Code quality tools

For .py files:

  • black: Code formatting
  • mypy: Optional static type checking
  • isort: Sorting imports sanely
  • pylance: Fast code quality checking in VSCode

For Jupyter notebooks:

  • nbqa: Run any file checker that would run on .py files instead on .ipynb notebooks.
  • nbstripout: Strip outputs from Jupyter notebooks to make them clean before committing.

Data scientists should learn how to write good code

Data scientists are most commonly writing and developing custom code. It's the most flexible way to write all the abstractions that are needed. By writing custom code, we need some tools to help with code quality.