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 →

16Python repos scanned
4no dependency cache
15no job timeout
14no concurrency guard
0fully clean
RepoRuns (30d)CI min (30d)Recoverable min/moFailure rateFindings
python/mypypip500+6,8621,4945%8
numpy/numpypip500+8,0799221%47
sqlalchemy/sqlalchemypip1325,15750020%6
pydantic/pydanticpip500+2,58022515%21
fastapi/fastapipip500+947809%23
psf/blackpip500+1,073704%34
huggingface/transformerspip500+3,602527%33
psf/requestspip1371374223%16
aio-libs/aiohttppip500+1,455409%17
python-poetry/poetrypip127500324%10
scikit-learn/scikit-learnpip500+803143%26
scrapy/scrapypip500+7,12843%17
pytest-dev/pytestpip500+8,26119%6
pandas-dev/pandaspip500+4,374111%28
django/djangopip500+51305%14
pallets/flaskpip109330040%9

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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