True, 6), (True, 7), (False, 8), (False, 9), ] self.assertEqual(actual, expected) def test_distance(self): actual = list(mi.adjacent(lambda x: x % 5 == 0, range(10), distance=2)) expected = [ (True, 0), (True, 1), (True, 2), (True, 3), (True, 4), (True, 5), (True, 6), (True, 7), (False, 8), (False, 9), ] self.assertEqual(actual, expected) actual = list(mi.adjacent(lambda x: x % 5 == 0, range(10), distance=3)) expected = [ (True, 0), (True, 1), (True, 2), (True, 3), (True, 4), (True, 5), (True, 6), (True, 7), (True, 8), (False, 9), ] self.assertEqual(actual, expected) def test_large_distance(self): """Test distance larger than the length of the iterable""" iterable = range(10) actual = list(mi.adjacent(lambda x: x % 5 == 4, iterable, distance=20)) expected = list(zip(repeat(True), iterable)) self.assertEqual(actual, expected) actual = list(mi.adjacent(lambda x: False, iterable, distance=20)) expected = list(zip(repeat(False), iterable)) self.assertEqual(actual, expected) def test_zero_distance(self): """Test that adjacent() reduces to zip+map when distance is 0""" iterable = range(1000) predicate = lambda x: x % 4 == 2 actual = mi.adjacent(predicate, iterable, 0) expected = zip(map(predicate, iterable), iterable) self.assertTrue(all(a == e for a, e in zip(actual, expected))) def test_negative_distance(self): """Test that adjacent() raises an error with negative distance""" pred = lambda x: x self.assertRaises( ValueError, lambda: mi.adjacent(pred, range(1000), -1) ) self.assertRaises( ValueError, lambda: mi.adjacent(pred, range(10), -10) ) def test_grouping(self): """Test interaction of adjacent() with groupby_transform()""" iterable = mi.adjacent(lambda x: x % 5 == 0, range(10)) grouper = mi.groupby_transform(iterable, itemgetter(0), itemgetter(1)) actual = [(k, list(g)) for k, g in grouper] expected = [ (True, [0, 1]), (False, [2, 3]), (True, [4, 5, 6]), (False, [7, 8, 9]), ] self.assertEqual(actual, expected) def test_call_once(self): """Test that the predicate is only called once per item.""" already_seen = set() iterable = range(10) def predicate(item): self.assertNotIn(item, already_seen) already_seen.add(item) return True actual = list(mi.adjacent(predicate, iterable)) expected = [(True, x) for x in iterable] self.assertEqual(actual, expected) class GroupByTransformTests(TestCase): def assertAllGroupsEqual(self, groupby1, groupby2): for a, b in zip(groupby1, groupby2): key1, group1 = a key2, group2 = b self.assertEqual(key1, key2) self.assertListEqual(list(group1), list(group2)) self.assertRaises(StopIteration, lambda: next(groupby1)) self.assertRaises(StopIteration, lambda: next(groupby2)) def test_default_funcs(self): iterable = [(x // 5, x) for x in range(1000)] actual = mi.groupby_transform(iterable) expected = groupby(iterable) self.assertAllGroupsEqual(actual, expected) def test_valuefunc(self): iterable = [(int(x / 5), int(x / 3), x) for x in range(10)] # Test the standard usage of grouping one iterable using another's keys grouper = mi.groupby_transform( iterable, keyfunc=itemgetter(0), valuefunc=itemgetter(-1) ) actual = [(k, list(g)) for k, g in grouper] expected = [(0, [0, 1, 2, 3, 4]), (1, [5, 6, 7, 8, 9])] self.assertEqual(actual, expected) grouper = mi.groupby_transform( iterable, keyfunc=itemgetter(1), valuefunc=itemgetter(-1) ) actual = [(k, list(g)) for k, g in grouper] expected = [(0, [0, 1, 2]), (1, [3, 4, 5]), (2, [6, 7, 8]), (3, [9])] self.assertEqual(actual, expected) # and now for something a little different d = dict(zip(range(10), 'abcdefghij')) grouper = mi.groupby_transform( range(10), keyfunc=lambda x: x // 5, valuefunc=d.get ) actual = [(k, ''.join(g)) for k, g in grouper] expected = [(0, 'abcde'), (1, 'fghij')] self.assertEqual(actual, expected) def test_no_valuefunc(self): iterable = range(1000) def key(x): return x // 5 actual = mi.groupby_transform(iterable, key, valuefunc=None) expected = groupby(iterable, key) self.assertAllGroupsEqual(actual, expected) actual = mi.groupby_transform(iterable, key) # default valuefunc expected = groupby(iterable, key) self.assertAllGroupsEqual(actual, expected) def test_reducefunc(self): iterable = range(50) keyfunc = lambda k: 10 * (k // 10) valuefunc = lambda v: v + 1 reducefunc = sum actual = list( mi.groupby_transform( iterable, keyfunc=keyfunc, valuefunc=valuefunc, reducefunc=reducefunc, ) ) expected = [(0, 55), (10, 155), (20, 255), (30, 355), (40, 455)] self.assertEqual(actual, expected) class NumericRangeTests(TestCase): def test_basic(self): for args, expected in [ ((4,), [0, 1, 2, 3]), ((4.0,), [0.0, 1.0, 2.0, 3.0]), ((1.0, 4), [1.0, 2.0, 3.0]), ((1, 4.0), [1.0, 2.0, 3.0]), ((1.0, 5), [1.0, 2.0, 3.0, 4.0]), ((0, 20, 5), [0, 5, 10, 15]), ((0, 20, 5.0), [0.0, 5.0, 10.0, 15.0]), ((0, 10, 3), [0, 3, 6, 9]), ((0, 10, 3.0), [0.0, 3.0, 6.0, 9.0]), ((0, -5, -1), [0, -1, -2, -3, -4]), ((0.0, -5, -1), [0.0, -1.0, -2.0, -3.0, -4.0]), ((1, 2, Fraction(1, 2)), [Fraction(1, 1), Fraction(3, 2)]), ((0,), []), ((0.0,), []), ((1, 0), []), ((1.0, 0.0), []), ((0.1, 0.30000000000000001, 0.2), [0.1]), # IEE 754 ! ( ( Decimal("0.1"), Decimal("0.30000000000000001"), Decimal("0.2"), ), [Decimal("0.1"), Decimal("0.3")], ), # okay with Decimal ( ( Fraction(1, 10), Fraction(30000000000000001, 100000000000000000), Fraction(2, 10), ), [Fraction(1, 10), Fraction(3, 10)], ), # okay with Fraction ((Fraction(2, 1),), [Fraction(0, 1), Fraction(1, 1)]), ((Decimal('2.0'),), [Decimal('0.0'), Decimal('1.0')]), ( ( datetime(2019, 3, 29, 12, 34, 56), datetime(2019, 3, 29, 12, 37, 55), timedelta(minutes=1), ), [ datetime(2019, 3, 29, 12, 34, 56), datetime(2019, 3, 29, 12, 35, 56), datetime(2019, 3, 29, 12, 36, 56), ], ), ]: actual = list(mi.numeric_range(*args)) self.assertEqual(expected, actual) self.assertTrue( all(type(a) == type(e) for a, e in zip(actual, expected)) ) def test_arg_count(self): for args, message in [ ((), 'numeric_range expected at least 1 argument, got 0'), ( (0, 1, 2, 3), 'numeric_range expected at most 3 arguments, got 4', ), ]: with self.assertRaisesRegex(TypeError, message): mi.numeric_range(*args) def test_zero_step(self): for args in [ (1, 2, 0), ( datetime(2019, 3, 29, 12, 34, 56), datetime(2019, 3, 29, 12, 37, 55), timedelta(minutes=0), ), (1.0, 2.0, 0.0), (Decimal("1.0"), Decimal("2.0"), Decimal("0.0")), (Fraction(2, 2), Fraction(4, 2), Fraction(0, 2)), ]: with self.assertRaises(ValueError): list(mi.numeric_range(*args)) def test_bool(self): for args, expected in [ ((1.0, 3.0, 1.5), True), ((1.0, 2.0, 1.5), True), ((1.0, 1.0, 1.5), False), ((1.0, 0.0, 1.5), False), ((3.0, 1.0, -1.5), True), ((2.0, 1.0, -1.5), True), ((1.0, 1.0, -1.5), False), ((0.0, 1.0, -1.5), False), ((Decimal("1.0"), Decimal("2.0"), Decimal("1.5")), True), ((Decimal("1.0"), Decimal("0.0"), Decimal("1.5")), False), ((Fraction(2, 2), Fraction(4, 2), Fraction(3, 2)), True), ((Fraction(2, 2), Fraction(0, 2), Fraction(3, 2)), False), ( ( datetime(2019, 3, 29), datetime(2019, 3, 30), timedelta(hours=1), ), True, ), ( ( datetime(2019, 3, 29), datetime(2019, 3, 28), timedelta(hours=1), ), False, ), ]: self.assertEqual(expected, bool(mi.numeric_range(*args))) def test_contains(self): for args, expected_in, expected_not_in in [ ((10,), range(10), (0.5,)), ((1.0, 9.9, 1.5), (1.0, 2.5, 4.0, 5.5, 7.0, 8.5), (0.9,)), ((9.0, 1.0, -1.5), (1.5, 3.0, 4.5, 6.0, 7.5, 9.0), (0.0, 0.9)), ( (Decimal("1.0"), Decimal("9.9"), Decimal("1.5")), ( Decimal("1.0"), Decimal("2.5"), Decimal("4.0"), Decimal("5.5"), Decimal("7.0"), Decimal("8.5"), ), (Decimal("0.9"),), ), ( (Fraction(0, 1), Fraction(5, 1), Fraction(1, 2)), (Fraction(0, 1), Fraction(1, 2), Fraction(9, 2)), (Fraction(10, 2),), ), ( ( datetime(2019, 3, 29), datetime(2019, 3, 30), timedelta(hours=1), ), (datetime(2019, 3, 29, 15),), (datetime(2019, 3, 29, 15, 30),), ), ]: r = mi.numeric_range(*args) for v in expected_in: self.assertTrue(v in r) self.assertFalse(v not in r) for v in expected_not_in: self.assertFalse(v in r) self.assertTrue(v not in r) def test_eq(self): for args1, args2 in [ ((0, 5, 2), (0, 6, 2)), ((1.0, 9.9, 1.5), (1.0, 8.6, 1.5)), ((8.5, 0.0, -1.5), (8.5, 0.7, -1.5)), ((7.0, 0.0, 1.0), (17.0, 7.0, 0.5)), ( (Decimal("1.0"), Decimal("9.9"), Decimal("1.5")), (Decimal("1.0"), Decimal("8.6"), Decimal("1.5")), ), ( (Fraction(1, 1), Fraction(10, 1), Fraction(3, 2)), (Fraction(1, 1), Fraction(9, 1), Fraction(3, 2)), ), ( ( datetime(2019, 3, 29), datetime(2019, 3, 30), timedelta(hours=10), ), ( datetime(2019, 3, 29), datetime(2019, 3, 30, 1), timedelta(hours=10), ), ), ]: self.assertEqual( mi.numeric_range(*args1), mi.numeric_range(*args2) ) for args1, args2 in [ ((0, 5, 2), (0, 7, 2)), ((1.0, 9.9, 1.5), (1.2, 9.9, 1.5)), ((1.0, 9.9, 1.5), (1.0, 10.3, 1.5)), ((1.0, 9.9, 1.5), (1.0, 9.9, 1.4)), ((8.5, 0.0, -1.5), (8.4, 0.0, -1.5)), ((8.5, 0.0, -1.5), (8.5, -0.7, -1.5)), ((8.5, 0.0, -1.5), (8.5, 0.0, -1.4)), ((0.0, 7.0, 1.0), (7.0, 0.0, 1.0)), ( (Decimal("1.0"), Decimal("10.0"), Decimal("1.5")), (Decimal("1.0"), Decimal("10.5"), Decimal("1.5")), ), ( (Fraction(1, 1), Fraction(10, 1), Fraction(3, 2)), (Fraction(1, 1), Fraction(21, 2), Fraction(3, 2)), ), ( ( datetime(2019, 3, 29), datetime(2019, 3, 30), timedelta(hours=10), ), ( datetime(2019, 3, 29), datetime(2019, 3, 30, 15), timedelta(hours=10), ), ), ]: self.assertNotEqual( mi.numeric_range(*args1), mi.numeric_range(*args2) ) self.assertNotEqual(mi.numeric_range(7.0), 1) self.assertNotEqual(mi.numeric_range(7.0), "abc") def test_get_item_by_index(self): for args, index, expected in [ ((1, 6), 2, 3), ((1.0, 6.0, 1.5), 0, 1.0), ((1.0, 6.0, 1.5), 1, 2.5), ((1.0, 6.0, 1.5), 2, 4.0), ((1.0, 6.0, 1.5), 3, 5.5), ((1.0, 6.0, 1.5), -1, 5.5), ((1.0, 6.0, 1.5), -2, 4.0), ( (Decimal("1.0"), Decimal("9.0"), Decimal("1.5")), -1, Decimal("8.5"), ), ( (Fraction(1, 1), Fraction(10, 1), Fraction(3, 2)), 2, Fraction(4, 1), ), ( ( datetime(2019, 3, 29), datetime(2019, 3, 30), timedelta(hours=10), ), 1, datetime(2019, 3, 29, 10), ), ]: self.assertEqual(expected, mi.numeric_range(*args)[index]) for args, index in [ ((1.0, 6.0, 1.5), 4), ((1.0, 6.0, 1.5), -5), ((6.0, 1.0, 1.5), 