Fair enough. I'm not sure what fueled this idea that marking variables with types will make the code faster. Cython? I think part of the issue, too, is that in Python type annotations are really just fancy comments. If you mark a function as taking ints in Python and stick a double in, at most your editor or mypy will complain. If you do it in Julia, it's a compilation error. Tangent: JET.jl might catch these sorts of issues for you and I think has linter support in VS Code now or imminently.
I'm not sure being able to subtype concrete types will help with the specific issue you're showing here. Really the right thing to do is make the function take Numbers. If you allowed Int to be subtyped, things would still be semantically wrong, and you would have introduced a parallel inheritance tree that will break a lot of the interoperability multiple dispatch enables.
I'm not sure being able to subtype concrete types will help with the specific issue you're showing here. Really the right thing to do is make the function take Numbers. If you allowed Int to be subtyped, things would still be semantically wrong, and you would have introduced a parallel inheritance tree that will break a lot of the interoperability multiple dispatch enables.