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CONTRIBUTING.md

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Development workflow

The current workflow is the following:

  1. Open an issue to describe your feature request or your bug fix with a detailed explanation of what you want to achieve.
  2. Fork the repo
  3. Develop locally:
    • Install the precommit file (pip install pre-commit, then pre-commit install)
    • Create a branch based on the master branch (git checkout -b <prefix-branchname> master)
    • Create a conda environment (conda create -n python==3.10)
    • Activate this environment (conda activate <your-env-name>)
    • Install the extra dependencies for tests (pip install kedro-mlflow[dev,test])
    • Apply your changes
    • Run pre-commit (black linting, flake8 errors, isort with pre-commit run)
  4. Submit your changes:
    • Ensure test coverage is still 100%
    • Update documentation accordingly
    • Update CHANGELOG.md according to "Keep a Changelog" guidelines
    • Squash all the changes within a single commit as much as possible, and ensure the commit message has the format ":gitmoji_icon: Informative description (#<issue-number>)"
    • Rebase your branch on master to ensure linear history
    • Open a pull request against master
  5. Ask for review:
    • Assign the review @Galileo-Galilei
    • Wait for review
    • Resolve all discussions (go back to step 3.)
  6. The PR will be merged as soon as possible

We reserve the right to take over (suppress or modify) PR that do not match the workflow or are abandoned.

Release workflow

  1. Check the issues:
    • Ensure all the release issues are completed. Eventually move the not addressed yet issues to a further release.
    • Create a new milestone
  2. Create the release candidate:
  3. If the workflow has run sucessfully:
    • Go to the newly openened PR named "Release candidate <version>"
    • Check that changelog and version have been properly updated.
    • (If everything is normal, skip this step) Eventually pull the branch and make changes if necessary
    • Merge the PR to master
  4. Checkout the publish workflow to see if:
    • The package has been uploaded on PyPI sucessfully
    • A Github release has been created
  5. If the pipeline has failed, please raise an issue to correct the CI, and ensure merge on master manually.