I am more and more convinced that type checked Python is not always the best idea. The people who are the most virulently pro type checking in Python are not data science folks.
Python's type ecosystem's support for proper type checked data science libraries is abysmal (`nptyping` is pretty much the most feature complete, and it too is far from complete), and has tons of weird bugs.
The Array API standard (https://data-apis.org/array-api/latest/purpose_and_scope.htm...) is a step in the right direction, but until that work is close to some sort of beta version, data science folks will have tons of type errors in their code, in spite of trying their best.