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✏️ Editing: validate_call.py

"""Decorator for validating function calls."""
from __future__ import annotations as _annotations

from typing import TYPE_CHECKING, Any, Callable, TypeVar, overload

from ._internal import _validate_call

__all__ = ('validate_call',)

if TYPE_CHECKING:
    from .config import ConfigDict

AnyCallableT = TypeVar('AnyCallableT', bound=Callable[..., Any])

@overload
def validate_call(
    *, config: ConfigDict | None = None, validate_return: bool = False
) -> Callable[[AnyCallableT], AnyCallableT]:
    ...

@overload
def validate_call(__func: AnyCallableT) -> AnyCallableT:
    ...

def validate_call(
    __func: AnyCallableT | None = None,
    *,
    config: ConfigDict | None = None,
    validate_return: bool = False,
) -> AnyCallableT | Callable[[AnyCallableT], AnyCallableT]:
    """Usage docs: https://docs.pydantic.dev/2.4/concepts/validation_decorator/

Returns a decorated wrapper around the function that validates the arguments and, optionally, the return value.

Usage may be either as a plain decorator `@validate_call` or with arguments `@validate_call(...)`.

Args:
        __func: The function to be decorated.
        config: The configuration dictionary.
        validate_return: Whether to validate the return value.

Returns:
        The decorated function.
    """

def validate(function: AnyCallableT) -> AnyCallableT:
        if isinstance(function, (classmethod, staticmethod)):
            name = type(function).__name__
            raise TypeError(f'The `@{name}` decorator should be applied after `@validate_call` (put `@{name}` on top)')
        return _validate_call.ValidateCallWrapper(function, config, validate_return)  # type: ignore

if __func:
        return validate(__func)
    else:
        return validate

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