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Contributing (Azure Automated Machine Learning Samples)

Please follow Python-SDK for general contributing guide.

Pull Requests

Pull requests (PRs) to this repo require review and approval by the Azure Automated Machine Learning team to merge. Please follow the pre-defined template and read all relevant sections below.

Miscellaneous

  • use the existing AutoML environment definition (from the yml files corresponding to each supported OS)
  • use an existing dataset where possible
  • don't modify automl_env_OS.yml files
  • you probably shouldn't modify any files in the root of the repo

Thinking of contributing a new example? Read this first!

A tutorial is a self-contained end-to-end directory with an excellent README.md which can be followed to accomplish something meaningful or teaching how to scale up and out in the cloud. The README.md must clearly state:

  • required prerequisites
  • any one-time setup needed by the user (preferably via setup.sh or similar)
  • any other setup instructions
  • overview of files in the tutorial
  • relevant links

Tutorials are often, but not required to be, a series of ordered Jupyter notebooks. All Jupyter notebooks must utilize notebook features (i.e. be interactive, have explanation in markdown cells, etc).

You should probably ask (open an issue) before contributing a new tutorial. Currently, themes for tutorials include:

Tutorials will need to include frequent automated testing through GitHub Actions. Please run generate_workflows.py to generate the required GitHub workflow which will validate the tutorial on an ongoing basis. Checklist:

  • add the tutorial directory under automl-with-azureml/, following naming conventions
  • add tutorial files (Jupyter notebook & any other required helper files)
  • reference the new tutorial in the README.md describing what it covers
  • run generate_workflows.py, to auto-generate the required GitHub action workflow for automated testing
  • run python readme.py within the /python-sdk/ folder to update the readme.md at that level and ensure an uniform code formatting across the repo
  • test
  • submit PR, which will run your tutorial if set up properly

If this contributing guide has not answered your question(s), please open an issue.