I disagree about the speed. I don't have a problem with pyflake, but running `time ruff -s .` in a project with 1,236 Python files took 78ms. At that speed, it could re-check the file I'm working on in an editor after every keystroke with no noticeable latency. It's not just a little bit faster. It's freakishly, ridiculously, gone-plaid faster.
Edit: for comparison, flake8 took 8.19s and found approximately the same number of issues. pyflakes took 4.49s and found fewer.
That’s not true unless you have a dependency map between all modules. (Note: that’s what I did in pytest-fastest to only retest modules that had changed, or that imported modules that had changed.) Otherwise, if you rename a function, you wouldn’t know what all broke.
Edit: for comparison, flake8 took 8.19s and found approximately the same number of issues. pyflakes took 4.49s and found fewer.