【译】 python 基础知识:装饰器(decorator) 装饰器进阶 最佳实践 怎么有效使用装饰器

译注:本文译自 StackOverFlow 上对一个问题回答。虽然提的问题不是很难,但回答者却非常认真,详述了 Python 中装饰器,是一个很不错的入门和进阶的材料。而且作者的回答很容易看懂,大家可以直接看英文。不过,为了更加深入理解装饰器,本人还是翻译一下。另外,作者在回答的时候,有较多的口语化描述,所以本文在部分地方会进行意译和删节。

Python 函数是对象

为了理解装饰器,你首先必须理解,在 Python 中,函数是对象。理解这点有重要意义(consequences)。让我们通过一个简单例子来了解:

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def (word="yes"):
return word.capitalize()+"!"

print(shout())


# As an object, you can assign the function to a variable like any other object
scream = shout

# Notice we don't use parentheses: we are not calling the function, we are putting the function "shout" into the variable "scream". It means you can then call "shout" from "scream":

print(scream())


# More than that, it means you can remove the old name 'shout', and the function will still be accessible from 'scream'

del shout
try:
print(shout())
except NameError, e:
print(e)
#outputs: "name 'shout' is not defined"

print(scream())
# outputs: 'Yes!'

Python 函数的另一个有趣的特性就是它们能够被定义在其他函数的内部!

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def talk():

# You can define a function on the fly in "talk" ...
def whisper(word="yes"):
return word.lower()+"..."

# ... and use it right away!
print(whisper())

# You call "talk", that defines "whisper" EVERY TIME you call it, then
# "whisper" is called in "talk".
talk()
# outputs:
# "yes..."

# But "whisper" DOES NOT EXIST outside "talk":

try:
print(whisper())
except NameError, e:
print(e)
#outputs : "name 'whisper' is not defined"*
#Python's functions are objects

函数引用

好了,还不理解?现在开始进入有趣的部分…
你已经知道函数是对象,所以,函数能够:

  • 赋给一个变量

  • 能够被定义在另一个函数内部

这意味着一个函数能够返回另一个函数

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def getTalk(kind="shout"):

# We define functions on the fly
def (word="yes"):
return word.capitalize()+"!"

def whisper(word="yes") :
return word.lower()+"...";

# Then we return one of them
if kind == "shout":
# We don't use "()", we are not calling the function, we are returning the function object
return shout
else:
return whisper

# How do you use this strange beast?

# Get the function and assign it to a variable
talk = getTalk()

# You can see that "talk" is here a function object:
print(talk)
#outputs : <function shout at 0xb7ea817c>

# The object is the one returned by the function:
print(talk())
#outputs : Yes!

# And you can even use it directly if you feel wild:
print(getTalk("whisper")())
#outputs : yes...

还有更多!
如果你能够返回一个函数,你也可以把函数当成参数进行传递。

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def doSomethingBefore(func): 
print("I do something before then I call the function you gave me")
print(func())

doSomethingBefore(scream)
#outputs:
#I do something before then I call the function you gave me
#Yes!

现在你已经知道所有理解装饰器的必要知识。正如你所看到的,装饰器就是一个包装器(wrapper)。这意味着,它允许你,在不修改待装饰的函数的前提下,在该函数(执行)的前后执行其他代码。

手动构造装饰器

下边展示了如何手动构造装饰器:

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# A decorator is a function that expects ANOTHER function as parameter
def my_shiny_new_decorator(a_function_to_decorate):

# Inside, the decorator defines a function on the fly: the wrapper.
# This function is going to be wrapped around the original function
# so it can execute code before and after it.
def the_wrapper_around_the_original_function():

# Put here the code you want to be executed BEFORE the original function is called
print("Before the function runs")

# Call the function here (using parentheses)
a_function_to_decorate()

# Put here the code you want to be executed AFTER the original function is called
print("After the function runs")

# At this point, "a_function_to_decorate" HAS NEVER BEEN EXECUTED.
# We return the wrapper function we have just created.
# The wrapper contains the function and the code to execute before and after. It’s ready to use!
return the_wrapper_around_the_original_function