0), ((6.0, 1.0, 1.5), -1), ((Decimal("1.0"), Decimal("9.0"), Decimal("-1.5")), -1), ((Fraction(1, 1), Fraction(2, 1), Fraction(3, 2)), 2), ( ( datetime(2019, 3, 29), datetime(2019, 3, 30), timedelta(hours=10), ), 8, ), ]: with self.assertRaises(IndexError): mi.numeric_range(*args)[index] def test_get_item_by_slice(self): for args, sl, expected_args in [ ((1.0, 9.0, 1.5), slice(None, None, None), (1.0, 9.0, 1.5)), ((1.0, 9.0, 1.5), slice(None, 1, None), (1.0, 2.5, 1.5)), ((1.0, 9.0, 1.5), slice(None, None, 2), (1.0, 9.0, 3.0)), ((1.0, 9.0, 1.5), slice(None, 2, None), (1.0, 4.0, 1.5)), ((1.0, 9.0, 1.5), slice(1, 2, None), (2.5, 4.0, 1.5)), ((1.0, 9.0, 1.5), slice(1, -1, None), (2.5, 8.5, 1.5)), ((1.0, 9.0, 1.5), slice(10, None, 3), (9.0, 9.0, 4.5)), ((1.0, 9.0, 1.5), slice(-10, None, 3), (1.0, 9.0, 4.5)), ((1.0, 9.0, 1.5), slice(None, -10, 3), (1.0, 1.0, 4.5)), ((1.0, 9.0, 1.5), slice(None, 10, 3), (1.0, 9.0, 4.5)), ( (Decimal("1.0"), Decimal("9.0"), Decimal("1.5")), slice(1, -1, None), (Decimal("2.5"), Decimal("8.5"), Decimal("1.5")), ), ( (Fraction(1, 1), Fraction(5, 1), Fraction(3, 2)), slice(1, -1, None), (Fraction(5, 2), Fraction(4, 1), Fraction(3, 2)), ), ( ( datetime(2019, 3, 29), datetime(2019, 3, 30), timedelta(hours=10), ), slice(1, -1, None), ( datetime(2019, 3, 29, 10), datetime(2019, 3, 29, 20), timedelta(hours=10), ), ), ]: self.assertEqual( mi.numeric_range(*expected_args), mi.numeric_range(*args)[sl] ) def test_hash(self): for args, expected in [ ((1.0, 6.0, 1.5), hash((1.0, 5.5, 1.5))), ((1.0, 7.0, 1.5), hash((1.0, 5.5, 1.5))), ((1.0, 7.5, 1.5), hash((1.0, 7.0, 1.5))), ((1.0, 1.5, 1.5), hash((1.0, 1.0, 1.5))), ((1.5, 1.0, 1.5), hash(range(0, 0))), ((1.5, 1.5, 1.5), hash(range(0, 0))), ( (Decimal("1.0"), Decimal("9.0"), Decimal("1.5")), hash((Decimal("1.0"), Decimal("8.5"), Decimal("1.5"))), ), ( (Fraction(1, 1), Fraction(5, 1), Fraction(3, 2)), hash((Fraction(1, 1), Fraction(4, 1), Fraction(3, 2))), ), ( ( datetime(2019, 3, 29), datetime(2019, 3, 30), timedelta(hours=10), ), hash( ( datetime(2019, 3, 29), datetime(2019, 3, 29, 20), timedelta(hours=10), ) ), ), ]: self.assertEqual(expected, hash(mi.numeric_range(*args))) def test_iter_twice(self): r1 = mi.numeric_range(1.0, 9.9, 1.5) r2 = mi.numeric_range(8.5, 0.0, -1.5) self.assertEqual([1.0, 2.5, 4.0, 5.5, 7.0, 8.5], list(r1)) self.assertEqual([1.0, 2.5, 4.0, 5.5, 7.0, 8.5], list(r1)) self.assertEqual([8.5, 7.0, 5.5, 4.0, 2.5, 1.0], list(r2)) self.assertEqual([8.5, 7.0, 5.5, 4.0, 2.5, 1.0], list(r2)) def test_len(self): for args, expected in [ ((1.0, 7.0, 1.5), 4), ((1.0, 7.01, 1.5), 5), ((7.0, 1.0, -1.5), 4), ((7.01, 1.0, -1.5), 5), ((0.1, 0.30000000000000001, 0.2), 1), # IEE 754 ! ( ( Decimal("0.1"), Decimal("0.30000000000000001"), Decimal("0.2"), ), 2, ), # works with Decimal ((Decimal("1.0"), Decimal("9.0"), Decimal("1.5")), 6), ((Fraction(1, 1), Fraction(5, 1), Fraction(3, 2)), 3), ( ( datetime(2019, 3, 29), datetime(2019, 3, 30), timedelta(hours=10), ), 3, ), ]: self.assertEqual(expected, len(mi.numeric_range(*args))) def test_repr(self): for args, *expected in [ ((7.0,), "numeric_range(0.0, 7.0)"), ((1.0, 7.0), "numeric_range(1.0, 7.0)"), ((7.0, 1.0, -1.5), "numeric_range(7.0, 1.0, -1.5)"), ( (Decimal("1.0"), Decimal("9.0"), Decimal("1.5")), ( "numeric_range(Decimal('1.0'), Decimal('9.0'), " "Decimal('1.5'))" ), ), ( (Fraction(7, 7), Fraction(10, 2), Fraction(3, 2)), ( "numeric_range(Fraction(1, 1), Fraction(5, 1), " "Fraction(3, 2))" ), ), ( ( datetime(2019, 3, 29), datetime(2019, 3, 30), timedelta(hours=10), ), "numeric_range(datetime.datetime(2019, 3, 29, 0, 0), " "datetime.datetime(2019, 3, 30, 0, 0), " "datetime.timedelta(seconds=36000))", "numeric_range(datetime.datetime(2019, 3, 29, 0, 0), " "datetime.datetime(2019, 3, 30, 0, 0), " "datetime.timedelta(0, 36000))", ), ]: with self.subTest(args=args): self.assertIn(repr(mi.numeric_range(*args)), expected) def test_reversed(self): for args, expected in [ ((7.0,), [6.0, 5.0, 4.0, 3.0, 2.0, 1.0, 0.0]), ((1.0, 7.0), [6.0, 5.0, 4.0, 3.0, 2.0, 1.0]), ((7.0, 1.0, -1.5), [2.5, 4.0, 5.5, 7.0]), ((7.0, 0.9, -1.5), [1.0, 2.5, 4.0, 5.5, 7.0]), ( (Decimal("1.0"), Decimal("5.0"), Decimal("1.5")), [Decimal('4.0'), Decimal('2.5'), Decimal('1.0')], ), ( (Fraction(1, 1), Fraction(5, 1), Fraction(3, 2)), [Fraction(4, 1), Fraction(5, 2), Fraction(1, 1)], ), ( ( datetime(2019, 3, 29), datetime(2019, 3, 30), timedelta(hours=10), ), [ datetime(2019, 3, 29, 20), datetime(2019, 3, 29, 10), datetime(2019, 3, 29), ], ), ]: self.assertEqual(expected, list(reversed(mi.numeric_range(*args)))) def test_count(self): for args, v, c in [ ((7.0,), 0.0, 1), ((7.0,), 0.5, 0), ((7.0,), 6.0, 1), ((7.0,), 7.0, 0), ((7.0,), 10.0, 0), ( (Decimal("1.0"), Decimal("5.0"), Decimal("1.5")), Decimal('4.0'), 1, ), ( (Fraction(1, 1), Fraction(5, 1), Fraction(3, 2)), Fraction(5, 2), 1, ), ( ( datetime(2019, 3, 29), datetime(2019, 3, 30), timedelta(hours=10), ), datetime(2019, 3, 29, 20), 1, ), ]: self.assertEqual(c, mi.numeric_range(*args).count(v)) def test_index(self): for args, v, i in [ ((7.0,), 0.0, 0), ((7.0,), 6.0, 6), ((7.0, 0.0, -1.0), 7.0, 0), ((7.0, 0.0, -1.0), 1.0, 6), ( (Decimal("1.0"), Decimal("5.0"), Decimal("1.5")), Decimal('4.0'), 2, ), ( (Fraction(1, 1), Fraction(5, 1), Fraction(3, 2)), Fraction(5, 2), 1, ), ( ( datetime(2019, 3, 29), datetime(2019, 3, 30), timedelta(hours=10), ), datetime(2019, 3, 29, 20), 2, ), ]: self.assertEqual(i, mi.numeric_range(*args).index(v)) for args, v in [ ((0.7,), 0.5), ((0.7,), 7.0), ((0.7,), 10.0), ((7.0, 0.0, -1.0), 0.5), ((7.0, 0.0, -1.0), 0.0), ((7.0, 0.0, -1.0), 10.0), ((7.0, 0.0), 5.0), ((Decimal("1.0"), Decimal("5.0"), Decimal("1.5")), Decimal('4.5')), ((Fraction(1, 1), Fraction(5, 1), Fraction(3, 2)), Fraction(5, 3)), ( ( datetime(2019, 3, 29), datetime(2019, 3, 30), timedelta(hours=10), ), datetime(2019, 3, 30), ), ]: with self.assertRaises(ValueError): mi.numeric_range(*args).index(v) def test_parent_classes(self): r = mi.numeric_range(7.0) self.assertTrue(isinstance(r, abc.Iterable)) self.assertFalse(isinstance(r, abc.Iterator)) self.assertTrue(isinstance(r, abc.Sequence)) self.assertTrue(isinstance(r, abc.Hashable)) def test_bad_key(self): r = mi.numeric_range(7.0) for arg, message in [ ('a', 'numeric range indices must be integers or slices, not str'), ( (), 'numeric range indices must be integers or slices, not tuple', ), ]: with self.assertRaisesRegex(TypeError, message): r[arg] def test_pickle(self): for args in [ (7.0,), (5.0, 7.0), (5.0, 7.0, 3.0), (7.0, 5.0), (7.0, 5.0, 4.0), (7.0, 5.0, -1.0), (Decimal("1.0"), Decimal("5.0"), Decimal("1.5")), (Fraction(1, 1), Fraction(5, 1), Fraction(3, 2)), (datetime(2019, 3, 29), datetime(2019, 3, 30)), ]: r = mi.numeric_range(*args) self.assertTrue(dumps(r)) # assert not empty self.assertEqual(r, loads(dumps(r))) class CountCycleTests(TestCase): def test_basic(self): expected = [ (0, 'a'), (0, 'b'), (0, 'c'), (1, 'a'), (1, 'b'), (1, 'c'), (2, 'a'), (2, 'b'), (2, 'c'), ] for actual in [ mi.take(9, mi.count_cycle('abc')), # n=None list(mi.count_cycle('abc', 3)), # n=3 ]: self.assertEqual(actual, expected) def test_empty(self): self.assertEqual(list(mi.count_cycle('')), []) self.assertEqual(list(mi.count_cycle('', 2)), []) def test_negative(self): self.assertEqual(list(mi.count_cycle('abc', -3)), []) class MarkEndsTests(TestCase): def test_basic(self): for size, expected in [ (0, []), (1, [(True, True, '0')]), (2, [(True, False, '0'), (False, True, '1')]), (3, [(True, False, '0'), (False, False, '1'), (False, True, '2')]), ( 4, [ (True, False, '0'), (False, False, '1'), (False, False, '2'), (False, True, '3'), ], ), ]: with self.subTest(size=size): iterable = map(str, range(size)) actual = list(mi.mark_ends(iterable)) self.assertEqual(actual, expected) class LocateTests(TestCase): def test_default_pred(self): iterable = [0, 1, 1, 0, 1, 0, 0] actual = list(mi.locate(iterable)) expected = [1, 2, 4] self.assertEqual(actual, expected) def test_no_matches(self): iterable = [0, 0, 0] actual = list(mi.locate(iterable)) expected = [] self.assertEqual(actual, expected) def test_custom_pred(self): iterable = ['0', 1, 1, '0', 1, '0', '0'] pred = lambda x: x == '0' actual = list(mi.locate(iterable, pred)) expected = [0, 3, 5, 6] self.assertEqual(actual, expected) def test_window_size(self): iterable = ['0', 1, 1, '0', 1, '0', '0'] pred = lambda *args: args == ('0', 1) actual = list(mi.locate(iterable, pred, window_size=2)) expected = [0, 3] self.assertEqual(actual, expected) def test_window_size_large(self): iterable = [1, 2, 3, 4] pred = lambda a, b, c, d, e: True actual = list(mi.locate(iterable, pred, window_size=5)) expected = [0] self.assertEqual(actual, expected) def test_window_size_zero(self): iterable = [1, 2, 3, 4] pred = lambda: True with self.assertRaises(ValueError): list(mi.locate(iterable, pred, window_size=0)) class StripFunctionTests(TestCase): def test_hashable(self): iterable = list('www.example.com') pred = lambda x: x in set('cmowz.') self.assertEqual(list(mi.lstrip(iterable, pred)), list('example.com')) self.assertEqual(list(mi.rstrip(iterable, pred)), list('www.example')) self.assertEqual(list(mi.strip(iterable, pred)), list('example')) def test_not_hashable(self): iterable = [ list('http://'), list('www'), list('.example'), list('.com'), ] pred = lambda x: x in [list('http://'), list('www'), list('.com')] self.assertEqual(list(mi.lstrip(iterable, pred)), iterable[2:]) self.assertEqual(list(mi.rstrip(iterable, pred)), iterable[:3]) self.assertEqual(list(mi.strip(iterable, pred)), iterable[2:3]) def test_math(self): iterable = [0, 1, 2, 3, 0, 1, 2, 3, 0, 1, 2] pred = lambda x: x <= 2 self.assertEqual(list(mi.lstrip(iterable, pred)), iterable[3:]) self.assertEqual(list(mi.rstrip(iterable, pred)), iterable[:-3]) self.assertEqual(list(mi.strip(iterable, pred)), iterable[3:-3]) class IsliceExtendedTests(TestCase): def test_all(self): iterable = ['0', '1', '2', '3', '4', '5'] indexes = list(range(-4, len(iterable) + 4)) + [None] steps = [1, 2, 3, 4, -1, -2, -3, 4] for slice_args in product(indexes, indexes, steps): with