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Minimal library that enables partitioning of iterable collections in a concise manner.
Minimal library that enables partitioning of iterable collections in a concise manner.
|pypi| |readthedocs| |actions| |coveralls|
.. |pypi| image:: https://badge.fury.io/py/parts.svg# :target: https://badge.fury.io/py/parts :alt: PyPI version and link.
.. |readthedocs| image:: https://readthedocs.org/projects/parts/badge/?version=latest :target: https://parts.readthedocs.io/en/latest/?badge=latest :alt: Read the Docs documentation status.
.. |actions| image:: https://github.com/lapets/parts/workflows/lint-test-cover-docs/badge.svg# :target: https://github.com/lapets/parts/actions/workflows/lint-test-cover-docs.yml :alt: GitHub Actions status.
.. |coveralls| image:: https://coveralls.io/repos/github/lapets/parts/badge.svg?branch=main :target: https://coveralls.io/github/lapets/parts?branch=main :alt: Coveralls test coverage summary.
This library provides a function for partitioning iterable <https://docs.python.org/3/glossary.html#term-iterable>
__ data structure instances. When the number of parts is specified explicitly, it is treated as a strict requirement and an exception is raised when it cannot be satisfied. When a length for all parts (or each part) is specified explicitly, a best-effort approach is used: as many parts of the specified length are retrieved as possible, with the possibility that some parts at the end of the partition sequence have a shorter (but still non-zero) length.
This library is available as a package on PyPI <https://pypi.org/project/parts>
__:
.. code-block:: bash
python -m pip install parts
The library can be imported in the usual manner:
.. code-block:: python
import parts
from parts import parts
Examples ^^^^^^^^ Several examples are presented below:
.. code-block:: python
>>> list(parts([1, 2, 3, 4, 5, 6, 7], length=2))
[[1, 2], [3, 4], [5, 6], [7]]
>>> list(parts([1, 2, 3, 4, 5, 6, 7], length=4))
[[1, 2, 3, 4], [5, 6, 7]]
>>> list(parts([1, 2, 3, 4, 5, 6, 7], number=1))
[[1, 2, 3, 4, 5, 6, 7]]
>>> list(parts([1, 2, 3, 4, 5, 6, 7], 5))
[[1], [2], [3], [4, 5], [6, 7]]
>>> list(parts([1, 2, 3, 4, 5, 6], 2, 3))
[[1, 2, 3], [4, 5, 6]]
>>> list(parts([1, 2, 3, 4, 5, 6], number=3, length=2))
[[1, 2], [3, 4], [5, 6]]
>>> list(parts([1, 2, 3, 4, 5, 6, 7], 7, [1, 1, 1, 1, 1, 1, 1]))
[[1], [2], [3], [4], [5], [6], [7]]
>>> list(parts([1, 2, 3, 4, 5, 6], length=[2, 2, 2]))
[[1, 2], [3, 4], [5, 6]]
>>> list(parts([1, 2, 3, 4, 5, 6], length=[1, 2, 3]))
[[1], [2, 3], [4, 5, 6]]
>>> list(parts([1, 2, 3, 4, 5, 6, 7], number=3, length=2))
Traceback (most recent call last):
...
ValueError: cannot retrieve 3 parts from object given part length parameter of 2
All installation and development dependencies are fully specified in pyproject.toml
. The project.optional-dependencies
object is used to specify optional requirements <https://peps.python.org/pep-0621>
__ for various development tasks. This makes it possible to specify additional options (such as docs
, lint
, and so on) when performing installation using pip <https://pypi.org/project/pip>
__:
.. code-block:: bash
python -m pip install ".[docs,lint]"
Documentation
^^^^^^^^^^^^^
The documentation can be generated automatically from the source files using Sphinx <https://www.sphinx-doc.org>
__:
.. code-block:: bash
python -m pip install ".[docs]"
cd docs
sphinx-apidoc -f -E --templatedir=_templates -o _source .. && make html
Testing and Conventions
^^^^^^^^^^^^^^^^^^^^^^^
All unit tests are executed and their coverage is measured when using pytest <https://docs.pytest.org>
__ (see the pyproject.toml
file for configuration details):
.. code-block:: bash
python -m pip install ".[test]"
python -m pytest
Alternatively, all unit tests are included in the module itself and can be executed using doctest <https://docs.python.org/3/library/doctest.html>
__:
.. code-block:: bash
python src/parts/parts.py -v
Style conventions are enforced using Pylint <https://pylint.readthedocs.io>
__:
.. code-block:: bash
python -m pip install ".[lint]"
python -m pylint src/parts
Contributions
^^^^^^^^^^^^^
In order to contribute to the source code, open an issue or submit a pull request on the GitHub page <https://github.com/lapets/parts>
__ for this library.
Versioning
^^^^^^^^^^
Beginning with version 0.2.0, the version number format for this library and the changes to the library associated with version number increments conform with Semantic Versioning 2.0.0 <https://semver.org/#semantic-versioning-200>
__.
Publishing
^^^^^^^^^^
This library can be published as a package on PyPI <https://pypi.org/project/parts>
__ via the GitHub Actions workflow found in .github/workflows/build-publish-sign-release.yml
that follows the recommendations found in the Python Packaging User Guide <https://packaging.python.org/en/latest/guides/publishing-package-distribution-releases-using-github-actions-ci-cd-workflows/>
__.
Ensure that the correct version number appears in pyproject.toml
, and that any links in this README document to the Read the Docs documentation of this package (or its dependencies) have appropriate version numbers. Also ensure that the Read the Docs project for this library has an automation rule <https://docs.readthedocs.io/en/stable/automation-rules.html>
__ that activates and sets as the default all tagged versions.
To publish the package, create and push a tag for the version being published (replacing ?.?.?
with the version number):
.. code-block:: bash
git tag ?.?.?
git push origin ?.?.?
FAQs
Minimal library that enables partitioning of iterable collections in a concise manner.
We found that parts demonstrated a healthy version release cadence and project activity because the last version was released less than a year ago. It has 2 open source maintainers collaborating on the project.
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