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Support for specifying type parameters at function call time (like func[int]()) with runtime introspection
#2199
jonathanslenders
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Here is an improved implementation that adds support for from types import FunctionType
from typing import TypeVar, Any, Protocol, Callable
from functools import wraps, cache
__all__ = [
"GenericFunction",
"generic_function",
]
class GenericFunction[**P, R](Protocol):
def __call__(self, *a: P.args, **kw: P.kwargs) -> R: ...
def __getitem__(self, params: Any) -> Callable[P, R]: ...
def generic_function[**P, R](func: Callable[P, R]) -> GenericFunction[P, R]:
"""
Function decorator that allows calling a generic function with type
parameters, and expose the actual types within the function.
"""
class wrapper:
@cache
def __getitem__(self, type_params: TypeVar | tuple[TypeVar, ...]) -> Callable[P, R]:
if not isinstance(type_params, tuple):
type_params = (type_params,)
# Map typevar names to types that we receive in vars.
typevar_name_to_type = {
name: type_ for type_, name in zip(type_params, func.__type_params__)
}
# Helper for creating a function closure.
def make_cell(value: object) -> Any:
def inner() -> object:
return value
return inner.__closure__[0] # type:ignore[index]
# Create a new closure for the given function by replacing the type
# variables with the actual types.
def replace_closure(f: FunctionType) -> tuple[Any, ...]:
closure = []
for cell in f.__closure__: # type:ignore[union-attr]
contents = cell.cell_contents
if isinstance(contents, TypeVar):
closure.append(make_cell(typevar_name_to_type[contents]))
elif hasattr(contents, "__closure__"):
closure.append(make_cell(replace_func(contents)))
else:
closure.append(cell)
return tuple(closure)
def replace_func(f: FunctionType) -> FunctionType:
return FunctionType(
f.__code__,
f.__globals__,
name=f.__name__,
argdefs=f.__defaults__,
closure=replace_closure(f),
)
return replace_func(func) # type:ignore[arg-type]
# `__call__` staticmethod to make `inspect.signature` work on the
# `GenericFunction`.
@staticmethod
@wraps(func)
def __call__(*a: P.args, **kw: P.kwargs) -> R:
return func(*a, **kw)
wrapper.__doc__ = func.__doc__
return wrapper()Example usage: from contextlib import contextmanager
from typing import Generator
from typing import TYPE_CHECKING
import inspect
@generic_function
def func[T, U](data: T, data2: U) -> tuple[T, U]:
"Docstring"
# XXX: Here mypy complains we can't use it T at runtime, but now we can!
print("Type of T=", T)
print("Type of U=", U)
print("value of data=", data, data2)
return (data, data2)
@generic_function
@contextmanager
def cm_func[T, U](data: T, data2: U) -> Generator[tuple[T, U]]:
"Generic context manager."
print("Type of T=", T)
print("Type of U=", U)
print("value of data=", data, data2)
yield (data, data2)
with cm_func[int, bool](4, True) as (a, b):
if TYPE_CHECKING:
reveal_type(a)
reveal_type(b)
c, d = func[int, str](4, "test")
if TYPE_CHECKING:
reveal_type(c)
reveal_type(d)
reveal_type(func[int, str]) # XXX: not yet inferred correctly!
print("Docstrings:")
print("doc=", cm_func.__doc__)
print("doc=", func.__doc__)
print("Signature:")
print(inspect.signature(cm_func)) # Incorrect due to `@contextmanager`, but also without `@generic_function`
print(inspect.signature(func))Looks like Mypy has some rough edge cases where not everything is well supported, but overall it works great. |
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tl;dr: proof-of-concept decorator at the bottom to make
func[int]()work with runtime support.This has been discussed before:
We have a justification from the Pydantic world where runtime support is important. Imagine this:
In this case, the
[T]is not really needed for the type checkers, because they can infer it from thedataargument. But Pydantic needs to know the type parameters at runtime in order to properly deserialize/serialize. So, within the function, we have to be able to resolve the runtime value.The Mypy docs suggests to use a generic class with a call
__call__, however I think that would require an extra pair of parentheses. Anyio has a creative solution by turning the function into a class that inherits from a typed tuple with a__new__, but that only works for functions that return multiple arguments.https://github.com/agronholm/anyio/blob/master/src/anyio/_core/_streams.py#L16
The anyio approach however doesn't provide runtime access to the value of T due to
__orig_class__not being available in__new__(for doingget_args(self.__orig_class__)).What I came up with is a use of
__class__getitem__and creating a newFunctionTypewhere the cells in the__closure__are replaced with the actual types.This approach can also be combined with other decorators like
contextmanager:(edit: the following snippet does not work - to make it work with
contextmanagerwe have to dig recursively through the closure and replace the typevars everywhere.)Is this a reasonable approach? Would it make sense for Python itself to do something similar and substitute the closure?
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