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mypy
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Increasing velocity by modernizing a Python codebase
An expanding monorepo of machine learning workflows became difficult to change safely as contributors and projects multiplied, undermining the velocity it was intended to support. The team replaced requirements.txt with Poetry, using pyproject.toml for direct dependencies and poetry.lock to record transitive dependencies and hashes, while virtual environments simplified setup. Ruff standardized formatting, linting, and CI enforcement; pytest addressed corner cases and bad assumptions, and mypy added annotations and stricter checks that could expose incompatible changes across call sites. To adopt these controls incrementally, the team used ignore comments and staged remediation, including a script for mypy exceptions, while an ignored revision preserved useful git blame history. The resulting codebase was kept in better shape, enabling faster iteration with greater confidence.
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