parts 1.4.0

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

Minimal library that enables partitioning of iterable objects 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 managed using setuptools and are fully specified in setup.py. The extras_require parameter 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 .. ../setup.py && make html

Testing and Conventions

All unit tests are executed and their coverage is measured when using pytest (see setup.cfg 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 parts/parts.py -v

Style conventions are enforced using Pylint:

python -m pip install .[lint]
python -m pylint 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 by a package maintainer. First, install the dependencies required for packaging and publishing:

python -m pip install .[publish]

Remove any old build/distribution files. Then, package the source into a distribution archive using the wheel package:

rm -rf dist *.egg-info
python setup.py sdist bdist_wheel

Finally, upload the package distribution archive to PyPI using the twine package:

python -m twine upload dist/*