Contributing to Pint#

Pint uses (and thanks):

You can contribute in different ways:

Report issues#

You can report any issues with the package, the documentation to the Pint issue tracker. Also feel free to submit feature requests, comments or questions.

Contribute code#

To contribute fixes, code or documentation to Pint, fork Pint in github and submit the changes using a pull request against the master branch.

  • If you are submitting new code, add tests (see below) and documentation.

  • Write “Closes #<bug number>” in the PR description or a comment, as described in the github docs.

  • Log the change in the CHANGES file.

  • Execute pre-commit run --all-files and resolve any issues.

In any case, feel free to use the issue tracker to discuss ideas for new features or improvements.

Notice that we will not merge a PR if tests are failing. In certain cases tests pass in your machine but not in travis. There might be multiple reasons for this but these are some of the most common

  • Your new code does not work for other Python or Numpy versions.

  • The documentation is not being built properly or the examples in the docs are not working.

  • linters are reporting that the code does no adhere to the standards.

Setting up your environment#

If you’re contributing to this project for the fist time, you can set up your environment on Linux or OSX with the following commands:

$ git clone
$ cd pint
$ python -m virtualenv venv
$ source venv/bin/activate
$ pip install -e '.[test]'
$ pip install -r requirements_docs.txt
$ pip install pre-commit # This step and the next are optional but recommended.
$ pre-commit install

Writing tests#

We use pytest for testing. If you contribute code you need to add tests:

  • If you are fixing a bug, add a test to, or amend/enrich the general test suite to cover the use case.

  • If you are adding a new feature, add a test in the appropiate place. There is usually a for each file. There are some other test files that deal with individual/specific features. If in doubt, ask.

  • Prefer functions to classes.

  • When using classes, derive from QuantityTestCase.

  • Use parametrize as much as possible.

  • Use fixtures (see instead of instantiating the registry yourself. Check out the existing fixtures before creating your own.

  • When your test does not modify the registry, use sess_registry fixture.

  • Do not create a unit registry outside a test or fixture setup.

  • If you need a specific registry, and you need to reuse it create a fixture in your test module called local_registry or similar.

  • Checkout for some convenience functions before reinventing the wheel.

Running tests and building documentation#

To run the test suite, invoke pytest from the pint directory:

$ cd pint
$ pytest

To run the doctests, invoke Sphinx’s doctest module from the docs directory:

$ cd docs
$ make doctest

To build the documentation, invoke Sphinx from the docs directory:

$ cd docs
$ make html

Extension Packages#

Pint naturally integrates with other libraries in the scientific Python ecosystem, and a small ecosystem have arisen to aid in compatibility between certain packages allowing to build an

Pint’s rule of thumb for integration features that work best as an extension package versus direct inclusion in Pint is:

  • Extension (separate packages)

    • Duck array types that wrap Pint (come above Pint in the type casting hierarchy

    • Uses features independent/on top of the libraries

    • Examples: xarray, Pandas

  • Integration (built in to Pint)

    • Duck array types wrapped by Pint (below Pint in the type casting hierarchy)

    • Intermingling of APIs occurs

    • Examples: Dask