Welcome to Gurobi Machine Learning!
We value your experience in using Gurobi Machine Learning and would like to encourage you to contribute directly to this project.
If you encounter a bug, or you think there is a need for a new feature, we recommend to first add the bug report or feature request to the Gurobi Machine Learning's GitHub issue tracker.
It would be great if you add a minimal reproducible example when reporting a bug, or include reasoning on how the new requested feature improves the code.
We welcome your contribution in directly tackling some of the issues.
We use the GitHub pull request workflow. Once your pull request is ready for review, one of the core maintainers of Gurobi Machine Learning will review your pull request.
A pull request should contain tests for the changes made to the code behavior, should include a clear message outlining the changes done, and should be linked to an existing issue.
Before submitting a pull request:
- install the pre-commit package to enable the automatic
running of the pre-commit hooks in the
.pre-commit-configuration.yamlfile, - make sure all tests pass by running
toxin the root folder of thegurobi-machinelearning. - add any other relevant checks for your changes to Gurobi Machine Learning.
After a pull request is submitted, the tests will be run automatically, and the status will appear on the pull request page. If the tests failed, there is a link which can be used to debug the failed tests.
The pull request author should respond to all comments received. If the comment has been accepted and appropriate changes applied, the author should respond by a short message such as "Done" and then resolve the comment. If more discussion is needed on a comment, it should remain open until a solution can be figured out.
Explicit approval and passing tests are required before merging. The pull request author should always merge via "Squash and Merge" and the remote pull request branch should be deleted.