They are different, but on some fundamental level when you're writing code you're expressing an idea and it is still the same. The same way photograph and drawing of a cat are obviously different and they're made in vastly different ways, but still they're representations of a cat. It's all lambda calculus, turing machines, ram machines, combinator logic, posts' dominoes etc., etc. in the end.

They’re both turing complete, which make them equivalent.

Code is a description of a solution, which can be executed by a computer. You have the inputs and the outputs (we usually split the former into arguments amd environment, and we split the latter into side effects and return values). Python and Haskell are just different towers of abstraction built on the same computation land. The code may not be the same, but the relation between inputs and outputs does not change if they solve the same problem.

> The paradigms literally are different. […] They’re extremely far apart.

And yet, you can write pure-functional thunked streams in Python (and have the static type-checker enforce strong type checking), and high-level duck-typed OO with runtime polymorphism in Haskell.

The hardest part is getting a proper sum type going in Python, but ducktyping comes to the rescue. You can write `MyType = ConstructA | ConstructB | ConstructC` where each ConstructX type has a field like `discriminant: Literal[MyTypeDiscrim.A]`, but that's messy. (Technically, you can use the type itself as a discriminant, but that means you have to worry about subclasses; you can fix that by introducing an invariance constraint, or by forbidding subclasses….) It shouldn't be too hard to write a library to deal with this nicely, but I haven't found one. (https://pypi.org/project/pydantic-discriminated/ isn't quite the same thing, and its comparison table claims that everything else is worse.)