self.subTest(slice_args=slice_args): actual = list(mi.islice_extended(iterable, *slice_args)) expected = iterable[slice(*slice_args)] self.assertEqual(actual, expected, slice_args) def test_zero_step(self): with self.assertRaises(ValueError): list(mi.islice_extended([1, 2, 3], 0, 1, 0)) def test_slicing(self): iterable = map(str, count()) first_slice = mi.islice_extended(iterable)[10:] second_slice = mi.islice_extended(first_slice)[:10] third_slice = mi.islice_extended(second_slice)[::2] self.assertEqual(list(third_slice), ['10', '12', '14', '16', '18']) def test_slicing_extensive(self): iterable = range(10) options = (None, 1, 2, 7, -1) for start, stop, step in product(options, options, options): with self.subTest(slice_args=(start, stop, step)): sliced_tuple_0 = tuple( mi.islice_extended(iterable)[start:stop:step] ) sliced_tuple_1 = tuple( mi.islice_extended(iterable, start, stop, step) ) sliced_range = tuple(iterable[start:stop:step]) self.assertEqual(sliced_tuple_0, sliced_range) self.assertEqual(sliced_tuple_1, sliced_range) def test_invalid_slice(self): with self.assertRaises(TypeError): mi.islice_extended(count())[13] class ConsecutiveGroupsTest(TestCase): def test_numbers(self): iterable = [-10, -8, -7, -6, 1, 2, 4, 5, -1, 7] actual = [list(g) for g in mi.consecutive_groups(iterable)] expected = [[-10], [-8, -7, -6], [1, 2], [4, 5], [-1], [7]] self.assertEqual(actual, expected) def test_custom_ordering(self): iterable = ['1', '10', '11', '20', '21', '22', '30', '31'] ordering = lambda x: int(x) actual = [list(g) for g in mi.consecutive_groups(iterable, ordering)] expected = [['1'], ['10', '11'], ['20', '21', '22'], ['30', '31']] self.assertEqual(actual, expected) def test_exotic_ordering(self): iterable = [ ('a', 'b', 'c', 'd'), ('a', 'c', 'b', 'd'), ('a', 'c', 'd', 'b'), ('a', 'd', 'b', 'c'), ('d', 'b', 'c', 'a'), ('d', 'c', 'a', 'b'), ] ordering = list(permutations('abcd')).index actual = [list(g) for g in mi.consecutive_groups(iterable, ordering)] expected = [ [('a', 'b', 'c', 'd')], [('a', 'c', 'b', 'd'), ('a', 'c', 'd', 'b'), ('a', 'd', 'b', 'c')], [('d', 'b', 'c', 'a'), ('d', 'c', 'a', 'b')], ] self.assertEqual(actual, expected) class DifferenceTest(TestCase): def test_normal(self): iterable = [10, 20, 30, 40, 50] actual = list(mi.difference(iterable)) expected = [10, 10, 10, 10, 10] self.assertEqual(actual, expected) def test_custom(self): iterable = [10, 20, 30, 40, 50] actual = list(mi.difference(iterable, add)) expected = [10, 30, 50, 70, 90] self.assertEqual(actual, expected) def test_roundtrip(self): original = list(range(100)) accumulated = accumulate(original) actual = list(mi.difference(accumulated)) self.assertEqual(actual, original) def test_one(self): self.assertEqual(list(mi.difference([0])), [0]) def test_empty(self): self.assertEqual(list(mi.difference([])), []) @skipIf(version_info[:2] < (3, 8), 'accumulate with initial needs 3.8+') def test_initial(self): original = list(range(100)) accumulated = accumulate(original, initial=100) actual = list(mi.difference(accumulated, initial=100)) self.assertEqual(actual, original) class SeekableTest(PeekableMixinTests, TestCase): cls = mi.seekable def test_exhaustion_reset(self): iterable = [str(n) for n in range(10)] s = mi.seekable(iterable) self.assertEqual(list(s), iterable) # Normal iteration self.assertEqual(list(s), []) # Iterable is exhausted s.seek(0) self.assertEqual(list(s), iterable) # Back in action def test_partial_reset(self): iterable = [str(n) for n in range(10)] s = mi.seekable(iterable) self.assertEqual(mi.take(5, s), iterable[:5]) # Normal iteration s.seek(1) self.assertEqual(list(s), iterable[1:]) # Get the rest of the iterable def test_forward(self): iterable = [str(n) for n in range(10)] s = mi.seekable(iterable) self.assertEqual(mi.take(1, s), iterable[:1]) # Normal iteration s.seek(3) # Skip over index 2 self.assertEqual(list(s), iterable[3:]) # Result is similar to slicing s.seek(0) # Back to 0 self.assertEqual(list(s), iterable) # No difference in result def test_past_end(self): iterable = [str(n) for n in range(10)] s = mi.seekable(iterable) self.assertEqual(mi.take(1, s), iterable[:1]) # Normal iteration s.seek(20) self.assertEqual(list(s), []) # Iterable is exhausted s.seek(0) # Back to 0 self.assertEqual(list(s), iterable) # No difference in result def test_elements(self): iterable = map(str, count()) s = mi.seekable(iterable) mi.take(10, s) elements = s.elements() self.assertEqual( [elements[i] for i in range(10)], [str(n) for n in range(10)] ) self.assertEqual(len(elements), 10) mi.take(10, s) self.assertEqual(list(elements), [str(n) for n in range(20)]) def test_maxlen(self): iterable = map(str, count()) s = mi.seekable(iterable, maxlen=4) self.assertEqual(mi.take(10, s), [str(n) for n in range(10)]) self.assertEqual(list(s.elements()), ['6', '7', '8', '9']) s.seek(0) self.assertEqual(mi.take(14, s), [str(n) for n in range(6, 20)]) self.assertEqual(list(s.elements()), ['16', '17', '18', '19']) def test_maxlen_zero(self): iterable = [str(x) for x in range(5)] s = mi.seekable(iterable, maxlen=0) self.assertEqual(list(s), iterable) self.assertEqual(list(s.elements()), []) class SequenceViewTests(TestCase): def test_init(self): view = mi.SequenceView((1, 2, 3)) self.assertEqual(repr(view), "SequenceView((1, 2, 3))") self.assertRaises(TypeError, lambda: mi.SequenceView({})) def test_update(self): seq = [1, 2, 3] view = mi.SequenceView(seq) self.assertEqual(len(view), 3) self.assertEqual(repr(view), "SequenceView([1, 2, 3])") seq.pop() self.assertEqual(len(view), 2) self.assertEqual(repr(view), "SequenceView([1, 2])") def test_indexing(self): seq = ('a', 'b', 'c', 'd', 'e', 'f') view = mi.SequenceView(seq) for i in range(-len(seq), len(seq)): self.assertEqual(view[i], seq[i]) def test_slicing(self): seq = ('a', 'b', 'c', 'd', 'e', 'f') view = mi.SequenceView(seq) n = len(seq) indexes = list(range(-n - 1, n + 1)) + [None] steps = list(range(-n, n + 1)) steps.remove(0) for slice_args in product(indexes, indexes, steps): i = slice(*slice_args) self.assertEqual(view[i], seq[i]) def test_abc_methods(self): # collections.Sequence should provide all of this functionality seq = ('a', 'b', 'c', 'd', 'e', 'f', 'f') view = mi.SequenceView(seq) # __contains__ self.assertIn('b', view) self.assertNotIn('g', view) # __iter__ self.assertEqual(list(iter(view)), list(seq)) # __reversed__ self.assertEqual(list(reversed(view)), list(reversed(seq))) # index self.assertEqual(view.index('b'), 1) # count self.assertEqual(seq.count('f'), 2) class RunLengthTest(TestCase): def test_encode(self): iterable = (int(str(n)[0]) for n in count(800)) actual = mi.take(4, mi.run_length.encode(iterable)) expected = [(8, 100), (9, 100), (1, 1000), (2, 1000)] self.assertEqual(actual, expected) def test_decode(self): iterable = [('d', 4), ('c', 3), ('b', 2), ('a', 1)] actual = ''.join(mi.run_length.decode(iterable)) expected = 'ddddcccbba' self.assertEqual(actual, expected) class ExactlyNTests(TestCase): """Tests for ``exactly_n()``""" def test_true(self): """Iterable has ``n`` ``True`` elements""" self.assertTrue(mi.exactly_n([True, False, True], 2)) self.assertTrue(mi.exactly_n([1, 1, 1, 0], 3)) self.assertTrue(mi.exactly_n([False, False], 0)) self.assertTrue(mi.exactly_n(range(100), 10, lambda x: x < 10)) def test_false(self): """Iterable does not have ``n`` ``True`` elements""" self.assertFalse(mi.exactly_n([True, False, False], 2)) self.assertFalse(mi.exactly_n([True, True, False], 1)) self.assertFalse(mi.exactly_n([False], 1)) self.assertFalse(mi.exactly_n([True], -1)) self.assertFalse(mi.exactly_n(repeat(True), 100)) def test_empty(self): """Return ``True`` if the iterable is empty and ``n`` is 0""" self.assertTrue(mi.exactly_n([], 0)) self.assertFalse(mi.exactly_n([], 1)) class AlwaysReversibleTests(TestCase): """Tests for ``always_reversible()``""" def test_regular_reversed(self): self.assertEqual( list(reversed(range(10))), list(mi.always_reversible(range(10))) ) self.assertEqual( list(reversed([1, 2, 3])), list(mi.always_reversible([1, 2, 3])) ) self.assertEqual( reversed([1, 2, 3]).__class__, mi.always_reversible([1, 2, 3]).__class__, ) def test_nonseq_reversed(self): # Create a non-reversible generator from a sequence with self.assertRaises(TypeError): reversed(x for x in range(10)) self.assertEqual( list(reversed(range(10))), list(mi.always_reversible(x for x in range(10))), ) self.assertEqual( list(reversed([1, 2, 3])), list(mi.always_reversible(x for x in [1, 2, 3])), ) self.assertNotEqual( reversed((1, 2)).__class__, mi.always_reversible(x for x in (1, 2)).