parts 4.0.0

Minimal library that enables partitioning of iterable collections in a concise manner.

Minimal library that enables partitioning of iterable collections in a concise manner.

Purpose

This library provides a function for partitioning 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.

Installation and Usage

This library is available as a package on PyPI:

python -m pip install parts

The library can be imported in the usual manner:

import parts
from parts import parts

Examples

Several examples are presented below:

>>> 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

Development

All installation and development dependencies are fully specified in pyproject.toml. The project.optional-dependencies object is used to specify optional requirements for various development tasks. This makes it possible to specify additional options (such as docs, lint, and so on) when performing installation using pip:

python -m pip install ".[docs,lint]"

Documentation

The documentation can be generated automatically from the source files using Sphinx:

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 (see the pyproject.toml file for configuration details):

python -m pip install ".[test]"
python -m pytest

Alternatively, all unit tests are included in the module itself and can be executed using doctest:

python src/parts/parts.py -v

Style conventions are enforced using Pylint:

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 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.

Publishing

This library can be published as a package on PyPI 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.

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 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):

git tag ?.?.?
git push origin ?.?.?