Any opinions about the current state of the art type checker?
Main tradeoff is this only works if your codebase/core dependencies are typed. For a while that was not true and we used pylint + pyright. Eventually most of our code is typed and we added type stubs for our main untyped dependencies.
edit: Also on pylint, it did work well mostly. tensorflow was main library that created most false positives. Other thing I found awkward was occasionally pylint produces non-deterministic lints on my codebase.
Besides re-adding features that Microsoft makes exclusive to pylance, it tweaks a number of features that IMO makes pyright work better out the box:
https://docs.basedpyright.com/latest/benefits-over-pyright/p...
You can use an extension fork which swaps it with NetCoreDbg maintained by Samsung instead. This is what VSCodium uses.
Also note that both of these essentially consume the debugger API exposed by the runtime itself, you can easily make one yourself in a weekend but no one bothered because there isn't much need for another one.
Code Name is Red Knot: https://github.com/astral-sh/ruff/discussions/12143
For typechecker, I also vouch for Pyright which is what we use for all our django backends at work.
Just be aware that you will have hard time to typecheck part of your code where you rely heavily on django's magic (magic strings, auto-generated properties/methods, etc...).
In these cases, it's sometimes better to avoid these features entirely or accept that some part of your code will not be typechecked.