有人翻译过了，很多转载，暂时没找到原文，各个地方的排版不一样，排版（代码格式），代码注解等都不怎么好
练练手，顺手一翻吧，权当加深理解
来源stackoverflow上的问题 链接
很长哦(应该是巨长…分了三次搞完)，要有耐心看完
python的函数是对象
要理解装饰器，首先，你必须明白，在python中，函数是对象. 这很重要.
简单例子来理解为什么
def shout(word="yes"): return word.capitalize()+"!"print shout()# outputs : 'Yes!'# 作为一个对象，你可以讲函数赋值给另一个对象scream = shout# 注意到这里我们并没有使用括号：我们不是调用函数，而是将函数'shout'赋给变量'scream'# 这意味着，你可以通过'scream'调用'shout'print scream()# outputs : 'Yes!'# 不仅如此，你可以删除老的名称'shout'，但是通过'scream'依旧可以访问原有函数del shouttry: print shout()except NameError, e: print e #outputs: "name 'shout' is not defined"print scream()# outputs: 'Yes!'
好了，记住这点，我们将会很快用到它.
Python函数另一个有趣的特性是，函数可以被定义在另一个函数里面
def talk(): # 你可以定义一个函数 def whisper(word="yes"): return word.lower()+"..." # ... 并且立刻调用 print whisper()# 每次当你调用"talk", 都会定义"whisper"# 并且在"talk"中被调用talk()# outputs:# "yes..."#但是在"talk"外部，函数"whisper"不存在！try: print whisper()except NameError, e: print e #outputs : "name 'whisper' is not defined"*
函数引用
好了，到这里了，接下来是有意思的部分，我们刚才看到 函数是对象，然后:
1.函数可以赋值给一个变量
2.函数可以定义在另一个函数内部
即，这也意味着一个函数可以返回另一个函数:-）,让我们来看另一段代码
def getTalk(type="shout"): # 定义函数 def shout(word="yes"): return word.capitalize()+"!" def whisper(word="yes") : return word.lower()+"..."; # 返回函数 if type == "shout": # 没有使用"()", 并不是要调用函数，而是要返回函数对象 return shout else: return whisper# 如何使用？# 将函数返回值赋值给一个变量talk = getTalk()# 我们可以打印下这个函数对象print talk#outputs : <function shout at 0xb7ea817c># 这个对象是函数的返回值print talk()#outputs : Yes!# 不仅如此，你还可以直接使用之print getTalk("whisper")()#outputs : yes...
但是稍等，如果你可以返回一个函数，那么你也可以将函数作为参数传递
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!
好了，现在你已经了解要理解装饰器的每件事.
装饰器就是封装器，可以让你在被装饰函数之前或之后执行代码，而不必修改函数本身
手工装饰器
如何书写一个装饰器
# 装饰器是一个以另一个函数为参数的函数def my_shiny_new_decorator(a_function_to_decorate): # 在这里，装饰器定义一个函数： 包装器. # 这个函数将原始函数进行包装，以达到在原始函数之前、之后执行代码的目的 def the_wrapper_around_the_original_function(): # 将你要在原始函数之前执行的代码放到这里 print "Before the function runs" # 调用原始函数(需要带括号) a_function_to_decorate() # 将你要在原始函数之后执行的代码放到这里 print "After the function runs" # 代码到这里，函数‘a_function_to_decorate’还没有被执行 # 我们将返回刚才创建的这个包装函数 # 这个函数包含原始函数及要执行的附加代码，并且可以被使用 return the_wrapper_around_the_original_function# 创建一个函数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# 好了，在这里你可以装饰这个函数，扩展其行为# 将函数传递给装饰器，装饰器将动态地将其包装在任何你想执行的代码中，然后返回一个新的函数a_stand_alone_function_decorated = my_shiny_new_decorator(a_stand_alone_function)# 调用新函数，可以看到装饰器的效果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
到这里，或许你想每次调用a_stand_alone_function都使用a_stand_alone_function_decorated替代之很简单，只需要将a_stand_alone_function用my_shiny_new_decorator装饰返回
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# 这就是装饰器做的事情!