# Now imagine you create a function you don't want to ever touch again.
def a_stand_alone_function():
print("I am a stand alone function, don't you dare modify me")

a_stand_alone_function()
#outputs: I am a stand alone function, don't you dare modify me

# Well, you can decorate it to extend its behavior.
# Just pass it to the decorator, it will wrap it dynamically in
# any code you want and return you a new function ready to be used:

a_stand_alone_function_decorated = my_shiny_new_decorator(a_stand_alone_function)
a_stand_alone_function_decorated()
#outputs:
#Before the function runs
#I am a stand alone function, don't you dare modify me
#After the function runs

现在,你可能想要每次执行函数a_stand_alone_function的时候都执行的是a_stand_alone_function_decorated。这很简单,只要用my_shiny_new_decorator返回值覆盖a_stand_alone_function就行了:

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a_stand_alone_function = my_shiny_new_decorator(a_stand_alone_function)
a_stand_alone_function()
#outputs:
#Before the function runs
#I am a stand alone function, don't you dare modify me
#After the function runs

# That’s EXACTLY what decorators do!

装饰器解密

对前面的例子使用 Python 装饰器语法:

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def another_stand_alone_function():
print("Leave me alone")

another_stand_alone_function()
#outputs:
#Before the function runs
#Leave me alone
#After the function runs

对,就这么简单。@decorator只是下式的缩写:

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another_stand_alone_function = my_shiny_new_decorator(another_stand_alone_function)

装饰器只是一个装饰器设计模式的一个 Pythonic 的变体。Python 集成了几种经典的设计模式以便于开发(如迭代器)。

当然,你也可以堆叠(accumulate )装饰器:

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def bread(func):
def wrapper():
print("</''''''>")
func()
print("<______/>")
return wrapper

def ingredients(func):
def wrapper():
print("#tomatoes#")
func()
print("~salad~")
return wrapper

def sandwich(food="--ham--"):
print(food)

sandwich()
#outputs: --ham--
sandwich = bread(ingredients(sandwich))
sandwich()
#outputs:
#</''''''>
# #tomatoes#
# --ham--
# ~salad~
#<______/>

用 Python 的装饰器语法:

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@bread
@ingredients
def sandwich(food="--ham--"):
print(food)

sandwich()
#outputs:
#</''''''>
# #tomatoes#
# --ham--
# ~salad~
#<______/>

装饰器的顺序很重要:

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@ingredients
@bread
def strange_sandwich(food="--ham--"):
print(food)

strange_sandwich()
#outputs:
##tomatoes#
#</''''''>
# --ham--
#<______/>
# ~salad~

现在,回答提出的问题

现在,你很容易就能够回答提出的问题

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# The decorator to make it bold
def makebold(fn):
# The new function the decorator returns
def wrapper():
# Insertion of some code before and after
return "<b>" + fn() + "</b>"
return wrapper

# The decorator to make it italic
def makeitalic(fn):
# The new function the decorator returns
def wrapper():
# Insertion of some code before and after
return "<i>" + fn() + "</i>"
return wrapper

@makebold
@makeitalic
def say():
return "hello"

print(say())
#outputs: <b><i>hello</i></b>

# This is the exact equivalent to
def say():
return "hello"
say = makebold(makeitalic(say))

print(say())
#outputs: <b><i>hello</i></b>

现在,你可以高兴地(带着答案)离开,或者多烧下脑,看看装饰器的高级用法。

装饰器进阶

向待装饰函数传参

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# It’s not black magic, you just have to let the wrapper 
# pass the argument:

def a_decorator_passing_arguments(function_to_decorate):
def a_wrapper_accepting_arguments(arg1, arg2):
print("I got args! Look: {0}, {1}".format(arg1, arg2))
function_to_decorate(arg1, arg2)
return a_wrapper_accepting_arguments

# Since when you are calling the function returned by the decorator, you are
# calling the wrapper, passing arguments to the wrapper will let it pass them to
# the decorated function

@a_decorator_passing_arguments
def print_full_name(first_name, last_name):
print("My name is {0} {1}".format(first_name, last_name))

print_full_name("Peter", "Venkman")
# outputs:
#I got args! Look: Peter Venkman
#My name is Peter Venkman

