@wraps作用
python中的装饰器装饰过的函数其实就不是函数本身了，我们可以看看下面的例子
import time
def timmer(func):
"""timmer doc"""
def inner(*args, **kwargs):
"""inner doc"""
start = time.time()
res = func(*args, **kwargs)
end = time.time()
print("函数运行时间为 %s" % (end - start))
return res
return inner @timmer
def func_test():
"""func_test doc"""
time.sleep(2)
return print(func_test.__name__) # inner
print(func_test.__doc__) # inner doc
按我们正常的思维，func_test.__name__应该拿到的就是“func_test”，所以这个结果就印证了上面的第一句话，但是这是我们加一个@wraps，就会发现好像一切都正常了：
import time
from functools import wraps
def timmer(func):
"""timmer doc"""
@wraps(func)
def inner(*args, **kwargs):
"""inner doc"""
start = time.time()
res = func(*args, **kwargs)
end = time.time()
print("函数运行时间为 %s" % (end - start))
return res
return inner @timmer
def func_test():
"""func_test doc"""
time.sleep(2)
return print(func_test.__name__) # func_test
print(func_test.__doc__) # func_test doc
@wraps的实现原理
为了方便理解，我把源码和例子放在了一起，这样的话我们看着会方便：
import time
from functools import partial WRAPPER_ASSIGNMENTS = ('__module__', '__name__', '__qualname__', '__doc__',
'__annotations__')
WRAPPER_UPDATES = ('__dict__',) def update_wrapper(wrapper, # inner
wrapped, # func_test
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)
"""
print('update_wrapper 执行...')
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()
print('update_wrapper 执行结束')
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().
"""
print('wraps 执行...')
print('wraps 执行结束') # 纯粹为了打印出来的结果好理解
return partial(update_wrapper, wrapped=wrapped,
assigned=assigned, updated=updated) def timmer(func):
print('timmer 执行...') @wraps(func) # inner = update_wrapper的返回值
def inner(*args, **kwargs):
start = time.time()
res = func(*args, **kwargs)
end = time.time()
print("函数运行时间为 %s" % (end - start))
return res print('timmer 执行结束') # 当然不是真正的结束，执行完下一行才结束
return inner @timmer
def func_test():
print("func_test 执行...")
time.sleep(2)
print("func_test 运行结束")
return func_test() """
打印结果如下：
timmer 执行...
wraps 执行...
wraps 执行结束
update_wrapper 执行...
update_wrapper 执行结束
timmer 执行结束
func_test 执行...
func_test 运行结束
函数运行时间为 2.0000197887420654 从打印的结果我们可以看出，@语法会在函数定义或者说模块初始化阶段(可能称呼不对，以后回来改)就执行了
"""
上面的例子中我加了很多打印，主要是为了提醒一下在func_test()函数执行之前，@语法已经执行了。
其实原理很简单，用了一个偏函数，去执行update_wrapper，真正起作用的也是这个函数，func_test执行之前，update_wrapper函数就会把inner函数的好多属性（示例中WRAPPER_ASSIGNMENTS，WRAPPER_UPDATES指向的属性 ，还有__wrapped__属性）全部其换成func_test的属性。