Pyantic and Cattrs both suffer with unacceptable issues and footguns. I have used Pydantic in production a lot and have played around with Cattrs. I've also loo

Pyantic and Cattrs both suffer with unacceptable issues and footguns. I have used Pydantic in production a lot and have played around with Cattrs. I've also looked at similar libraries like Dacite and marshmallow-dataclasses but none seem to be well thought out and mature. * Neither Pydantic nor Cattrs handle unions like how I'd expect (although Cattrs has stronger guarantees in converting Unions) >>> class Y(BaseModel): pass >>> class X(BaseModel): pass >>> class Z(BaseModel): a: Union[X, Y] >>> Z(a=Y()) Z(a=X()) # Converts Y to X implicitly Cattrs has some problems with generics [1] [2]. Dacite and marshmallow-dataclasses don't support generics well either, with some issues around Union types. They do work well for simple python types but what I'd like to see is guarantee that the serialisation operation is completely reversible and if not raise warning/exception. [1] https://github.com/Tinche/cattrs/issues/149 https://github.com/Tinche/cattrs/issues/149 [2] https://github.com/Tinche/cattrs/issues/44 https://github.com/Tinche/cattrs/issues/44