修饰(类)方法

Python 一个奇特的地方在于方法跟函数实际上是一样的,唯一的区别在于方法的第一个参数是当前对象的引用(self)。这意味着你可以像装饰函数一样装饰方法。记得考虑self变量。

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def method_friendly_decorator(method_to_decorate):
def wrapper(self, lie):
lie = lie - 3 # very friendly, decrease age even more :-)
return method_to_decorate(self, lie)
return wrapper

class Lucy(object):

def __init__(self):
self.age = 32

@method_friendly_decorator
def sayYourAge(self, lie):
print("I am {0}, what did you think?".format(self.age + lie))

l = Lucy()
l.sayYourAge(-3)
#outputs: I am 26, what did you think?

如果你想要构造一个通用装饰器——能够应用到任意函数或方法,不管它们的参数是什么——那么就使用*args, **kwargs

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def a_decorator_passing_arbitrary_arguments(function_to_decorate):
# The wrapper accepts any arguments
def a_wrapper_accepting_arbitrary_arguments(*args, **kwargs):
print("Do I have args?:")
print(args)
print(kwargs)
# Then you unpack the arguments, here *args, **kwargs
# If you are not familiar with unpacking, check:
# http://www.saltycrane.com/blog/2008/01/how-to-use-args-and-kwargs-in-python/
function_to_decorate(*args, **kwargs)
return a_wrapper_accepting_arbitrary_arguments

@a_decorator_passing_arbitrary_arguments
def function_with_no_argument():
print("Python is cool, no argument here.")

function_with_no_argument()
#outputs
#Do I have args?:
#()
#{}
#Python is cool, no argument here.

@a_decorator_passing_arbitrary_arguments
def function_with_arguments(a, b, c):
print(a, b, c)

function_with_arguments(1,2,3)
#outputs
#Do I have args?:
#(1, 2, 3)
#{}
#1 2 3

@a_decorator_passing_arbitrary_arguments
def function_with_named_arguments(a, b, c, platypus="Why not ?"):
print("Do {0}, {1} and {2} like platypus? {3}".format(a, b, c, platypus))

function_with_named_arguments("Bill", "Linus", "Steve", platypus="Indeed!")
#outputs
#Do I have args ? :
#('Bill', 'Linus', 'Steve')
#{'platypus': 'Indeed!'}
#Do Bill, Linus and Steve like platypus? Indeed!

class Mary(object):

def __init__(self):
self.age = 31

@a_decorator_passing_arbitrary_arguments
def sayYourAge(self, lie=-3): # You can now add a default value
print("I am {0}, what did you think?".format(self.age + lie))

m = Mary()
m.sayYourAge()
#outputs
# Do I have args?:
#(<__main__.Mary object at 0xb7d303ac>,)
#{}
#I am 28, what did you think?

向装饰器传参

很好!如果我们向装饰器传参会怎么样?这样做看起来有点怪怪的,因为一个装饰器必须接受一个函数作为参数,因此,你不能够将被装饰的函数的参数直接传给装饰器。在看结论之前,我们先写一点以备提醒:

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# Decorators are ORDINARY functions
def my_decorator(func):
print("I am an ordinary function")
def wrapper():
print("I am function returned by the decorator")
func()
return wrapper

# Therefore, you can call it without any "@"

def lazy_function():
print("zzzzzzzz")

decorated_function = my_decorator(lazy_function)
#outputs: I am an ordinary function

# It outputs "I am an ordinary function", because that’s just what you do:
# calling a function. Nothing magic.

@my_decorator
def lazy_function():
print("zzzzzzzz")

#outputs: I am an ordinary function

上述两种方法效果完全一样,my_decorator被调用。所以当你写下@my_decorator,你在告诉 Python 解释器去调用标签为 my_decorator的函数。这很重要!你给定的标签能够直接指向装饰器,或者不是。

让我们更进一步:

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def decorator_maker():

print("I make decorators! I am executed only once: "
"when you make me create a decorator.")