__class__, ) class CircularShiftsTests(TestCase): def test_empty(self): # empty iterable -> empty list self.assertEqual(list(mi.circular_shifts([])), []) def test_simple_circular_shifts(self): # test the a simple iterator case self.assertEqual( mi.circular_shifts(range(4)), [(0, 1, 2, 3), (1, 2, 3, 0), (2, 3, 0, 1), (3, 0, 1, 2)], ) def test_duplicates(self): # test non-distinct entries self.assertEqual( mi.circular_shifts([0, 1, 0, 1]), [(0, 1, 0, 1), (1, 0, 1, 0), (0, 1, 0, 1), (1, 0, 1, 0)], ) class MakeDecoratorTests(TestCase): def test_basic(self): slicer = mi.make_decorator(islice) @slicer(1, 10, 2) def user_function(arg_1, arg_2, kwarg_1=None): self.assertEqual(arg_1, 'arg_1') self.assertEqual(arg_2, 'arg_2') self.assertEqual(kwarg_1, 'kwarg_1') return map(str, count()) it = user_function('arg_1', 'arg_2', kwarg_1='kwarg_1') actual = list(it) expected = ['1', '3', '5', '7', '9'] self.assertEqual(actual, expected) def test_result_index(self): def stringify(*args, **kwargs): self.assertEqual(args[0], 'arg_0') iterable = args[1] self.assertEqual(args[2], 'arg_2') self.assertEqual(kwargs['kwarg_1'], 'kwarg_1') return map(str, iterable) stringifier = mi.make_decorator(stringify, result_index=1) @stringifier('arg_0', 'arg_2', kwarg_1='kwarg_1') def user_function(n): return count(n) it = user_function(1) actual = mi.take(5, it) expected = ['1', '2', '3', '4', '5'] self.assertEqual(actual, expected) def test_wrap_class(self): seeker = mi.make_decorator(mi.seekable) @seeker() def user_function(n): return map(str, range(n)) it = user_function(5) self.assertEqual(list(it), ['0', '1', '2', '3', '4']) it.seek(0) self.assertEqual(list(it), ['0', '1', '2', '3', '4']) class MapReduceTests(TestCase): def test_default(self): iterable = (str(x) for x in range(5)) keyfunc = lambda x: int(x) // 2 actual = sorted(mi.map_reduce(iterable, keyfunc).items()) expected = [(0, ['0', '1']), (1, ['2', '3']), (2, ['4'])] self.assertEqual(actual, expected) def test_valuefunc(self): iterable = (str(x) for x in range(5)) keyfunc = lambda x: int(x) // 2 valuefunc = int actual = sorted(mi.map_reduce(iterable, keyfunc, valuefunc).items()) expected = [(0, [0, 1]), (1, [2, 3]), (2, [4])] self.assertEqual(actual, expected) def test_reducefunc(self): iterable = (str(x) for x in range(5)) keyfunc = lambda x: int(x) // 2 valuefunc = int reducefunc = lambda value_list: reduce(mul, value_list, 1) actual = sorted( mi.map_reduce(iterable, keyfunc, valuefunc, reducefunc).items() ) expected = [(0, 0), (1, 6), (2, 4)] self.assertEqual(actual, expected) def test_ret(self): d = mi.map_reduce([1, 0, 2, 0, 1, 0], bool) self.assertEqual(d, {False: [0, 0, 0], True: [1, 2, 1]}) self.assertRaises(KeyError, lambda: d[None].append(1)) class RlocateTests(TestCase): def test_default_pred(self): iterable = [0, 1, 1, 0, 1, 0, 0] for it in (iterable[:], iter(iterable)): actual = list(mi.rlocate(it)) expected = [4, 2, 1] self.assertEqual(actual, expected) def test_no_matches(self): iterable = [0, 0, 0] for it in (iterable[:], iter(iterable)): actual = list(mi.rlocate(it)) expected = [] self.assertEqual(actual, expected) def test_custom_pred(self): iterable = ['0', 1, 1, '0', 1, '0', '0'] pred = lambda x: x == '0' for it in (iterable[:], iter(iterable)): actual = list(mi.rlocate(it, pred)) expected = [6, 5, 3, 0] self.assertEqual(actual, expected) def test_efficient_reversal(self): iterable = range(9 ** 9) # Is efficiently reversible target = 9 ** 9 - 2 pred = lambda x: x == target # Find-able from the right actual = next(mi.rlocate(iterable, pred)) self.assertEqual(actual, target) def test_window_size(self): iterable = ['0', 1, 1, '0', 1, '0', '0'] pred = lambda *args: args == ('0', 1) for it in (iterable, iter(iterable)): actual = list(mi.rlocate(it, pred, window_size=2)) expected = [3, 0] self.assertEqual(actual, expected) def test_window_size_large(self): iterable = [1, 2, 3, 4] pred = lambda a, b, c, d, e: True for it in (iterable, iter(iterable)): actual = list(mi.rlocate(iterable, pred, window_size=5)) expected = [0] self.assertEqual(actual, expected) def test_window_size_zero(self): iterable = [1, 2, 3, 4] pred = lambda: True for it in (iterable, iter(iterable)): with self.assertRaises(ValueError): list(mi.locate(iterable, pred, window_size=0)) class ReplaceTests(TestCase): def test_basic(self): iterable = range(10) pred = lambda x: x % 2 == 0 substitutes = [] actual = list(mi.replace(iterable, pred, substitutes)) expected = [1, 3, 5, 7, 9] self.assertEqual(actual, expected) def test_count(self): iterable = range(10) pred = lambda x: x % 2 == 0 substitutes = [] actual = list(mi.replace(iterable, pred, substitutes, count=4)) expected = [1, 3, 5, 7, 8, 9] self.assertEqual(actual, expected) def test_window_size(self): iterable = range(10) pred = lambda *args: args == (0, 1, 2) substitutes = [] actual = list(mi.replace(iterable, pred, substitutes, window_size=3)) expected = [3, 4, 5, 6, 7, 8, 9] self.assertEqual(actual, expected) def test_window_size_end(self): iterable = range(10) pred = lambda *args: args == (7, 8, 9) substitutes = [] actual = list(mi.replace(iterable, pred, substitutes, window_size=3)) expected = [0, 1, 2, 3, 4, 5, 6] self.assertEqual(actual, expected) def test_window_size_count(self): iterable = range(10) pred = lambda *args: (args == (0, 1, 2)) or (args == (7, 8, 9)) substitutes = [] actual = list( mi.replace(iterable, pred, substitutes, count=1, window_size=3) ) expected = [3, 4, 5, 6, 7, 8, 9] self.assertEqual(actual, expected) def test_window_size_large(self): iterable = range(4) pred = lambda a, b, c, d, e: True substitutes = [5, 6, 7] actual = list(mi.replace(iterable, pred, substitutes, window_size=5)) expected = [5, 6, 7] self.assertEqual(actual, expected) def test_window_size_zero(self): iterable = range(10) pred = lambda *args: True substitutes = [] with self.assertRaises(ValueError): list(mi.replace(iterable, pred, substitutes, window_size=0)) def test_iterable_substitutes(self): iterable = range(5) pred = lambda x: x % 2 == 0 substitutes = iter('__') actual = list(mi.replace(iterable, pred, substitutes)) expected = ['_', '_', 1, '_', '_', 3, '_', '_'] self.assertEqual(actual, expected) class PartitionsTest(TestCase): def test_types(self): for iterable in ['abcd', ['a', 'b', 'c', 'd'], ('a', 'b', 'c', 'd')]: with self.subTest(iterable=iterable): actual = list(mi.partitions(iterable)) expected = [ [['a', 'b', 'c', 'd']], [['a'], ['b', 'c', 'd']], [['a', 'b'], ['c', 'd']], [['a', 'b', 'c'], ['d']], [['a'], ['b'], ['c', 'd']], [['a'], ['b', 'c'], ['d']], [['a', 'b'], ['c'], ['d']], [['a'], ['b'], ['c'], ['d']], ] self.assertEqual(actual, expected) def test_empty(self): iterable = [] actual = list(mi.partitions(iterable)) expected = [[[]]] self.assertEqual(actual, expected) def test_order(self): iterable = iter([3, 2, 1]) actual = list(mi.partitions(iterable)) expected = [[[3, 2, 1]], [[3], [2, 1]], [[3, 2], [1]], [[3], [2], [1]]] self.assertEqual(actual, expected) def test_duplicates(self): iterable = [1, 1, 1] actual = list(mi.partitions(iterable)) expected = [[[1, 1, 1]], [[1], [1, 1]], [[1, 1], [1]], [[1], [1], [1]]] self.assertEqual(actual, expected) class _FrozenMultiset(Set): """ A helper class, useful to compare two lists without reference to the order of elements. FrozenMultiset represents a hashable set that allows duplicate elements. """ def __init__(self, iterable): self._collection = frozenset(Counter(iterable).items()) def __contains__(self, y): """ >>> (0, 1) in _FrozenMultiset([(0, 1), (2,), (0, 1)]) True """ return any(y == x for x, _ in self._collection) def __iter__(self): """ >>> sorted(_FrozenMultiset([(0, 1), (2,), (0, 1)])) [(0, 1), (0, 1), (2,)] """ return (x for x, c in self._collection for _ in range(c)) def __len__(self): """ >>> len(_FrozenMultiset([(0, 1), (2,), (0, 1)])) 3 """ return sum(c for x, c in self._collection) def has_duplicates(self): """ >>> _FrozenMultiset([(0, 1), (2,), (0, 1)]).has_duplicates() True """ return any(c != 1 for _, c in self._collection) def __hash__(self): return hash(self._collection) def __repr__(self): return "FrozenSet([{}]".format(", ".join(repr(x) for x in iter(self))) class SetPartitionsTests(TestCase): @staticmethod def _normalize_partition(p): """ Return a normalized, hashable, version of a partition using _FrozenMultiset """ return _FrozenMultiset(_FrozenMultiset(g) for g in p) @staticmethod def _normalize_partitions(ps): """ Return a normalized set of all normalized partitions using _FrozenMultiset """ return _FrozenMultiset( SetPartitionsTests._normalize_partition(p) for p in ps ) def test_repeated(self): it = 'aaa' actual = mi.set_partitions(it, 2) expected = [['a', 'aa'], ['a', 'aa'], ['a', 'aa']] self.assertEqual( self._normalize_partitions(expected), self._normalize_partitions(actual), ) def test_each_correct(self): a = set(range(6)) for p in mi.set_partitions(a): total = {e for g in p for e in g} self.assertEqual(a, total) def test_duplicates(self): a = set(range(6)) for p in mi.set_partitions(a): self.assertFalse(self._normalize_partition(p).has_duplicates()) def test_found_all(self): """small example, hand-checked""" expected = [ [[0], [1], [2, 3, 4]], [[0], [1, 2], [3, 4]], [[0], [2], [1, 3, 4]], [[0], [3], [1, 2, 4]], [[0], [4], [1, 2, 3]], [[0], [1, 3], [2, 4]], [[0], [1, 4], [2, 3]], [[1], [2], [0, 3, 4]], [[1], [3], [0, 2, 4]], [[1], [4], [0, 2, 3]], [[1], [0, 2], [3, 4]], [[1], [0, 3], [2, 4]], [[1], [0, 4], [2, 3]], [[2], [3], [0, 1, 4]], [[2], [4], [0, 1, 3]], [[2], [0, 1], [3, 4]], [[2], [0, 3], [1, 4]], [[2], [0, 4], [1, 3]], [[3], [4], [0, 1, 2]], [[3], [0, 1], [2, 4]], [[3], [0, 2], [1, 4]], [[3], [0, 4], [1, 2]], [[4], [0, 1], [2, 3]], [[4], [0, 2], [1, 3]], [[4], [0, 3], [1, 2]], ] actual = mi.set_partitions(range(5), 3) self.assertEqual( self._normalize_partitions(expected), self._normalize_partitions(actual), ) def test_stirling_numbers(self): """Check against https://en.wikipedia.org/wiki/ Stirling_numbers_of_the_second_kind#Table_of_values""" cardinality_by_k_by_n = [ [1], [1, 1], [1, 3, 1], [1, 7, 6, 1], [1, 15, 25, 10, 1], [1, 31, 90, 65, 15, 1], ] for n, cardinality_by_k in enumerate(cardinality_by_k_by_n, 1): for k, cardinality in enumerate(cardinality_by_k, 1): self.assertEqual( cardinality, len(list(mi.set_partitions(range(n), k))) ) def test_no_group(self): def helper(): list(mi.set_partitions(range(4), -1)) self.assertRaises(ValueError, helper) def test_to_many_groups(self): self.assertEqual([], list(mi.set_partitions(range(4), 5))) class TimeLimitedTests(TestCase): def test_basic(self): def generator(): yield 1 yield 2 sleep(0.2) yield 3 iterable = mi.time_limited(0.1, generator()) actual = list(iterable) expected = [1, 2] self.assertEqual(actual, expected) self.assertTrue(iterable.timed_out) def test_complete(self): iterable = mi.time_limited(2, iter(range(10))) actual = list(iterable) expected = [0, 1, 2, 3, 4, 5, 6, 7, 8, 9] self.assertEqual(actual, expected) self.assertFalse(iterable.timed_out) def test_zero_limit(self): iterable = mi.time_limited(0, count()) actual = list(iterable) expected = [] self.assertEqual(actual, expected) self.assertTrue(iterable.timed_out) def test_invalid_limit(self): with self.assertRaises(ValueError): list(mi.time_limited(-0.1, count())) class OnlyTests(TestCase): def test_defaults(self): self.assertEqual(mi.only([]), None) self.assertEqual(mi.only([1]), 1) self.assertRaises(ValueError, lambda: mi.only([1, 2])) def test_custom_value(self): self.assertEqual(mi.only([], default='!'), '!') self.assertEqual(mi.only([1], default='!'), 