AlkantarClanX12
Your IP : 18.223.206.84
"""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