You can still have extensive "compile-time" checking with linters and static type checkers. This makes Polars even better in typed Python, as it type-checks much better than the dynamic mess that is Pandas.
Python's linters leave many holes unfilled - it catches some stuff but still leaves everything else to the runtime. Literally every Python application that I've worked on in the last 3 years a) is 100% type checked yet b) still hits massive numbers of novel runtime errors on the regular. Python's anemic type system is in no way a substitute for an advanced compiler.
> I do have type and dirty data problems of the dataframes/csvs/parquet I'm reading.
Something about those two statements makes my brain explode. You rarely have type problems, except when dealing with data? Isn't the whole point of a program to deal with data?
I get where you're coming from. A good type system should provide invariant guarantees about runtime behavior. But Python's does not.