1) self.assertRaises(ValueError, lambda: mi.only([1, 2], default='!')) def test_custom_exception(self): self.assertEqual(mi.only([], too_long=RuntimeError), None) self.assertEqual(mi.only([1], too_long=RuntimeError), 1) self.assertRaises( RuntimeError, lambda: mi.only([1, 2], too_long=RuntimeError) ) def test_default_exception_message(self): self.assertRaisesRegex( ValueError, "Expected exactly one item in iterable, " "but got 'foo', 'bar', and perhaps more", lambda: mi.only(['foo', 'bar', 'baz']), ) class IchunkedTests(TestCase): def test_even(self): iterable = (str(x) for x in range(10)) actual = [''.join(c) for c in mi.ichunked(iterable, 5)] expected = ['01234', '56789'] self.assertEqual(actual, expected) def test_odd(self): iterable = (str(x) for x in range(10)) actual = [''.join(c) for c in mi.ichunked(iterable, 4)] expected = ['0123', '4567', '89'] self.assertEqual(actual, expected) def test_zero(self): iterable = [] actual = [list(c) for c in mi.ichunked(iterable, 0)] expected = [] self.assertEqual(actual, expected) def test_negative(self): iterable = count() with self.assertRaises(ValueError): [list(c) for c in mi.ichunked(iterable, -1)] def test_out_of_order(self): iterable = map(str, count()) it = mi.ichunked(iterable, 4) chunk_1 = next(it) chunk_2 = next(it) self.assertEqual(''.join(chunk_2), '4567') self.assertEqual(''.join(chunk_1), '0123') def test_laziness(self): def gen(): yield 0 raise RuntimeError yield from count(1) it = mi.ichunked(gen(), 4) chunk = next(it) self.assertEqual(next(chunk), 0) self.assertRaises(RuntimeError, next, it) class DistinctCombinationsTests(TestCase): def test_basic(self): for iterable in [ (1, 2, 2, 3, 3, 3), # In order range(6), # All distinct 'abbccc', # Not numbers 'cccbba', # Backward 'mississippi', # No particular order ]: for r in range(len(iterable)): with self.subTest(iterable=iterable, r=r): actual = list(mi.distinct_combinations(iterable, r)) expected = list( mi.unique_everseen(combinations(iterable, r)) ) self.assertEqual(actual, expected) def test_negative(self): with self.assertRaises(ValueError): list(mi.distinct_combinations([], -1)) def test_empty(self): self.assertEqual(list(mi.distinct_combinations([], 2)), []) class FilterExceptTests(TestCase): def test_no_exceptions_pass(self): iterable = '0123' actual = list(mi.filter_except(int, iterable)) expected = ['0', '1', '2', '3'] self.assertEqual(actual, expected) def test_no_exceptions_raise(self): iterable = ['0', '1', 'two', '3'] with self.assertRaises(ValueError): list(mi.filter_except(int, iterable)) def test_raise(self): iterable = ['0', '1' '2', 'three', None] with self.assertRaises(TypeError): list(mi.filter_except(int, iterable, ValueError)) def test_false(self): # Even if the validator returns false, we pass through validator = lambda x: False iterable = ['0', '1', '2', 'three', None] actual = list(mi.filter_except(validator, iterable, Exception)) expected = ['0', '1', '2', 'three', None] self.assertEqual(actual, expected) def test_multiple(self): iterable = ['0', '1', '2', 'three', None, '4'] actual = list(mi.filter_except(int, iterable, ValueError, TypeError)) expected = ['0', '1', '2', '4'] self.assertEqual(actual, expected) class MapExceptTests(TestCase): def test_no_exceptions_pass(self): iterable = '0123' actual = list(mi.map_except(int, iterable)) expected = [0, 1, 2, 3] self.assertEqual(actual, expected) def test_no_exceptions_raise(self): iterable = ['0', '1', 'two', '3'] with self.assertRaises(ValueError): list(mi.map_except(int, iterable)) def test_raise(self): iterable = ['0', '1' '2', 'three', None] with self.assertRaises(TypeError): list(mi.map_except(int, iterable, ValueError)) def test_multiple(self): iterable = ['0', '1', '2', 'three', None, '4'] actual = list(mi.map_except(int, iterable, ValueError, TypeError)) expected = [0, 1, 2, 4] self.assertEqual(actual, expected) class MapIfTests(TestCase): def test_without_func_else(self): iterable = list(range(-5, 5)) actual = list(mi.map_if(iterable, lambda x: x > 3, lambda x: 'toobig')) expected = [-5, -4, -3, -2, -1, 0, 1, 2, 3, 'toobig'] self.assertEqual(actual, expected) def test_with_func_else(self): iterable = list(range(-5, 5)) actual = list( mi.map_if( iterable, lambda x: x >= 0, lambda x: 'notneg', lambda x: 'neg' ) ) expected = ['neg'] * 5 + ['notneg'] * 5 self.assertEqual(actual, expected) def test_empty(self): actual = list(mi.map_if([], lambda x: len(x) > 5, lambda x: None)) expected = [] self.assertEqual(actual, expected) class SampleTests(TestCase): def test_unit_case(self): """Test against a fixed case by seeding the random module.""" # Beware that this test really just verifies random.random() behavior. # If the algorithm is changed (e.g. to a more naive implementation) # this test will fail, but the algorithm might be correct. # Also, this test can pass and the algorithm can be completely wrong. data = "abcdef" weights = list(range(1, len(data) + 1)) seed(123) actual = mi.sample(data, k=2, weights=weights) expected = ['f', 'e'] self.assertEqual(actual, expected) def test_length(self): """Check that *k* elements are sampled.""" data = [1, 2, 3, 4, 5] for k in [0, 3, 5, 7]: sampled = mi.sample(data, k=k) actual = len(sampled) expected = min(k, len(data)) self.assertEqual(actual, expected) def test_samling_entire_iterable(self): """If k=len(iterable), the sample contains the original elements.""" data = ["a", 2, "a", 4, (1, 2, 3)] actual = set(mi.sample(data, k=len(data))) expected = set(data) self.assertEqual(actual, expected) def test_scale_invariance_of_weights(self): """The probabilit of chosing element a_i is w_i / sum(weights). Scaling weights should not change the probability or outcome.""" data = "abcdef" weights = list(range(1, len(data) + 1)) seed(123) first_sample = mi.sample(data, k=2, weights=weights) # Scale the weights and sample again weights_scaled = [w / 1e10 for w in weights] seed(123) second_sample = mi.sample(data, k=2, weights=weights_scaled) self.assertEqual(first_sample, second_sample) def test_invariance_under_permutations_unweighted(self): """The order of the data should not matter. This is a stochastic test, but it will fail in less than 1 / 10_000 cases.""" # Create a data set and a reversed data set data = list(range(100)) data_rev = list(reversed(data)) # Sample each data set 10 times data_means = [mean(mi.sample(data, k=50)) for _ in range(10)] data_rev_means = [mean(mi.sample(data_rev, k=50)) for _ in range(10)] # The difference in the means should be low, i.e. little bias difference_in_means = abs(mean(data_means) - mean(data_rev_means)) # The observed largest difference in 10,000 simulations was 5.09599 self.assertTrue(difference_in_means < 5.1) def test_invariance_under_permutations_weighted(self): """The order of the data should not matter. This is a stochastic test, but it will fail in less than 1 / 10_000 cases.""" # Create a data set and a reversed data set data = list(range(1, 101)) data_rev = list(reversed(data)) # Sample each data set 10 times data_means = [ mean(mi.sample(data, k=50, weights=data)) for _ in range(10) ] data_rev_means = [ mean(mi.sample(data_rev, k=50, weights=data_rev)) for _ in range(10) ] # The difference in the means should be low, i.e. little bias difference_in_means = abs(mean(data_means) - mean(data_rev_means)) # The observed largest difference in 10,000 simulations was 4.337999 self.assertTrue(difference_in_means < 4.4) class IsSortedTests(TestCase): def test_basic(self): for iterable, kwargs, expected in [ ([], {}, True), ([1, 2, 3], {}, True), ([1, 1, 2, 3], {}, True), ([1, 10, 2, 3], {}, False), (['1', '10', '2', '3'], {}, True), (['1', '10', '2', '3'], {'key': int}, False), ([1, 2, 3], {'reverse': True}, False), ([1, 1, 2, 3], {'reverse': True}, False), ([1, 10, 2, 3], {'reverse': True}, False), (['3', '2', '10', '1'], {'reverse': True}, True), (['3', '2', '10', '1'], {'key': int, 'reverse': True}, False), # We'll do the same weird thing as Python here (['nan', 0, 'nan', 0], {'key': float}, True), ([0, 'nan', 0, 'nan'], {'key': float}, True), (['nan', 0, 'nan', 0], {'key': float, 'reverse': True}, True), ([0, 'nan', 0, 'nan'], {'key': float, 'reverse': True}, True), ]: with self.subTest(args=(iterable, kwargs)): mi_result = mi.is_sorted(iter(iterable), **kwargs) py_result = iterable == sorted(iterable, **kwargs) self.assertEqual(mi_result, expected) self.assertEqual(mi_result, py_result) class CallbackIterTests(TestCase): def _target(self, cb=None, exc=None, wait=0): total = 0 for i, c in enumerate('abc', 1): total += i if wait: sleep(wait) if cb: cb(i, c, intermediate_total=total) if exc: raise exc('error in target') return total def test_basic(self): func = lambda callback=None: self._target(cb=callback, wait=0.02) with mi.callback_iter(func, wait_seconds=0.01) as it: # Execution doesn't start until we begin iterating self.assertFalse(it.done) # Consume everything self.assertEqual( list(it), [ ((1, 'a'), {'intermediate_total': 1}), ((2, 'b'), {'intermediate_total': 3}), ((3, 'c'), {'intermediate_total': 6}), ], ) # After consuming everything the future is done and the # result is available. self.assertTrue(it.done) self.assertEqual(it.result, 6) # This examines the internal state of the ThreadPoolExecutor. This # isn't documented, so may break in future Python versions. self.assertTrue(it._executor._shutdown) def test_callback_kwd(self): with mi.callback_iter(self._target, callback_kwd='cb') as it: self.assertEqual( list(it), [ ((1, 'a'), {'intermediate_total': 1}), ((2, 'b'), {'intermediate_total': 3}), ((3, 'c'), {'intermediate_total': 6}), ], ) def test_partial_consumption(self): func = lambda callback=None: self._target(cb=callback) with mi.callback_iter(func) as it: self.assertEqual(next(it), ((1, 'a'), {'intermediate_total': 1})) self.assertTrue(it._executor._shutdown) def test_abort(self): func = lambda callback=None: self._target(cb=callback, wait=0.1) with mi.callback_iter(func) as it: self.assertEqual(next(it), ((1, 'a'), {'intermediate_total': 1})) with self.assertRaises(mi.AbortThread): it.result def