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Filename :
validate_call.py
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"""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