def my_decorator(func):

print("I am a decorator! I am executed only when you decorate a function.")

def wrapped():
print("I am the wrapper around the decorated function. "
"I am called when you call the decorated function. "
"As the wrapper, I return the RESULT of the decorated function.")
return func()

print("As the decorator, I return the wrapped function.")

return wrapped

print("As a decorator maker, I return a decorator")
return my_decorator

# Let’s create a decorator. It’s just a new function after all.
new_decorator = decorator_maker()
#outputs:
#I make decorators! I am executed only once: when you make me create a decorator.
#As a decorator maker, I return a decorator

# Then we decorate the function

def decorated_function():
print("I am the decorated function.")

decorated_function = new_decorator(decorated_function)
#outputs:
#I am a decorator! I am executed only when you decorate a function.
#As the decorator, I return the wrapped function

# Let’s call the function:
decorated_function()
#outputs:
#I am the wrapper around the decorated function. I am called when you call the decorated function.
#As the wrapper, I return the RESULT of the decorated function.
#I am the decorated function.

这没什么好惊讶的。我们再重复原来的事情,不过去掉一些繁杂的中间变量:

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def decorated_function():
print("I am the decorated function.")
decorated_function = decorator_maker()(decorated_function)
#outputs:
#I make decorators! I am executed only once: when you make me create a decorator.
#As a decorator maker, I return a decorator
#I am a decorator! I am executed only when you decorate a function.
#As the decorator, I return the wrapped function.

# Finally:
decorated_function()
#outputs:
#I am the wrapper around the decorated function. I am called when you call the decorated function.
#As the wrapper, I return the RESULT of the decorated function.
#I am the decorated function.

更简要一点:

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@decorator_maker()
def decorated_function():
print("I am the decorated function.")
#outputs:
#I make decorators! I am executed only once: when you make me create a decorator.
#As a decorator maker, I return a decorator
#I am a decorator! I am executed only when you decorate a function.
#As the decorator, I return the wrapped function.

#Eventually:
decorated_function()
#outputs:
#I am the wrapper around the decorated function. I am called when you call the decorated function.
#As the wrapper, I return the RESULT of the decorated function.
#I am the decorated function.

嘿,看到了吗?我们用@语法来调用一个函数。所以,回到带参数装饰器,如果我们能够直接(on the fly)利用函数来生成装饰器,我们就能够向该函数传递参数,对吧?

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def decorator_maker_with_arguments(decorator_arg1, decorator_arg2):

print("I make decorators! And I accept arguments: {0}, {1}".format(decorator_arg1, decorator_arg2))

def my_decorator(func):
# The ability to pass arguments here is a gift from closures.
# If you are not comfortable with closures, you can assume it’s ok,
# or read: http://stackoverflow.com/questions/13857/can-you-explain-closures-as-they-relate-to-python
print("I am the decorator. Somehow you passed me arguments: {0}, {1}".format(decorator_arg1, decorator_arg2))

# Don't confuse decorator arguments and function arguments!
def wrapped(function_arg1, function_arg2) :
print("I am the wrapper around the decorated function.n"
"I can access all the variablesn"
"t- from the decorator: {0} {1}n"
"t- from the function call: {2} {3}n"
"Then I can pass them to the decorated function"
.format(decorator_arg1, decorator_arg2,
function_arg1, function_arg2))
return func(function_arg1, function_arg2)

return wrapped

return my_decorator

@decorator_maker_with_arguments("Leonard", "Sheldon")
def decorated_function_with_arguments(function_arg1, function_arg2):
print("I am the decorated function and only knows about my arguments: {0}"
" {1}".format(function_arg1, function_arg2))

decorated_function_with_arguments("Rajesh", "Howard")
#outputs:
#I make decorators! And I accept arguments: Leonard Sheldon
#I am the decorator. Somehow you passed me arguments: Leonard Sheldon
#I am the wrapper around the decorated function.
#I can access all the variables
# - from the decorator: Leonard Sheldon
# - from the function call: Rajesh Howard
#Then I can pass them to the decorated function
#I am the decorated function and only knows about my arguments: Rajesh Howard

