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 requests 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 external contributions to Gurobi Machine Learning. Note that all contributors should accept the Contributor License Agreement (CLA).
To contribute code you should 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, tests will be run, 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.
The core maintainer that reviewed the pull request will merge it after all comments have been addressed and when all tests are passing.