类的 Python functools.wraps 等价物

Question

使用类定义装饰器时，如何自动传输 __name__ 、 __module__ 和 __doc__ ？通常，我会使用 functools 中的 @wraps 装饰器。这是我为课程所做的（这不完全是我的代码）：

 class memoized:
    """Decorator that caches a function's return value each time it is called.
    If called later with the same arguments, the cached value is returned, and
    not re-evaluated.
    """
    def __init__(self, func):
        super().__init__()
        self.func = func
        self.cache = {}

    def __call__(self, *args):
        try:
            return self.cache[args]
        except KeyError:
            value = self.func(*args)
            self.cache[args] = value
            return value
        except TypeError:
            # uncacheable -- for instance, passing a list as an argument.
            # Better to not cache than to blow up entirely.
            return self.func(*args)

    def __repr__(self):
        return self.func.__repr__()

    def __get__(self, obj, objtype):
        return functools.partial(self.__call__, obj)

    __doc__ = property(lambda self:self.func.__doc__)
    __module__ = property(lambda self:self.func.__module__)
    __name__ = property(lambda self:self.func.__name__)

是否有标准的装饰器来自动创建名称模块和文档？另外，要使 get 方法自动化（我假设这是为了创建绑定方法？）是否缺少任何方法？

原文由 Neil G 发布，翻译遵循 CC BY-SA 4.0 许可协议

Answer 1

每个人似乎都错过了明显的解决方案。使用 functools.update_wrapper ：

 >>> import functools
>>> class memoized(object):
    """Decorator that caches a function's return value each time it is called.
    If called later with the same arguments, the cached value is returned, and
    not re-evaluated.
    """
    def __init__(self, func):
        self.func = func
        self.cache = {}
        functools.update_wrapper(self, func)  ## TA-DA! ##
    def __call__(self, *args):
        pass  # Not needed for this demo.

>>> @memoized
def fibonacci(n):
    """fibonacci docstring"""
    pass  # Not needed for this demo.

>>> fibonacci
<__main__.memoized object at 0x0156DE30>
>>> fibonacci.__name__
'fibonacci'
>>> fibonacci.__doc__
'fibonacci docstring'

原文由 samwyse 发布，翻译遵循 CC BY-SA 4.0 许可协议

Answer 2

我不知道 stdlib 中有这样的东西，但如果需要，我们可以创建自己的东西。

这样的事情可以工作：

 from functools import WRAPPER_ASSIGNMENTS

def class_wraps(cls):
    """Update a wrapper class `cls` to look like the wrapped."""

    class Wrapper(cls):
        """New wrapper that will extend the wrapper `cls` to make it look like `wrapped`.

        wrapped: Original function or class that is beign decorated.
        assigned: A list of attribute to assign to the the wrapper, by default they are:
             ['__doc__', '__name__', '__module__', '__annotations__'].

        """

        def __init__(self, wrapped, assigned=WRAPPER_ASSIGNMENTS):
            self.__wrapped = wrapped
            for attr in assigned:
                setattr(self, attr, getattr(wrapped, attr))

            super().__init__(wrapped)

        def __repr__(self):
            return repr(self.__wrapped)

    return Wrapper

用法：

 @class_wraps
class memoized:
    """Decorator that caches a function's return value each time it is called.
    If called later with the same arguments, the cached value is returned, and
    not re-evaluated.
    """

    def __init__(self, func):
        super().__init__()
        self.func = func
        self.cache = {}

    def __call__(self, *args):
        try:
            return self.cache[args]
        except KeyError:
            value = self.func(*args)
            self.cache[args] = value
            return value
        except TypeError:
            # uncacheable -- for instance, passing a list as an argument.
            # Better to not cache than to blow up entirely.
            return self.func(*args)

    def __get__(self, obj, objtype):
        return functools.partial(self.__call__, obj)

@memoized
def fibonacci(n):
    """fibonacci docstring"""
    if n in (0, 1):
       return n
    return fibonacci(n-1) + fibonacci(n-2)

print(fibonacci)
print("__doc__: ", fibonacci.__doc__)
print("__name__: ", fibonacci.__name__)

输出：

 <function fibonacci at 0x14627c0>
__doc__:  fibonacci docstring
__name__:  fibonacci

编辑：

如果您想知道为什么它没有包含在 stdlib 中是因为您可以将类装饰器包装在函数装饰器中并使用 functools.wraps 如下所示：

 def wrapper(f):

    memoize = memoized(f)

    @functools.wraps(f)
    def helper(*args, **kws):
        return memoize(*args, **kws)

    return helper

@wrapper
def fibonacci(n):
    """fibonacci docstring"""
    if n <= 1:
       return n
    return fibonacci(n-1) + fibonacci(n-2)

原文由 mouad 发布，翻译遵循 CC BY-SA 4.0 许可协议