wraps装饰器
装饰器之functools模块的wraps的用途是啥?首先我们先写一个装饰器:
python
# 探索functools模块wraps装饰器的用途
from functools import wraps
def trace(func):
""" 装饰器 """
# @wraps(func)
def callf(*args, **kwargs):
""" A wrapper function """
print("Calling function:{}".format(func.__name__)) # Calling function:foo
res = func(*args, **kwargs)
print("Return value:{}".format(res)) # Return value:9
return res
return callf
@trace
def foo(x):
""" 返回给定数字的平方 """
return x * x
if __name__ == '__main__':
print(foo(3)) # 9
print(foo.__doc__)
help(foo)
print(foo.__name__)
# print(foo.__globals__)
t = trace(foo)
print(t)
"""
打印结果:
Calling function:foo
Return value:9
9
A wrapper function
Help on function callf in module __main__:
callf(*args, **kwargs)
A wrapper function
callf
<function trace.<locals>.callf at 0x0000022F744D8730>
"""
上面的装饰器例子等价于:trace(foo(3)),只是在使用装饰器时,我们不用再手动调用装饰器函数;如果把这段代码提供给其他人调用, 他可能会想看下foo函数的帮助信息时:
bash
>>>from xxx import foo
>>>help(foo) # print(foo__doc__)
Help on function callf in module __main__:
callf(*args, **kwargs)
A wrapper function
这里,他可能会感到迷惑,继续敲:
bash
>>> print(foo.__name__)
callf
最后, 他可能会看源码,找问题原因,我们知道Python中的对象都是"第一类"的,所以,trace函数会返回一个callf闭包函数,连带callf的上下文环境一并返回,所以,可以解释我们执行help(foo)的到结果了,那么,我们如果才能得到我们想要的foo的帮助信息呢,这里就要用到了functools的wraps了。
python
# 探索functools模块wraps装饰器的用途
from functools import wraps
def trace(func):
""" 装饰器 """
@wraps(func)
def callf(*args, **kwargs):
""" A wrapper function """
print("Calling function:{}".format(func.__name__)) # Calling function:foo
res = func(*args, **kwargs)
print("Return value:{}".format(res)) # Return value:9
return res
return callf
@trace
def foo(x):
""" 返回给定数字的平方 """
return x * x
if __name__ == '__main__':
print(foo(3)) # 9
print(foo.__doc__)
help(foo)
print(foo.__name__)
# print(foo.__globals__)
t = trace(foo)
print(t)
至于wraps的原理,在此就不予展开扩展了,你只要是知道,wraps是通过partial和update_wrapper来帮我们实现想要的结果的,有兴趣可以可以自行研究下面部分源码:
python
# 有关wraps的源码,有兴趣的可以自行研究下
WRAPPER_ASSIGNMENTS = ('__module__', '__name__', '__qualname__', '__doc__',
'__annotations__')
WRAPPER_UPDATES = ('__dict__',)
def update_wrapper(wrapper,
wrapped,
assigned = WRAPPER_ASSIGNMENTS,
updated = WRAPPER_UPDATES):
"""Update a wrapper function to look like the wrapped function
wrapper is the function to be updated
wrapped is the original function
assigned is a tuple naming the attributes assigned directly
from the wrapped function to the wrapper function (defaults to
functools.WRAPPER_ASSIGNMENTS)
updated is a tuple naming the attributes of the wrapper that
are updated with the corresponding attribute from the wrapped
function (defaults to functools.WRAPPER_UPDATES)
"""
for attr in assigned:
try:
value = getattr(wrapped, attr)
except AttributeError:
pass
else:
setattr(wrapper, attr, value)
for attr in updated:
getattr(wrapper, attr).update(getattr(wrapped, attr, {}))
# Issue #17482: set __wrapped__ last so we don't inadvertently copy it
# from the wrapped function when updating __dict__
wrapper.__wrapped__ = wrapped
# Return the wrapper so this can be used as a decorator via partial()
return wrapper
def wraps(wrapped,
assigned = WRAPPER_ASSIGNMENTS,
updated = WRAPPER_UPDATES):
"""Decorator factory to apply update_wrapper() to a wrapper function
Returns a decorator that invokes update_wrapper() with the decorated
function as the wrapper argument and the arguments to wraps() as the
remaining arguments. Default arguments are as for update_wrapper().
This is a convenience function to simplify applying partial() to
update_wrapper().
"""
return partial(update_wrapper, wrapped=wrapped,
assigned=assigned, updated=updated)
class partial:
"""New function with partial application of the given arguments
and keywords.
"""
__slots__ = "func", "args", "keywords", "__dict__", "__weakref__"
def __new__(*args, **keywords):
if not args:
raise TypeError("descriptor '__new__' of partial needs an argument")
if len(args) < 2:
raise TypeError("type 'partial' takes at least one argument")
cls, func, *args = args
if not callable(func):
raise TypeError("the first argument must be callable")
args = tuple(args)
if hasattr(func, "func"):
args = func.args + args
tmpkw = func.keywords.copy()
tmpkw.update(keywords)
keywords = tmpkw
del tmpkw
func = func.func
self = super(partial, cls).__new__(cls)
self.func = func
self.args = args
self.keywords = keywords
return self
def __call__(*args, **keywords):
if not args:
raise TypeError("descriptor '__call__' of partial needs an argument")
self, *args = args
newkeywords = self.keywords.copy()
newkeywords.update(keywords)
return self.func(*self.args, *args, **newkeywords)
@recursive_repr()
def __repr__(self):
qualname = type(self).__qualname__
args = [repr(self.func)]
args.extend(repr(x) for x in self.args)
args.extend(f"{k}={v!r}" for (k, v) in self.keywords.items())
if type(self).__module__ == "functools":
return f"functools.{qualname}({', '.join(args)})"
return f"{qualname}({', '.join(args)})"
def __reduce__(self):
return type(self), (self.func,), (self.func, self.args,
self.keywords or None, self.__dict__ or None)
def __setstate__(self, state):
if not isinstance(state, tuple):
raise TypeError("argument to __setstate__ must be a tuple")
if len(state) != 4:
raise TypeError(f"expected 4 items in state, got {len(state)}")
func, args, kwds, namespace = state
if (not callable(func) or not isinstance(args, tuple) or
(kwds is not None and not isinstance(kwds, dict)) or
(namespace is not None and not isinstance(namespace, dict))):
raise TypeError("invalid partial state")
args = tuple(args) # just in case it's a subclass
if kwds is None:
kwds = {}
elif type(kwds) is not dict: # XXX does it need to be *exactly* dict?
kwds = dict(kwds)
if namespace is None:
namespace = {}
self.__dict__ = namespace
self.func = func
self.args = args
self.keywords = kwds