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Contributing to datadivr

Contributions are welcome, and they are greatly appreciated! Every little bit helps, and credit will always be given.

You can contribute in many ways:

Types of Contributions

Report Bugs

Report bugs at https://github.com/menchelab/datadivr/issues

If you are reporting a bug, please include:

  • Your operating system name and version.
  • Any details about your local setup that might be helpful in troubleshooting.
  • Detailed steps to reproduce the bug.

Fix Bugs

Look through the GitHub issues for bugs. Anything tagged with "bug" and "help wanted" is open to whoever wants to implement a fix for it.

Implement Features

Look through the GitHub issues for features. Anything tagged with "enhancement" and "help wanted" is open to whoever wants to implement it.

Write Documentation

datadivr could always use more documentation, whether as part of the official docs, in docstrings, or even on the web in blog posts, articles, and such.

Submit Feedback

The best way to send feedback is to file an issue at https://github.com/menchelab/datadivr/issues.

If you are proposing a new feature:

  • Explain in detail how it would work.
  • Keep the scope as narrow as possible, to make it easier to implement.
  • Remember that this is a volunteer-driven project, and that contributions are welcome :)

Get Started!

Ready to contribute? Here's how to set up datadivr for local development. Please note this documentation assumes you already have uv and Git installed and ready to go.

1. Fork the datadivr repo on GitHub.

2. Clone your fork locally:

cd <directory_in_which_repo_should_be_created>
git clone git@github.com:menchelab/datadivr.git

3. Now we need to install the environment. Navigate into the directory

cd datadivr

Then, install and activate the environment with:

uv sync

4. Install pre-commit to run linters/formatters at commit time:

uv run pre-commit install

5. Create a branch for local development:

git checkout -b name-of-your-bugfix-or-feature

6. Alternatively you can use vscode devcontainer feature which only requires you to have vscode and docker desktop installed, when you open the project in vscode install the extension and click the reopen in container button

Now you can make your changes locally.

6. Don't forget to add test cases for your added functionality to the tests directory.

7. When you're done making changes, check that your changes pass the formatting tests.

make check

Now, validate that all unit tests are passing:

make test

9. Before raising a pull request you should also run tox. This will run the tests across different versions of Python:

uv run tox

10. Commit your changes and push your branch to GitHub:

git add .
git commit -m "Your detailed description of your changes."
git push origin name-of-your-bugfix-or-feature

When writing commit messages, please follow the Conventional Commits specification. This helps maintain a standardized commit history and enables automated tooling. The basic format is:

<type>[optional scope]: <description>

[optional body]

[optional footer(s)]

Common types include:

  • feat: A new feature
  • fix: A bug fix
  • docs: Documentation changes
  • style: Code style changes (formatting, etc.)
  • refactor: Code changes that neither fix bugs nor add features
  • test: Adding or modifying tests
  • chore: Changes to build process or auxiliary tools

Example commit messages:

feat(api): add new data validation endpoint
fix: correct memory leak in processing loop
docs: update installation instructions

11. Submit a pull request through the GitHub website.

Pull Request Guidelines

Before you submit a pull request, check that it meets these guidelines:

1. The pull request should include tests.

2. If the pull request adds functionality, the docs should be updated. Put your new functionality into a function with a docstring.