test_no_result(self): func = lambda callback=None: self._target(cb=callback) with mi.callback_iter(func) as it: with self.assertRaises(RuntimeError): it.result def test_exception(self): func = lambda callback=None: self._target(cb=callback, exc=ValueError) with mi.callback_iter(func) as it: self.assertEqual( next(it), ((1, 'a'), {'intermediate_total': 1}), ) with self.assertRaises(ValueError): it.result class WindowedCompleteTests(TestCase): """Tests for ``windowed_complete()``""" def test_basic(self): actual = list(mi.windowed_complete([1, 2, 3, 4, 5], 3)) expected = [ ((), (1, 2, 3), (4, 5)), ((1,), (2, 3, 4), (5,)), ((1, 2), (3, 4, 5), ()), ] self.assertEqual(actual, expected) def test_zero_length(self): actual = list(mi.windowed_complete([1, 2, 3], 0)) expected = [ ((), (), (1, 2, 3)), ((1,), (), (2, 3)), ((1, 2), (), (3,)), ((1, 2, 3), (), ()), ] self.assertEqual(actual, expected) def test_wrong_length(self): seq = [1, 2, 3, 4, 5] for n in (-10, -1, len(seq) + 1, len(seq) + 10): with self.subTest(n=n): with self.assertRaises(ValueError): list(mi.windowed_complete(seq, n)) def test_every_partition(self): every_partition = lambda seq: chain( *map(partial(mi.windowed_complete, seq), range(len(seq))) ) seq = 'ABC' actual = list(every_partition(seq)) expected = [ ((), (), ('A', 'B', 'C')), (('A',), (), ('B', 'C')), (('A', 'B'), (), ('C',)), (('A', 'B', 'C'), (), ()), ((), ('A',), ('B', 'C')), (('A',), ('B',), ('C',)), (('A', 'B'), ('C',), ()), ((), ('A', 'B'), ('C',)), (('A',), ('B', 'C'), ()), ] self.assertEqual(actual, expected) class AllUniqueTests(TestCase): def test_basic(self): for iterable, expected in [ ([], True), ([1, 2, 3], True), ([1, 1], False), ([1, 2, 3, 1], False), ([1, 2, 3, '1'], True), ]: with self.subTest(args=(iterable,)): self.assertEqual(mi.all_unique(iterable), expected) def test_non_hashable(self): self.assertEqual(mi.all_unique([[1, 2], [3, 4]]), True) self.assertEqual(mi.all_unique([[1, 2], [3, 4], [1, 2]]), False) def test_partially_hashable(self): self.assertEqual(mi.all_unique([[1, 2], [3, 4], (5, 6)]), True) self.assertEqual( mi.all_unique([[1, 2], [3, 4], (5, 6), [1, 2]]), False ) self.assertEqual( mi.all_unique([[1, 2], [3, 4], (5, 6), (5, 6)]), False ) def test_key(self): iterable = ['A', 'B', 'C', 'b'] self.assertEqual(mi.all_unique(iterable, lambda x: x), True) self.assertEqual(mi.all_unique(iterable, str.lower), False) def test_infinite(self): self.assertEqual(mi.all_unique(mi.prepend(3, count())), False) class NthProductTests(TestCase): def test_basic(self): iterables = ['ab', 'cdef', 'ghi'] for index, expected in enumerate(product(*iterables)): actual = mi.nth_product(index, *iterables) self.assertEqual(actual, expected) def test_long(self): actual = mi.nth_product(1337, range(101), range(22), range(53)) expected = (1, 3, 12) self.assertEqual(actual, expected) def test_negative(self): iterables = ['abc', 'de', 'fghi'] for index, expected in enumerate(product(*iterables)): actual = mi.nth_product(index - 24, *iterables) self.assertEqual(actual, expected) def test_invalid_index(self): with self.assertRaises(IndexError): mi.nth_product(24, 'ab', 'cde', 'fghi') class ValueChainTests(TestCase): def test_empty(self): actual = list(mi.value_chain()) expected = [] self.assertEqual(actual, expected) def test_simple(self): actual = list(mi.value_chain(1, 2.71828, False, 'foo')) expected = [1, 2.71828, False, 'foo'] self.assertEqual(actual, expected) def test_more(self): actual = list(mi.value_chain(b'bar', [1, 2, 3], 4, {'key': 1})) expected = [b'bar', 1, 2, 3, 4, 'key'] self.assertEqual(actual, expected) def test_empty_lists(self): actual = list(mi.value_chain(1, 2, [], [3, 4])) expected = [1, 2, 3, 4] self.assertEqual(actual, expected) def test_complex(self): obj = object() actual = list( mi.value_chain( (1, (2, (3,))), ['foo', ['bar', ['baz']], 'tic'], {'key': {'foo': 1}}, obj, ) ) expected = [1, (2, (3,)), 'foo', ['bar', ['baz']], 'tic', 'key', obj] self.assertEqual(actual, expected) class ProductIndexTests(TestCase): def test_basic(self): iterables = ['ab', 'cdef', 'ghi'] first_index = {} for index, element in enumerate(product(*iterables)): actual = mi.product_index(element, *iterables) expected = first_index.setdefault(element, index) self.assertEqual(actual, expected) def test_multiplicity(self): iterables = ['ab', 'bab', 'cab'] first_index = {} for index, element in enumerate(product(*iterables)): actual = mi.product_index(element, *iterables) expected = first_index.setdefault(element, index) self.assertEqual(actual, expected) def test_long(self): actual = mi.product_index((1, 3, 12), range(101), range(22), range(53)) expected = 1337 self.assertEqual(actual, expected) def test_invalid_empty(self): with self.assertRaises(ValueError): mi.product_index('', 'ab', 'cde', 'fghi') def test_invalid_small(self): with self.assertRaises(ValueError): mi.product_index('ac', 'ab', 'cde', 'fghi') def test_invalid_large(self): with self.assertRaises(ValueError): mi.product_index('achi', 'ab', 'cde', 'fghi') def test_invalid_match(self): with self.assertRaises(ValueError): mi.product_index('axf', 'ab', 'cde', 'fghi') class CombinationIndexTests(TestCase): def test_r_less_than_n(self): iterable = 'abcdefg' r = 4 first_index = {} for index, element in enumerate(combinations(iterable, r)): actual = mi.combination_index(element, iterable) expected = first_index.setdefault(element, index) self.assertEqual(actual, expected) def test_r_equal_to_n(self): iterable = 'abcd' r = len(iterable) first_index = {} for index, element in enumerate(combinations(iterable, r=r)): actual = mi.combination_index(element, iterable) expected = first_index.setdefault(element, index) self.assertEqual(actual, expected) def test_multiplicity(self): iterable = 'abacba' r = 3 first_index = {} for index, element in enumerate(combinations(iterable, r)): actual = mi.combination_index(element, iterable) expected = first_index.setdefault(element, index) self.assertEqual(actual, expected) def test_null(self): actual = mi.combination_index(tuple(), []) expected = 0 self.assertEqual(actual, expected) def test_long(self): actual = mi.combination_index((2, 12, 35, 126), range(180)) expected = 2000000 self.assertEqual(actual, expected) def test_invalid_order(self): with self.assertRaises(ValueError): mi.combination_index(tuple('acb'), 'abcde') def test_invalid_large(self): with self.assertRaises(ValueError): mi.combination_index(tuple('abcdefg'), 'abcdef') def test_invalid_match(self): with self.assertRaises(ValueError): mi.combination_index(tuple('axe'), 'abcde') class PermutationIndexTests(TestCase): def test_r_less_than_n(self): iterable = 'abcdefg' r = 4 first_index = {} for index, element in enumerate(permutations(iterable, r)): actual = mi.permutation_index(element, iterable) expected = first_index.setdefault(element, index) self.assertEqual(actual, expected) def test_r_equal_to_n(self): iterable = 'abcd' first_index = {} for index, element in enumerate(permutations(iterable)): actual = mi.permutation_index(element, iterable) expected = first_index.setdefault(element, index) self.assertEqual(actual, expected) def test_multiplicity(self): iterable = 'abacba' r = 3 first_index = {} for index, element in enumerate(permutations(iterable, r)): actual = mi.permutation_index(element, iterable) expected = first_index.setdefault(element, index) self.assertEqual(actual, expected) def test_null(self): actual = mi.permutation_index(tuple(), []) expected = 0 self.assertEqual(actual, expected) def test_long(self): actual = mi.permutation_index((2, 12, 35, 126), range(180)) expected = 11631678 self.assertEqual(actual, expected) def test_invalid_large(self): with self.assertRaises(ValueError): mi.permutation_index(tuple('abcdefg'), 'abcdef') def test_invalid_match(self): with self.assertRaises(ValueError): mi.permutation_index(tuple('axe'), 'abcde') class CountableTests(TestCase): def test_empty(self): iterable = [] it = mi.countable(iterable) self.assertEqual(it.items_seen, 0) self.assertEqual(list(it), []) def test_basic(self): iterable = '0123456789' it = mi.countable(iterable) self.assertEqual(it.items_seen, 0) self.assertEqual(next(it), '0') self.assertEqual(it.items_seen, 1) self.assertEqual(''.join(it), '123456789') self.assertEqual(it.items_seen, 10) class ChunkedEvenTests(TestCase): """Tests for ``chunked_even()``""" def test_0(self): self._test_finite('', 3, []) def test_1(self): self._test_finite('A', 1, [['A']]) def test_4(self): self._test_finite('ABCD', 3, [['A', 'B'], ['C', 'D']]) def test_5(self): self._test_finite('ABCDE', 3, [['A', 'B', 'C'], ['D', 'E']]) def test_6(self): self._test_finite('ABCDEF', 3, [['A', 'B', 'C'], ['D', 'E', 'F']]) def test_7(self): self._test_finite( 'ABCDEFG', 3, [['A', 'B', 'C'], ['D', 'E'], ['F', 'G']] ) def _test_finite(self, seq, n, expected): # Check with and without `len()` self.assertEqual(list(mi.chunked_even(seq, n)), expected) self.assertEqual(list(mi.chunked_even(iter(seq), n)), expected) def test_infinite(self): for n in range(1, 5): k = 0 def count_with_assert(): for i in count(): # Look-ahead should be less than n^2 self.assertLessEqual(i, n * k + n * n) yield i ls = mi.chunked_even(count_with_assert(), n) while k < 2: self.assertEqual(next(ls), list(range(k * n, (k + 1) * n))) k += 1 def test_evenness(self): for N in range(1, 50): for n in range(1, N + 2): lengths = [] items = [] for l in mi.chunked_even(range(N), n): L = len(l) self.assertLessEqual(L, n) self.assertGreaterEqual(L, 1) lengths.append(L) items.extend(l) self.assertEqual(items, list(range(N))) self.assertLessEqual(max(lengths) - min(lengths), 1) class ZipBroadcastTests(TestCase): def test_basic(self): for objects, expected in [ # All scalar ([1, 2], [(1, 2)]), # Scalar, iterable ([1, [2]], [(1, 2)]), # Iterable, scalar ([[1], 2], [(1, 2)]), # Mixed length ([1, [2, 3]], [(1, 2), (1, 3)]), # All iterable ([[1, 2], [3, 4]], [(1, 3), (2, 4)]), ]: with self.subTest(expected=expected): actual = list(mi.zip_broadcast(*objects)) self.assertEqual(actual, expected) def test_scalar_types(self): # Default: str and bytes