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Python

A cleaner Python project structure

A maintainable project structure for machine learning, with packaging, configuration, and testing.

◷ 4 min read · · AI Workbench
A cleaner Python project structure

Separate code from everything else

Keep importable code under src/, tests in tests/ and experiments in notebooks/. A src layout prevents accidental imports from the working directory.

Package and configure it properly

Describe the project in pyproject.toml, pin dependencies and keep configuration in files or environment variables, never hard-coded in modules.

Make it reproducible

Add a lockfile, a short README with setup commands and a test run in CI. A new teammate should go from clone to passing tests in a few minutes.

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