I think designing for static types changes the design of a library’s api. So, in this case, Pandas would likely have to evolve (handwave) in some fashion, if it were to support Mypy types.

One way Mypy could help do this is by implementing a feature like Type Providers https://docs.microsoft.com/en-us/dotnet/fsharp/tutorials/typ...

If you _really_ don't know what type of data you have, you type it as `mixed`. But if you _do_ know the shape of your data, you write your own types, and tell the library about those types (eg; with generics). Think like `my_df: DataFrame<MyDataShape> = pandas.DataFrame(my_data)` where you manually define the shape of `MyDataShape`.

Scala is a language that is often used for data processing, and is statically typed.

Depending on the situation, codegen can also be useful in these situations, eg; https://github.com/typeorm/typeorm

EDIT: in any case, this certainly answers my question :-) sounds like they're not there yet, and perhaps not even moving in that direction yet.