are treated as scalar self.assertEqual( list(mi.zip_broadcast('ab', [1, 2, 3])), [('ab', 1), ('ab', 2), ('ab', 3)], ) self.assertEqual( list(mi.zip_broadcast(b'ab', [1, 2, 3])), [(b'ab', 1), (b'ab', 2), (b'ab', 3)], ) # scalar_types=None allows str and bytes to be treated as iterable self.assertEqual( list(mi.zip_broadcast('abc', [1, 2, 3], scalar_types=None)), [('a', 1), ('b', 2), ('c', 3)], ) # Use a custom type self.assertEqual( list(mi.zip_broadcast({'a': 'b'}, [1, 2, 3], scalar_types=dict)), [({'a': 'b'}, 1), ({'a': 'b'}, 2), ({'a': 'b'}, 3)], ) def test_strict(self): # Truncate by default self.assertEqual( list(mi.zip_broadcast('a', [1, 2], [3, 4, 5])), [('a', 1, 3), ('a', 2, 4)], ) # Raise an exception for strict=True with self.assertRaises(mi.UnequalIterablesError): list(mi.zip_broadcast('a', [1, 2], [3, 4, 5], strict=True)) def test_empty(self): self.assertEqual(list(mi.zip_broadcast()), []) ././@PaxHeader0000000000000000000000000000002600000000000011453 xustar000000000000000022 mtime=1631273505.0 more-itertools-8.10.0/tests/test_recipes.py0000664000175000017500000005452000000000000020024 0ustar00bobo00000000000000import warnings from doctest import DocTestSuite from itertools import combinations, count, permutations from math import factorial from unittest import TestCase import more_itertools as mi def load_tests(loader, tests, ignore): # Add the doctests tests.addTests(DocTestSuite('more_itertools.recipes')) return tests class TakeTests(TestCase): """Tests for ``take()``""" def test_simple_take(self): """Test basic usage""" t = mi.take(5, range(10)) self.assertEqual(t, [0, 1, 2, 3, 4]) def test_null_take(self): """Check the null case""" t = mi.take(0, range(10)) self.assertEqual(t, []) def test_negative_take(self): """Make sure taking negative items results in a ValueError""" self.assertRaises(ValueError, lambda: mi.take(-3, range(10))) def test_take_too_much(self): """Taking more than an iterator has remaining should return what the iterator has remaining. """ t = mi.take(10, range(5)) self.assertEqual(t, [0, 1, 2, 3, 4]) class TabulateTests(TestCase): """Tests for ``tabulate()``""" def test_simple_tabulate(self): """Test the happy path""" t = mi.tabulate(lambda x: x) f = tuple([next(t) for _ in range(3)]) self.assertEqual(f, (0, 1, 2)) def test_count(self): """Ensure tabulate accepts specific count""" t = mi.tabulate(lambda x: 2 * x, -1) f = (next(t), next(t), next(t)) self.assertEqual(f, (-2, 0, 2)) class TailTests(TestCase): """Tests for ``tail()``""" def test_greater(self): """Length of iterable is greater than requested tail""" self.assertEqual(list(mi.tail(3, 'ABCDEFG')), ['E', 'F', 'G']) def test_equal(self): """Length of iterable is equal to the requested tail""" self.assertEqual( list(mi.tail(7, 'ABCDEFG')), ['A', 'B', 'C', 'D', 'E', 'F', 'G'] ) def test_less(self): """Length of iterable is less than requested tail""" self.assertEqual( list(mi.tail(8, 'ABCDEFG')), ['A', 'B', 'C', 'D', 'E', 'F', 'G'] ) class ConsumeTests(TestCase): """Tests for ``consume()``""" def test_sanity(self): """Test basic functionality""" r = (x for x in range(10)) mi.consume(r, 3) self.assertEqual(3, next(r)) def test_null_consume(self): """Check the null case""" r = (x for x in range(10)) mi.consume(r, 0) self.assertEqual(0, next(r)) def test_negative_consume(self): """Check that negative consumsion throws an error""" r = (x for x in range(10)) self.assertRaises(ValueError, lambda: mi.consume(r, -1)) def test_total_consume(self): """Check that iterator is totally consumed by default""" r = (x for x in range(10)) mi.consume(r) self.assertRaises(StopIteration, lambda: next(r)) class NthTests(TestCase): """Tests for ``nth()``""" def test_basic(self): """Make sure the nth item is returned""" l = range(10) for i, v in enumerate(l): self.assertEqual(mi.nth(l, i), v) def test_default(self): """Ensure a default value is returned when nth item not found""" l = range(3) self.assertEqual(mi.nth(l, 100, "zebra"), "zebra") def test_negative_item_raises(self): """Ensure asking for a negative item raises an exception""" self.assertRaises(ValueError, lambda: mi.nth(range(10), -3)) class AllEqualTests(TestCase): """Tests for ``all_equal()``""" def test_true(self): """Everything is equal""" self.assertTrue(mi.all_equal('aaaaaa')) self.assertTrue(mi.all_equal([0, 0, 0, 0])) def test_false(self): """Not everything is equal""" self.assertFalse(mi.all_equal('aaaaab')) self.assertFalse(mi.all_equal([0, 0, 0, 1])) def test_tricky(self): """Not everything is identical, but everything is equal""" items = [1, complex(1, 0), 1.0] self.assertTrue(mi.all_equal(items)) def test_empty(self): """Return True if the iterable is empty""" self.assertTrue(mi.all_equal('')) self.assertTrue(mi.all_equal([])) def test_one(self): """Return True if the iterable is singular""" self.assertTrue(mi.all_equal('0')) self.assertTrue(mi.all_equal([0])) class QuantifyTests(TestCase): """Tests for ``quantify()``""" def test_happy_path(self): """Make sure True count is returned""" q = [True, False, True] self.assertEqual(mi.quantify(q), 2) def test_custom_predicate(self): """Ensure non-default predicates return as expected""" q = range(10) self.assertEqual(mi.quantify(q, lambda x: x % 2 == 0), 5) class PadnoneTests(TestCase): def test_basic(self): iterable = range(2) for func in (mi.pad_none, mi.padnone): with self.subTest(func=func): p = func(iterable) self.assertEqual( [0, 1, None, None], [next(p) for _ in range(4)] ) class NcyclesTests(TestCase): """Tests for ``nyclces()``""" def test_happy_path(self): """cycle a sequence three times""" r = ["a", "b", "c"] n = mi.ncycles(r, 3) self.assertEqual( ["a", "b", "c", "a", "b", "c", "a", "b", "c"], list(n) ) def test_null_case(self): """asking for 0 cycles should return an empty iterator""" n = mi.ncycles(range(100), 0) self.assertRaises(StopIteration, lambda: next(n)) def test_pathalogical_case(self): """asking for negative cycles should return an empty iterator""" n = mi.ncycles(range(100), -10) self.assertRaises(StopIteration, lambda: next(n)) class DotproductTests(TestCase): """Tests for ``dotproduct()``'""" def test_happy_path(self): """simple dotproduct example""" self.assertEqual(400, mi.dotproduct([10, 10], [20, 20])) class FlattenTests(TestCase): """Tests for ``flatten()``""" def test_basic_usage(self): """ensure list of lists is flattened one level""" f = [[0, 1, 2], [3, 4, 5]] self.assertEqual(list(range(6)), list(mi.flatten(f))) def test_single_level(self): """ensure list of lists is flattened only one level""" f = [[0, [1, 2]], [[3, 4], 5]] self.assertEqual([0, [1, 2], [3, 4], 5], list(mi.flatten(f))) class RepeatfuncTests(TestCase): """Tests for ``repeatfunc()``""" def test_simple_repeat(self): """test simple repeated functions""" r = mi.repeatfunc(lambda: 5) self.assertEqual([5, 5, 5, 5, 5], [next(r) for _ in range(5)]) def test_finite_repeat(self): """ensure limited repeat when times is provided""" r = mi.repeatfunc(lambda: 5, times=5) self.assertEqual([5, 5, 5, 5, 5], list(r)) def test_added_arguments(self): """ensure arguments are applied to the function""" r = mi.repeatfunc(lambda x: x, 2, 3) self.assertEqual([3, 3], list(r)) def test_null_times(self): """repeat 0 should return an empty iterator""" r = mi.repeatfunc(range, 0, 3) self.assertRaises(StopIteration, lambda: next(r)) class PairwiseTests(TestCase): """Tests for ``pairwise()``""" def test_base_case(self): """ensure an iterable will return pairwise""" p = mi.pairwise([1, 2, 3]) self.assertEqual([(1, 2), (2, 3)], list(p)) def test_short_case(self): """ensure an empty iterator if there's not enough values to pair""" p = mi.pairwise("a") self.assertRaises(StopIteration, lambda: next(p)) class GrouperTests(TestCase): """Tests for ``grouper()``""" def test_even(self): """Test when group size divides evenly into the length of the iterable. """ self.assertEqual( list(mi.grouper('ABCDEF', 3)), [('A', 'B', 'C'), ('D', 'E', 'F')] ) def test_odd(self): """Test when group size does not divide evenly into the length of the iterable. """ self.assertEqual( list(mi.grouper('ABCDE', 3)), [('A', 'B', 'C'), ('D', 'E', None)] ) def test_fill_value(self): """Test that the fill value is used to pad the final group""" self.assertEqual( list(mi.grouper('ABCDE', 3, 'x')), [('A', 'B', 'C'), ('D', 'E', 'x')], ) def test_legacy_order(self): """Historically, grouper expected the n as the first parameter""" with warnings.catch_warnings(record=True) as caught: warnings.simplefilter('always') self.assertEqual( list(mi.grouper(3, 'ABCDEF')), [('A', 'B', 'C'), ('D', 'E', 'F')], ) (warning,) = caught assert warning.category == DeprecationWarning class RoundrobinTests(TestCase): """Tests for ``roundrobin()``""" def test_even_groups(self): """Ensure ordered output from evenly populated iterables""" self.assertEqual( list(mi.roundrobin('ABC', [1, 2, 3], range(3))), ['A', 1, 0, 'B', 2, 1, 'C', 3, 2], ) def test_uneven_groups(self): """Ensure ordered output from unevenly populated iterables""" self.assertEqual( list(mi.roundrobin('ABCD', [1, 2], range(0))), ['A', 1, 'B', 2, 'C', 'D'], ) class PartitionTests(TestCase): """Tests for ``partition()``""" def test_bool(self): lesser, greater = mi.partition(lambda x: x > 5, range(10)) self.assertEqual(list(lesser), [0, 1, 2, 3, 4, 5]) self.assertEqual(list(greater), [6, 7, 8, 9]) def test_arbitrary(self): divisibles, remainders = mi.partition(lambda x: x % 3, range(10)) self.assertEqual(list(divisibles), [0, 3, 6, 9]) self.assertEqual(list(remainders), [1, 2, 4, 5, 7, 8]) def test_pred_is_none(self): falses, trues = mi.partition(None, range(3)) self.assertEqual(list(falses), [0]) self.assertEqual(list(trues), [1, 2]) class PowersetTests(TestCase): """Tests for ``powerset()``""" def test_combinatorics(self): """Ensure a proper enumeration""" p = mi.powerset([1, 2, 3]) self.assertEqual( list(p), [(), (1,), (2,), (3,), (1, 2), (1, 3), (2, 3), (1, 2, 3)] ) class UniqueEverseenTests(TestCase): """Tests for ``unique_everseen()``""" def test_everseen(self): """ensure duplicate elements are ignored""" u = mi.unique_everseen('AAAABBBBCCDAABBB') self.assertEqual(['A', 'B', 'C', 'D'], list(u)) def test_custom_key(self): """ensure the custom key comparison works""" u = mi.unique_everseen('aAbACCc', key=str.lower) self.assertEqual(list('abC'), list(u)) def test_unhashable(self): """ensure things work for unhashable items""" iterable = ['a', [1, 2, 3], [1, 2, 3], 'a'] u = mi.unique_everseen(iterable) self.assertEqual(list(u), ['a', [1, 2, 3]]) def test_unhashable_key(self): """ensure things work for unhashable items with a custom key""" iterable = ['a', [1, 2, 3], [1, 2, 3], 'a'] u = mi.unique_everseen(iterable, key=lambda x: x) self.assertEqual(list(u), ['a', [1, 2, 3]]) class UniqueJustseenTests(TestCase): """Tests for ``unique_justseen()``""" def test_justseen(self): """ensure only last item is remembered""" u = mi.unique_justseen('AAAABBBCCDABB') self.assertEqual(list('ABCDAB'), list(u)) def test_custom_key(self): """ensure the custom key comparison works""" u = mi.unique_justseen('AABCcAD', str.lower) self.assertEqual(list('ABCAD'), list(u)) class IterExceptTests(TestCase): """Tests for ``iter_except()``""" def test_exact_exception(self): """ensure the exact specified exception is caught""" l = [1, 2, 3] i = mi.iter_except(l.pop, IndexError) self.assertEqual(list(i), [3, 2, 1]) def test_generic_exception(self): """ensure the generic exception can be caught""" l = [1, 2] i = mi.iter_except(l.pop, Exception) self.assertEqual(list(i), [2, 1]) def test_uncaught_exception_is_raised(self): """ensure a non-specified exception is raised""" l = [1, 2, 3] i = mi.iter_except(l.pop, KeyError) self.assertRaises(IndexError, lambda: list(i)) def test_first(self): """ensure first is run before the function""" l = [1, 2, 3] f = lambda: 25 i = mi.iter_except(l.pop, IndexError, f) self.assertEqual(list(i), [25, 3, 2, 1]) def test_multiple(self): """ensure can catch multiple exceptions""" class Fiz(Exception): pass class Buzz(Exception): pass i = 0 def fizbuzz(): nonlocal i i += 1 if i % 3 == 0: raise Fiz if i % 5 == 0: raise Buzz return i expected = ([1, 2], [4], [], [7, 8], []) for x in expected: self.assertEqual(list(mi.iter_except(fizbuzz, (Fiz, Buzz))), x) class FirstTrueTests(TestCase): """Tests for ``first_true()``""" def test_something_true(self): """Test with no keywords""" self.assertEqual(mi.first_true(range(10)), 1) def test_nothing_true(self): """Test default return value.""" self.assertIsNone(mi.first_true([0, 0, 0])) def test_default(self): """Test with a default keyword""" self.assertEqual(mi.first_true([0, 0, 0], default='!'), '!') def test_pred(self): """Test with a custom predicate""" self.assertEqual( mi.first_true([2, 4, 6], pred=lambda x: x % 3 == 0), 6 ) class RandomProductTests(TestCase): """Tests for ``random_product()`` Since random.choice() has different results with the same seed across python versions 2.x and 3.x, these tests use highly probably events to create predictable outcomes across platforms. """ def test_simple_lists(self): """Ensure that one item is chosen from each list in each pair. Also ensure that each item from each list eventually appears in the chosen combinations. Odds are roughly 1 in 7.1 * 10e16 that one item from either list will not be chosen after 100 samplings of one item from each list. Just to be safe, better use a known random seed, too. """ nums = [1, 2, 3] lets = ['a', 'b', 'c'] n, m = zip(*[mi.random_product(nums, lets) for _ in range(100)]) n, m = set(n), set(m) self.assertEqual(n, set(nums)) self.assertEqual(m, set(lets)) self.assertEqual(len(n), len(nums)) self.assertEqual(len(m), len(lets)) def test_list_with_repeat(self): """ensure multiple items are chosen, and that they appear to be chosen from one list then the next, in proper order. """ nums = [1, 2, 3] lets = ['a', 'b', 'c'] r = list(mi.random_product(nums, lets, repeat=100)) self.assertEqual(2 * 100, len(r)) n, m = set(r[::2]), set(r[1::2]) self.assertEqual(n, set(nums)) self.assertEqual(m, set(lets)) self.assertEqual(len(n), len(nums)) self.assertEqual(len(m), len(lets)) class RandomPermutationTests(TestCase): """Tests for ``random_permutation()``""" def test_full_permutation(self): """ensure every item from the iterable is returned in a new ordering 15 elements have a 1 in 1.3 * 10e12 of appearing in sorted order, so we fix a seed value just to be sure. """ i = range(15) r = mi.random_permutation(i) self.assertEqual(set(i), set(r)) if i == r: raise AssertionError("Values were not permuted") def test_partial_permutation(self): """ensure all returned items are from the iterable, that the returned permutation is of the desired length, and that all items eventually get returned. Sampling 100 permutations of length 5 from a set of 15 leaves a (2/3)^100 chance that an item will not be chosen. Multiplied by 15 items, there is a 1 in 2.6e16 chance that at least 1 item will not show up in the resulting output. Using a random seed will fix that. """ items = range(15) item_set = set(items) all_items = set() for _ in range(100): permutation = mi.random_permutation(items, 5) self.assertEqual(len(permutation), 5) permutation_set = set(permutation) self.assertLessEqual(permutation_set, item_set) all_items |= permutation_set self.assertEqual(all_items, item_set) class RandomCombinationTests(TestCase): """Tests for ``random_combination()``""" def test_pseudorandomness(self): """ensure different subsets of the iterable get returned over many samplings of random combinations""" items = range(15) all_items = set() for _ in range(50): combination = mi.random_combination(items, 5) all_items |= set(combination) self.assertEqual(all_items, set(items)) def test_no_replacement(self): """ensure that elements are sampled without replacement""" items = range(15) for _ in range(50): combination = mi.random_combination(items, len(items)) self.assertEqual(len(combination), len(set(combination))) self.assertRaises( ValueError, lambda: mi.random_combination(items, len(items) + 1) ) class RandomCombinationWithReplacementTests(TestCase): """Tests for ``random_combination_with_replacement()``""" def test_replacement(self): """ensure that elements are sampled with replacement""" items = range(5) combo = mi.random_combination_with_replacement(items, len(items) * 2) self.assertEqual(2 * len(items), len(combo)) if len(set(combo)) == len(combo): raise AssertionError("Combination contained no duplicates") def test_pseudorandomness(self): """ensure different subsets of the iterable get returned over many samplings of random combinations""" items = range(15) all_items = set() for _ in range(50): combination = mi.random_combination_with_replacement(items, 5) all_items |= set(combination) self.assertEqual(all_items, set(items)) class NthCombinationTests(TestCase): def test_basic(self): iterable = 'abcdefg' r = 4 for index, expected in enumerate(combinations(iterable, r)): actual = mi.nth_combination(iterable, r, index) self.assertEqual(actual, expected) def test_long(self): actual = mi.nth_combination(range(180), 4, 2000000) expected = (2, 12, 35, 126) self.assertEqual(actual, expected) def test_invalid_r(self): for r in (-1, 3): with self.assertRaises(ValueError): mi.nth_combination([], r, 0) def test_invalid_index(self): with self.assertRaises(IndexError): mi.nth_combination('abcdefg', 3, -36) class NthPermutationTests(TestCase): def test_r_less_than_n(self): iterable = 'abcde' r = 4 for index, expected in enumerate(permutations(iterable, r)): actual = mi.nth_permutation(iterable, r, index) self.assertEqual(actual, expected) def test_r_equal_to_n(self): iterable = 'abcde' for index, expected in enumerate(permutations(iterable)): actual = mi.nth_permutation(iterable, None, index) self.assertEqual(actual, expected) def test_long(self): iterable = tuple(range(180)) r = 4 index = 1000000 actual = mi.nth_permutation(iterable, r, index) expected = mi.nth(permutations(iterable, r), index) self.assertEqual(actual, expected) def test_null(self): actual = mi.nth_permutation([], 0, 0) expected = tuple() self.assertEqual(actual, expected) def test_negative_index(self): iterable = 'abcde' r = 4 n = factorial(len(iterable)) // factorial(len(iterable) - r) for index, expected in enumerate(permutations(iterable, r)): actual = mi.nth_permutation(iterable, r, index - n) self.assertEqual(actual, expected) def test_invalid_index(self): iterable = 'abcde' r = 4 n = factorial(len(iterable)) // factorial(len(iterable) - r) for index in [-1 - n, n + 1]: with self.assertRaises(IndexError): mi.nth_combination(iterable, r, index) def test_invalid_r(self): iterable = 'abcde' r = 4 n = factorial(len(iterable)) // factorial(len(iterable) - r) for r in [-1, n + 1]: with self.assertRaises(ValueError): mi.nth_combination(iterable, r, 0) class PrependTests(TestCase): def test_basic(self): value = 'a' iterator = iter('bcdefg') actual = list(mi.prepend(value, iterator)) expected = list('abcdefg') self.assertEqual(actual, expected) def test_multiple(self): value = 'ab' iterator = iter('cdefg') actual = tuple(mi.prepend(value, iterator)) expected = ('ab',) + tuple('cdefg') self.assertEqual(actual, expected) class Convolvetests(TestCase): def test_moving_average(self): signal = iter([10, 20, 30, 40, 50]) kernel = [0.5, 0.5] actual = list(mi.convolve(signal, kernel)) expected = [ (10 + 0) / 2, (20 + 10) / 2, (30 + 20) / 2, (40 + 30) / 2, (50 + 40) / 2, (0 + 50) / 2, ] self.assertEqual(actual, expected) def test_derivative(self): signal = iter([10, 20, 30, 40, 50]) kernel = [1, -1] actual = list(mi.convolve(signal, kernel)) expected = [10 - 0, 20 - 10, 30 - 20, 40 - 30, 50 - 40, 0 - 50] self.assertEqual(actual, expected) def test_infinite_signal(self): signal = count() kernel = [1, -1] actual = mi.take(5, mi.convolve(signal, kernel)) expected = [0, 1, 1, 1, 1] self.assertEqual(actual, expected) ././@PaxHeader0000000000000000000000000000002600000000000011453 xustar000000000000000022 mtime=1608173130.0 more-itertools-8.10.0/tox.ini0000664000175000017500000000013300000000000015121 0ustar00bobo00000000000000[tox] envlist = py{36,37,38,39} [testenv] commands = {envpython} -m unittest -v {posargs}