这就是带参数的装饰器。这些参数也可以是变量:

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c1 = "Penny"
c2 = "Leslie"

@decorator_maker_with_arguments("Leonard", c1)
def decorated_function_with_arguments(function_arg1, function_arg2):
print("I am the decorated function and only knows about my arguments:"
" {0} {1}".format(function_arg1, function_arg2))

decorated_function_with_arguments(c2, "Howard")
#outputs:
#I make decorators! And I accept arguments: Leonard Penny
#I am the decorator. Somehow you passed me arguments: Leonard Penny
#I am the wrapper around the decorated function.
#I can access all the variables
# - from the decorator: Leonard Penny
# - from the function call: Leslie Howard
#Then I can pass them to the decorated function
#I am the decorated function and only knows about my arguments: Leslie Howard

就如你所看到的,使用这个方法,你能够像其他参数一样向装饰器传递参数。你甚至能够使用*args, **kwargs参数,如果你愿意。不过需要记住的是,装饰器只被调用一次,且仅仅只在 Python 解释器导入代码的时候。你不能够后续动态地设定装饰器的参数。当你执行 import x时,函数就已经被装饰,所以你不能改变什么。

装饰装饰器

好了,作为奖励,我会给你们一个代码片段,创建一个能够接受任意参数的装饰器。毕竟,为了接受参数,我们用另外一个函数来创建装饰器。我们将装饰器包装起来。

让我们写一个用于装饰装饰器的装饰器:

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def decorator_with_args(decorator_to_enhance):
"""
This function is supposed to be used as a decorator.
It must decorate an other function, that is intended to be used as a decorator.
Take a cup of coffee.
It will allow any decorator to accept an arbitrary number of arguments,
saving you the headache to remember how to do that every time.
"""

# We use the same trick we did to pass arguments
def decorator_maker(*args, **kwargs):

# We create on the fly a decorator that accepts only a function
# but keeps the passed arguments from the maker.
def decorator_wrapper(func):

# We return the result of the original decorator, which, after all,
# IS JUST AN ORDINARY FUNCTION (which returns a function).
# Only pitfall: the decorator must have this specific signature or it won't work:
return decorator_to_enhance(func, *args, **kwargs)

return decorator_wrapper

return decorator_maker

我们能够这样使用它:

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# You create the function you will use as a decorator. And stick a decorator on it :-)
# Don't forget, the signature is "decorator(func, *args, **kwargs)"
@decorator_with_args
def decorated_decorator(func, *args, **kwargs):
def wrapper(function_arg1, function_arg2):
print("Decorated with {0} {1}".format(args, kwargs))
return func(function_arg1, function_arg2)
return wrapper

# Then you decorate the functions you wish with your brand new decorated decorator.

@decorated_decorator(42, 404, 1024)
def decorated_function(function_arg1, function_arg2):
print("Hello {0} {1}".format(function_arg1, function_arg2))

decorated_function("Universe and", "everything")
#outputs:
#Decorated with (42, 404, 1024) {}
#Hello Universe and everything

# Whoooot!

最佳实践

  • 装饰器从 Python 2.4 开始引入,保证你的代码可以运行在大于等于 2.4 版本的 Python
  • 装饰器会降低函数调用效率,记住
  • 你不能反装饰一个函数(有方法可以创建一个可移除的装饰器,但没人使用)。所以一旦一个函数被装饰了,那在所有代码中它都是被装饰的
  • 用装饰器包装函数,会使得这些函数难以调试(在大于等于 2.5 版本的 Python,这种情况有所改善,见下文)

functools模块在 Python 2.5 中被引入,它包含了函数functools.wraps()。该函数会拷贝被装饰函数的名字、模块和注释(docstring)到它的包装器(wrapper)。
(有趣的地方: functools.wraps() 是一个装饰器)

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# For debugging, the stacktrace prints you the function __name__
def foo():
print("foo")

print(foo.__name__)
#outputs: foo

# With a decorator, it gets messy
def bar(func):
def wrapper():
print("bar")
return func()
return wrapper

@bar
def foo():
print("foo")

print(foo.__name__)
#outputs: wrapper

# "functools" can help for that

import functools

def bar(func):
# We say that "wrapper", is wrapping "func"
# and the magic begins
@functools.wraps(func)
def wrapper():
print("bar")
return func()
return wrapper

