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Guidelines for Contributing

CausalPy welcomes contributions from interested individuals or groups. These guidelines are provided to give potential contributors information to make their contribution compliant with the conventions of the CausalPy project, and maximize the probability of such contributions are merged as quickly and efficiently as possible. Contributors need not be experts, but should be interested in the project, willing to learn, and share knowledge.

There are 4 main ways of contributing to the CausalPy project (in ascending order of difficulty or scope):

  1. Submitting issues related to bugs or desired enhancements.
  2. Contributing or improving the documentation (docs) or examples.
  3. Fixing outstanding issues (bugs) with the existing codebase. They range from low-level software bugs to higher-level design problems.
  4. Adding new or improved functionality to the existing codebase.

Items 2-4 require setting up a local development environment, see Local development steps for more information.

Opening issues

We appreciate being notified of problems with the existing CausalPy code. We prefer that issues be filed the on Github Issue Tracker, rather than on social media or by direct email to the developers.

Please verify that your issue is not being currently addressed by other issues or pull requests by using the GitHub search tool to look for key words in the project issue tracker.

Contributing code via pull requests

While issue reporting is valuable, we strongly encourage users who are inclined to do so to submit patches for new or existing issues via pull requests. This is particularly the case for simple fixes, such as typos or tweaks to documentation, which do not require a heavy investment of time and attention.

Contributors are also encouraged to contribute new code to enhance CausalPy's functionality, via pull requests.

The preferred workflow for contributing to CausalPy is to fork the GitHub repository, clone it to your local machine, and develop on a feature branch.

For more instructions see the Pull request checklist

Local development steps

  1. If you have not already done so, fork the project repository by clicking on the 'Fork' button near the top right of the main repository page. This creates a copy of the code under your GitHub user account.

  2. Clone your fork of the CausalPy repo from your GitHub account to your local disk, and add the base repository as a remote:

    git clone [email protected]:<your GitHub handle>/CausalPy.git
cd CausalPy
git remote add upstream [email protected]:pymc-labs/CausalPy.git

  3. Create a feature branch (e.g. my-feature) to hold your development changes:

    git checkout -b my-feature

    Always use a feature branch. It's good practice to never routinely work on the main branch of any repository.

  4. Create the environment from the environment.yml file.

    mamba env create -f environment.yml

    Activate the environment.

    conda activate CausalPy

    Install the package (in editable mode) and its development dependencies. The --no-deps flag is used to avoid installing the dependencies of CausalPy as they are already installed when installing the development dependencies. This can end up interfering with the conda-only install of pymc.

    pip install --no-deps -e .

    Install development dependencies

    pip install 'causalpy[dev]'
pip install 'causalpy[docs]'
pip install 'causalpy[test]'
pip install 'causalpy[lint]'
pip install 'pylint'

    It may also be necessary to install pandoc. On a mac, run brew install pandoc.

    Set pre-commit hooks

    pre-commit install

    If you are editing or writing new examples in the form of Jupyter notebooks, you may have to run the following command to make Jupyter Lab aware of the CausalPy environment.

    python -m ipykernel install --user --name CausalPy

  5. You can then work on your changes locally, in your feature branch. Add changed files using git add and then git commit files:

    git add modified_files
git commit -m "Message summarizing commit changes"

    to record your changes locally. After committing, it is a good idea to sync with the base repository in case there have been any changes:

    git fetch upstream
git rebase upstream/main

    Then push the changes to your GitHub account with:

    git push -u origin my-feature

  6. Before you submit a Pull Request, follow the Pull request checklist.

  7. Finally, to submit a pull request, go to the GitHub web page of your fork of the CausalPy repo. Click the 'Pull request' button to send your changes to the project's maintainers for review. This will send an email to the committers.

Pull request checklist

We recommend that your contribution complies with the following guidelines before you submit a pull request:

  • If your pull request addresses an issue, please use the pull request title to describe the issue and mention the issue number in the pull request description. This will make sure a link back to the original issue is created.

  • All public methods must have informative docstrings with sample usage when appropriate.

  • Example usage in docstrings is tested via doctest, which can be run via

    make doctest

  • Doctest can also be run directly via pytest, which can be helpful to run only specific tests during development. The following commands run all doctests, only doctests in the pymc_models module, and only the doctests for the PyMCModel class in pymc_models:

    pytest --doctest-modules causalpy/
pytest --doctest-modules causalpy/pymc_models.py
pytest --doctest-modules causalpy/pmyc_models.py::causalpy.pymc_models.PyMCModel

  • To indicate a work in progress please mark the PR as draft. Drafts may be useful to (1) indicate you are working on something to avoid duplicated work, (2) request broad review of functionality or API, or (3) seek collaborators.

  • All other tests pass when everything is rebuilt from scratch. Tests can be run with:

    make test

  • When adding additional functionality, either edit an existing example, or create a new example (typically in the form of a Jupyter Notebook). Have a look at other examples for reference. Examples should demonstrate why the new functionality is useful in practice.

  • Documentation and high-coverage tests are necessary for enhancements to be accepted.

  • Documentation follows NumPy style guide

  • If you have changed the documentation, you should build the docs locally and check that the changes look correct.

  • Run any of the pre-existing examples in CausalPy/docs/source/* that contain analyses that would be affected by your changes to ensure that nothing breaks. This is a useful opportunity to not only check your work for bugs that might not be revealed by unit test, but also to show how your contribution improves CausalPy for end users.

  • Your code passes linting tests. Run the line below to check linting errors:

    make check_lint

    If you want to fix linting errors automatically, run

    make lint

Building the documentation locally

A local build of the docs is achieved by:

cd docs
make html

Sometimes not all changes are recognised. In that case run this (again from within the docs folder):

make clean && make html

Docs are built in docs/_build, but these docs are not committed to the GitHub repository due to .gitignore.

Overview of code structure

Classes

Packages

UML diagrams can be created with the command below.

make uml

This guide takes some inspiration from the Bambi guide to contributing