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import functools
import warnings
from typing import Any, Callable, Type, TypeVar, cast
class VersionedDeprecationWarning(UserWarning):
"""A custom deprecation warning class that includes version information.
Attributes:
message (str): The deprecation message describing why the feature is deprecated.
remove_version (str): The version in which the feature will be removed.
Example:
>>> def deprecated_function():
... warnings.warn(
... VersionedDeprecationWarning(
... "Function XYZ is deprecated.",
... remove_version="2.0.0"
... )
... )
...
>>> deprecated_function()
DeprecationWarning: Function XYZ is deprecated. It will be removed in version 2.0.0.
"""
def __init__(self, message: str, remove_version: str) -> None:
super().__init__(message + f' It will be removed in version {remove_version}.')
class ExperimentalWarning(Warning):
"""A warning for experimental features.
Attributes:
feature_name (str): The name of the experimental feature.
"""
def __init__(self, feature_name: str) -> None:
super().__init__(f'{feature_name} is experimental and may change with future versions.')
F = TypeVar('F', bound=Callable[..., Any])
def experimental_function(feature_name: str) -> Callable[[F], F]:
"""Decorator to mark a function as experimental.
The message displayed will be {feature_name} is experimental and may change with future versions.
Args:
feature_name (str): The name of the experimental feature.
Returns:
The decorated function.
"""
def decorator(func: Callable):
@functools.wraps(func)
def wrapper(*args: Any, **kwargs: Any):
warnings.warn(ExperimentalWarning(feature_name))
return func(*args, **kwargs)
return cast(F, wrapper)
return decorator
def experimental_class(feature_name: str) -> Callable[[Type], Type]:
"""Class decorator to mark a class as experimental."""
def class_decorator(cls: Type):
original_init = cls.__init__
def new_init(self: Any, *args: Any, **kwargs: Any):
warnings.warn(ExperimentalWarning(feature_name))
original_init(self, *args, **kwargs)
cls.__init__ = new_init
return cls
return class_decorator |