@bar
def foo():
print("foo")

print(foo.__name__)
#outputs: foo

怎么有效使用装饰器

现在有一个很重要的问题:我能用装饰器来做什么?
装饰器看起来很酷也很强大,但有一个实际的例子会更好。好吧,这有无数种例子。经典的用法是拓展一个来自外部库函数的功能(你不能修改它),或者用于调试(你不想修改函数,因为调试只是暂时的)。

你可以遵循 DRY(Don’t repeat yourself)规则,使用装饰器来拓展函数功能,如:

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def benchmark(func):
"""
A decorator that prints the time a function takes
to execute.
"""
import time
def wrapper(*args, **kwargs):
t = time.clock()
res = func(*args, **kwargs)
print("{0} {1}".format(func.__name__, time.clock()-t))
return res
return wrapper


def logging(func):
"""
A decorator that logs the activity of the script.
(it actually just prints it, but it could be logging!)
"""
def wrapper(*args, **kwargs):
res = func(*args, **kwargs)
print("{0} {1} {2}".format(func.__name__, args, kwargs))
return res
return wrapper


def counter(func):
"""
A decorator that counts and prints the number of times a function has been executed
"""
def wrapper(*args, **kwargs):
wrapper.count = wrapper.count + 1
res = func(*args, **kwargs)
print("{0} has been used: {1}x".format(func.__name__, wrapper.count))
return res
wrapper.count = 0
return wrapper

@counter
@benchmark
@logging
def reverse_string(string):
return str(reversed(string))

print(reverse_string("Able was I ere I saw Elba"))
print(reverse_string("A man, a plan, a canoe, pasta, heros, rajahs, a coloratura, maps, snipe, percale, macaroni, a gag, a banana bag, a tan, a tag, a banana bag again (or a camel), a crepe, pins, Spam, a rut, a Rolo, cash, a jar, sore hats, a peon, a canal: Panama!"))

#outputs:
#reverse_string ('Able was I ere I saw Elba',) {}
#wrapper 0.0
#wrapper has been used: 1x
#ablE was I ere I saw elbA
#reverse_string ('A man, a plan, a canoe, pasta, heros, rajahs, a coloratura, maps, snipe, percale, macaroni, a gag, a banana bag, a tan, a tag, a banana bag again (or a camel), a crepe, pins, Spam, a rut, a Rolo, cash, a jar, sore hats, a peon, a canal: Panama!',) {}
#wrapper 0.0
#wrapper has been used: 2x
#!amanaP :lanac a ,noep a ,stah eros ,raj a ,hsac ,oloR a ,tur a ,mapS ,snip ,eperc a ,)lemac a ro( niaga gab ananab a ,gat a ,nat a ,gab ananab a ,gag a ,inoracam ,elacrep ,epins ,spam ,arutaroloc a ,shajar ,soreh ,atsap ,eonac a ,nalp a ,nam A

当然,好消息是你几乎可以把装饰器应用在任意函数上而不用重写它们:

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@counter
@benchmark
@logging
def get_random_futurama_quote():
from urllib import urlopen
result = urlopen("http://subfusion.net/cgi-bin/quote.pl?quote=futurama").read()
try:
value = result.split("<br><b><hr><br>")[1].split("<br><br><hr>")[0]
return value.strip()
except:
return "No, I'm ... doesn't!"


print(get_random_futurama_quote())
print(get_random_futurama_quote())

#outputs:
#get_random_futurama_quote () {}
#wrapper 0.02
#wrapper has been used: 1x
#The laws of science be a harsh mistress.
#get_random_futurama_quote () {}
#wrapper 0.01
#wrapper has been used: 2x
#Curse you, merciful Poseidon!

Python 自身也提供了几个装饰器:property,staticmethod等。

  • Django 使用装饰器来管理缓存和查看权限
  • Twisted 使用装饰器来伪造(fake)内联异步函数调用

可以发挥的空间太大了!