Thanks for considering contributing! Please read this document to learn the various ways you can contribute to this project and how to go about doing it.

Bug reports and feature requests#

Did you find a bug?#

First, do a quick search to see whether your issue has already been reported. If your issue has already been reported, please comment on the existing issue.

Otherwise, open a new GitHub issue. Be sure to include a clear title and description. The description should include as much relevant information as possible. The description should explain how to reproduce the erroneous behavior as well as the behavior you expect to see. Ideally you would include a code sample or an executable test case demonstrating the expected behavior.

Do you have a suggestion for an enhancement or new feature?#

We use GitHub issues to track feature requests. Before you create an feature request:

  • Make sure you have a clear idea of the enhancement you would like. If you have a vague idea, consider discussing it first on a GitHub issue.

  • Check the documentation to make sure your feature does not already exist.

  • Do a quick search to see whether your feature has already been suggested.

When creating your request, please:

  • Provide a clear title and description.

  • Explain why the enhancement would be useful. It may be helpful to highlight the feature in other libraries.

  • Include code examples to demonstrate how the enhancement would be used.

Making a pull request#

When you’re ready to contribute code to address an open issue, please follow these guidelines to help us be able to review your pull request (PR) quickly.

  1. Initial setup (only do this once)

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    If you haven’t already done so, please fork this repository on GitHub.

    Then clone your fork locally with

     git clone


     git clone

    At this point the local clone of your fork only knows that it came from your repo,, but doesn’t know anything the main repo, You can see this by running

     git remote -v

    which will output something like this:

     origin (fetch)
     origin (push)

    This means that your local clone can only track changes from your fork, but not from the main repo, and so you won’t be able to keep your fork up-to-date with the main repo over time. Therefore you’ll need to add another “remote” to your clone that points to To do this, run the following:

     git remote add upstream

    Now if you do git remote -v again, you’ll see

     origin (fetch)
     origin (push)
     upstream (fetch)
     upstream (push)

    Finally, you’ll need to create a Python 3 virtual environment suitable for working on this project. There a number of tools out there that making working with virtual environments easier, but the most direct way is with the venv module in the standard library.

    Once your virtual environment is activated, you can install your local clone in “editable mode” with

     pip install -U pip setuptools wheel
     pip install -e .[dev]

    The “editable mode” comes from the -e argument to pip, and essential just creates a symbolic link from the site-packages directory of your virtual environment to the source code in your local clone. That way any changes you make will be immediately reflected in your virtual environment.

  2. Ensure your fork is up-to-date

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    Once you’ve added an “upstream” remote pointing to, keeping your fork up-to-date is easy:

     git checkout main  # if not already on main
     git pull --rebase upstream main
     git push
  3. Create a new branch to work on your fix or enhancement

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    Commiting directly to the main branch of your fork is not recommended. It will be easier to keep your fork clean if you work on a seperate branch for each contribution you intend to make.

    You can create a new branch with

     # replace BRANCH with whatever name you want to give it
     git checkout -b BRANCH
     git push -u origin BRANCH
  4. Test your changes

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    Our continuous integration (CI) testing runs a number of checks for each pull request on GitHub Actions. You can run most of these tests locally, which is something you should do before opening a PR to help speed up the review process and make it easier for us.

    First, you should run isort and black to make sure you code is formatted consistently. Many IDEs support code formatters as plugins, so you may be able to setup isort and black to run automatically everytime you save. For example, black.vim will give you this functionality in Vim. But both isort and black are also easy to run directly from the command line. Just run this from the root of your clone:

     isort .
     black .

    Our CI also uses flake8 to lint the code base and mypy for type-checking. You should run both of these next with

     flake8 .


     mypy .

    We also strive to maintain high test coverage, so most contributions should include additions to the unit tests. These tests are run with pytest, which you can use to locally run any test modules that you’ve added or changed.

    For example, if you’ve fixed a bug in cached_path/a/, you can run the tests specific to that module with

     pytest -v tests/a/

    Our CI will automatically check that test coverage stays above a certain threshold (around 90%). To check the coverage locally in this example, you could run

     pytest -v --cov cached_path.a.b tests/a/

    If your contribution involves additions to any public part of the API, we require that you write docstrings for each function, method, class, or module that you add. See the Writing docstrings section below for details on the syntax. You should test to make sure the API documentation can build without errors by running

     make docs

    If the build fails, it’s most likely due to small formatting issues. If the error message isn’t clear, feel free to comment on this in your pull request.

    And finally, please update the CHANGELOG with notes on your contribution in the “Unreleased” section at the top.

    After all of the above checks have passed, you can now open a new GitHub pull request. Make sure you have a clear description of the problem and the solution, and include a link to relevant issues.

    We look forward to reviewing your PR!

Writing docstrings#

We use Sphinx to build our API docs, which automatically parses all docstrings of public classes and methods. All docstrings should adhere to the Numpy styling convention.