How popular Python repos run GitHub Actions

Python CI has the cheapest speedup in Actions: setup-python caches pip with one line (cache: 'pip'), yet plenty of workflows still reinstall requirements on every run. Here is how well-known Python projects actually run CI, gaps included. Read the fix →

17Python repos scanned
5no dependency cache
14no job timeout
15no concurrency guard
1fully clean
RepoRuns (30d)CI min (30d)Recoverable min/moFailure rateFindings
python/mypypip1,1267,091*1,5433%8
sqlalchemy/sqlalchemypip16110.7k97413%11
psf/blackpip1,5277,743*4739%27
numpy/numpypip2,5002,914*3251%49
pydantic/pydanticpip1,4863,434*26912%21
fastapi/fastapipip1,975640*588%23
python-poetry/poetrynpm3611,810568%16
huggingface/transformerspip2,5001,739*287%33
aio-libs/aiohttppip2,5001,645*226%19
psf/requestspip10991164%13
scikit-learn/scikit-learnpip2,500725*52%19
scrapy/scrapypip2,30513.0k*47%11
pytest-dev/pytestpip53718.7k*120%6
pandas-dev/pandaspip2,5005,844*03%28
django/djangopip2,500469*02%13
pallets/flaskpip5017014%8
encode/httpx110100%clean

* CI min, recoverable min and failure rate cover only the latest 500 runs of a repo with more in 30 days.

Public data from each repo's GitHub Actions. Minutes are wall-clock workflow time over 30 days. These repos run Actions free (public repos always do). Each scorecard shows the private-repo dollar equivalent as a labeled estimate. Repo owners can remove their scorecard any time.

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