I got curious about what actually is a blocker in terms of time complexity, for python. I’ve always known that the smaller the complexity the better, but it’s never quantitative. How bad is n^2? How bad is n^n? How much of an improvement is sqrt(n) or log(n)? What is outrageous to write and is absolutely no-go?
Either with pip:
pip install git+https://github.com/psf/black.git@1aa4d5bOr with pipx, which looks like a python equivalent of npx, and allows direct runs without installation, or for multiple versions to co-exist:
pipx install git+https://github.com/psf/black.git@1aa4d5bRef: [1]
A bit of a hack. So that whenever there is a request, its response will be recorded:
@pytest.fixture(autouse=True)
def stripe_vcr(vcr, request):
filename = f"{request.function.__module__}/{request.node.name}.yaml"
with vcr._use_cassette(path=filename):
yieldhttps://pytest-vcr.readthedocs.io/en/latest/configuration/#vcr
In simple terms:
flush and commit, later queries will be able to retrieve these changes.flush() changes are in a pending state (no db statements are issued yet), and can be undone by rollback(); commits are persisted to db and non-reversible.Why use flush:
Github actions getting stuck in limbo, never starting. No fear! There is a solution!
Continue readingError running pre-commit:
Type tag 'jupyter' is not recognized. Try upgrading identify and pre-commit?>>> dance.__name__
'dance'>>> callable(foo)
True/FalseSometimes data is corrupted, and you just want to nuke the whole world and start a new life. In which case do:
$ docker container prune
$ docker volume prune