[question] How can I compare function signatures in the typing.Callable syntax to inspect.signature syntax>

[sg-s]

My ultimate goal is to enforce some sort of type for functions that are passed to arguments to other functions.

I have a function that looks like:

def foo(bar: Callable[[int], int]):

I want to implement functionality so that it only accepts functions that look like:

def bar(a: int)->int:

If I inspect bar, I get this:

inspect.signature(bar)
<Signature (a: int) -> int>

How do I work with this and make sure it's the same as the function signature as defined in the Callable syntax?

[JelleZijlstra]

The native typing libraries aren't geared towards supporting this kind of runtime introspection. However, libraries that perform runtime introspection of types should support this. Examples include beartype and pydantic and the type checker I wrote, pyanalyze.

Here's how you could check this with pyanalyze:

from pyanalyze.annotations import type_from_runtime
from pyanalyze.test_value import CTX
from pyanalyze.value import KnownValue
from typing import Callable

cv = type_from_runtime(Callable[[int], int])


def bar(a: int) -> int:
    pass


def bad(a: str) -> int:
    pass

# ok
print(cv.can_assign(KnownValue(bar), CTX)) #  {} (indicating compatibility)

# error
#  type of positional-only parameter '__arg0' is incompatible
#    Cannot assign int to str
print(cv.can_assign(KnownValue(bad), CTX))

[sg-s]

thank you -- does pyanalyze have a wrapper that i can use to enforce type annotations?

[hauntsaninja]

https://github.com/agronholm/typeguard is also a pretty popular option here

[JelleZijlstra]

No, it’s not designed for runtime typechecking. The other tools I mentioned do, though.

…

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