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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 https://github.com/automl/CARP-S/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 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#

CARP-S could always use more documentation, whether as part of the official CARP-S 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 github.com/automl/CARP-S/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!#

Ready to contribute? Here's how to set up CARP-S for local development.

Fork the CARP-S repo on GitHub and then clone your fork locally: 

git clone git@github.com:YOUR_NAME_HERE/CARP-S.git
cd CARP-S

Install your local copy into a virtualenv. We'll also install pre-commit which runs some code quality checks. 

python -m venv .venv
pip install -e ".[dev]"
pre-commit install

Create a branch for local development: 

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

Now you can make your changes locally!

When you're done making changes, check that your changes pass ruff, including testing other Python versions: 

python setup.py test or pytest
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
Submit a pull request through the GitHub website!

Local Development#

Virtual Environments#

You can try to install all dependencies into one big environment, but probably there are package clashes. Therefore, you can build one virtual environment for each optimizer-benchmark combination. Either run scripts/build_envs.sh to build all existing combinations or copy the combination and run as needed. It will create an environment with name automlsuite_${OPTIMIZER_CONTAINER_ID}_${BENCHMARK_ID}.

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.md.
  3. The pull request should work for Python 3.9 and make sure that the tests pass for all supported Python versions.

Testing#

To run a subset of tests: 

pytest tests/some_file.py  # Run tests only in a certain file
pytest -k "test_mytest"  # Find tests with a name matching "test_mytest"

Deploying#

A reminder for the maintainers on how to deploy. Make sure all your changes are committed (including an entry in CHANGELOG.md).

Update the version in pyproject.toml, then run:

git tag "x.y.z"  # Replace with your version
git push
git push --tags