Python code feels like back in the day when JavaScript was typed using JSDoc comments, and libraries would use all kinds of fantastical object shapes for their option parameters, so users could pass "just about anything" and it would work. You would never know how to configure an Express app without digging through the documentation, for example.
I loathe the Python convention of just using kwargs instead of clearly annotated parameters; most libraries don't even have doc comments in the code, so you're really required to look up the documentation, hope that it actually describes the method you're interested in and contains more than stuff like "foo: the foo to use"βor fall back to rummaging in the library intestines to figure out how it works.
I'm not sure into what kind of industry you're in, but having most functions as (args, *kwargs) is not the way I deal with most of my code and the libraries I work at all (backend development). Everything is typed fully.
Maybe you're in a niche spot, or using scientist-based code. I've seen plenty of trainwrecks in 'conda-only' ""libraries"" done by scientists. Maybe that's the niche you're at?
Sometimes, though, you may get lucky, and find some tests for the code you want to use!
On a more serious note, I can't even blame library devs as long as they try. Type "hints" often are anything but _just_ hints. Some are expected to be statically checked; some may alter runtime behavior (e.g. the @overload decorator). It's like the anti-pattern of TypeScript's enums laid out here and there, and it's even harder to notice such side-effects in Python.
I loathe the Python convention of just using kwargs instead of clearly annotated parameters; most libraries don't even have doc comments in the code, so you're really required to look up the documentation, hope that it actually describes the method you're interested in and contains more than stuff like "foo: the foo to use"βor fall back to rummaging in the library intestines to figure out how it works.
It's pathetic.