Contributing

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 github:fqlearn/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.

Submit Feedback

The best way to send feedback is to file an issue at github:fqlearn/issues.

If you are proposing a 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!

For development, we encourage you to use conda. If you don't know what is that, check these links:

• https://docs.conda.io/en/latest/

We recommend you to use mamba-forge, a combination of miniconda + conda-forge + mamba. You can download it from here: https://github.com/conda-forge/miniforge#mambaforge

Ready to contribute? Here’s how to set up fqlearn for local development.

1. Clone this repository locally:

$ git clone git@github.com:osl-pocs/fqlearn.git

1. Create a conda environment and activate it:

$ cd fqlearn
$ mamba env create --file conda/base.yaml

and

$ conda activate fqlearn

1. Install your local project copy into your conda environment:

$ poetry install

1. Create a branch for local development:

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

1. When you’re done making changes, check that your changes pass flake8 and the tests, including testing other Python versions with tox:

$ pytest

1. 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

1. 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, and add the feature to the list in README.rst.
3. The pull request should work for Python == 3.10

Tips

Commit message format

semantic-release uses the commit messages to determine the consumer impact of changes in the codebase. Following formalized conventions for commit messages, semantic-release automatically determines the next semantic version number, generates a changelog and publishes the release.

By default, semantic-release uses Angular Commit Message Conventions. The commit message format can be changed with the preset or config options_ of the @semantic-release/commit-analyzer and @semantic-release/release-notes-generator plugins.

Tools such as commitizen or commitlint can be used to help contributors and enforce valid commit messages.

The table below shows which commit message gets you which release type when semantic-release runs (using the default configuration):

Commit message	Release type
fix(pencil): stop graphite breaking when pressure is applied	Fix Release
feat(pencil): add 'graphiteWidth' option	Feature Release
perf(pencil): remove graphiteWidth option	Chore
fix!: The graphiteWidth option has been removed	Breaking Release

source: https://github.com/semantic-release/semantic-release/blob/master/README.md#commit-message-format

As this project uses the squash and merge strategy, ensure to apply the commit message format to the PR's title.