装饰器阐述
前面的例子，使用装饰器语法
@my_shiny_new_decoratordef another_stand_alone_function(): print "Leave me alone"another_stand_alone_function()#outputs:#Before the function runs#Leave me alone#After the function runs
是的，就是这么简单. @decorator是下面代码的简写
nother_stand_alone_function = my_shiny_new_decorator(another_stand_alone_function)
装饰器只是 装饰器模式的python实现
python代码中还存在其他几个经典的设计模式，以方便开发，例如迭代器iterators
当然，你可以累加装饰器
def bread(func): def wrapper(): print "</''''''\&;" func() print "<\______/>" return wrapperdef ingredients(func): def wrapper(): print "#tomatoes#" func() print "~salad~" return wrapperdef sandwich(food="--ham--"): print foodsandwich()#outputs: --ham--#累加两个装饰器sandwich = bread(ingredients(sandwich))sandwich()#outputs:#</''''''\&;# #tomatoes## --ham--# ~salad~#<\______/>
使用python装饰器语法
@bread@ingredientsdef sandwich(food="--ham--"): print foodsandwich()#outputs:#</''''''\&;# #tomatoes## --ham--# ~salad~#<\______/>
装饰器位置的顺序很重要
@ingredients@breaddef strange_sandwich(food="--ham--"): print food strange_sandwich()#outputs:##tomatoes##</''''\&;# --ham--#<\______/># ~salad~'
最后回答问题
# bold装饰器def makebold(fn): def wrapper(): # 在前后加入标签 return "<b>" + fn() + "</b>" return wrapper# italic装饰器def makeitalic(fn): def wrapper(): # 加入标签 return "<i>" + fn() + "</i>" return wrapper@makebold@makeitalicdef say(): return "hello"print say()#outputs: <b><i>hello</i></b># 等价的代码def say(): return "hello"say = makebold(makeitalic(say))print say()#outputs: <b><i>hello</i></b>
好了，到这里你可以高兴地离开了，或者来看下一些装饰器高级的用法
向装饰器函数传递参数
# 这不是黑魔法，你只需要让包装传递参数:def a_decorator_passing_arguments(function_to_decorate): def a_wrapper_accepting_arguments(arg1, arg2): print "I got args! Look:", arg1, arg2 function_to_decorate(arg1, arg2) return a_wrapper_accepting_arguments# 当你调用装饰器返回的函数，实际上是调用包装函数，所以给包装函数传递参数即可将参数传给装饰器函数@a_decorator_passing_argumentsdef print_full_name(first_name, last_name): print "My name is", first_name, last_nameprint_full_name("Peter", "Venkman")# outputs:#I got args! Look: Peter Venkman#My name is Peter Venkman
装饰方法
Python中对象的方法和函数是一样的，除了对象的方法首个参数是指向当前对象的引用(self)。这意味着你可以用同样的方法构建一个装饰器，只是必须考虑self
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 wrapperclass Lucy(object): def __init__(self): self.age = 32 @method_friendly_decorator def sayYourAge(self, lie): print "I am %s, what did you think?" % (self.age + lie)l = Lucy()l.sayYourAge(-3)#outputs: I am 26, what did you think?
当然，你可以构造一个更加通用的装饰器，可以作用在任何函数或对象方法上，而不必关系其参数使用
*args, **kwargs
如下代码
def a_decorator_passing_arbitrary_arguments(function_to_decorate): # 包装函数可以接受任何参数 def a_wrapper_accepting_arbitrary_arguments(*args, **kwargs): print "Do I have args?:" print args print kwargs # 然后你可以解开参数， *args，**kwargs # 如果你对此不是很熟悉，可以参考 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_argumentsdef 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_argumentsdef function_with_arguments(a, b, c): print a, b, cfunction_with_arguments(1,2,3)#outputs#Do I have args?:#(1, 2, 3)#{}#1 2 3@a_decorator_passing_arbitrary_argumentsdef function_with_named_arguments(a, b, c, platypus="Why not ?"): print "Do %s, %s and %s like platypus? %s" %\ (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 %s, what did you think ?" % (self.age + lie)m = Mary()m.sayYourAge()#outputs# Do I have args?:#(<__main__.Mary object at 0xb7d303ac>,)#{}#I am 28, what did you think?
向装饰器传递参数
好了，现在你或许会想是否可以向装饰器本身传递参数
装饰器必须使用函数作为参数，所以这看起来会有些复杂，你不能直接传递参数给装饰器本身
在开始处理这个问题前，看一点提醒
# 装饰器是普通的方法def my_decorator(func): print "I am a ordinary function" def wrapper(): print "I am function returned by the decorator" func() return wrapper# 所以，你可以不通过@调用它def lazy_function(): print "zzzzzzzz"decorated_function = my_decorator(lazy_function)#outputs: I am a ordinary function# It outputs "I am a ordinary function", because that's just what you do:# 调用一个函数，没有什么特别@my_decoratordef lazy_function(): print "zzzzzzzz"#outputs: I am a ordinary function
上面两个形式本质上是相同的， “my_decorator” 被调用.所以当你使用”@my_decorator”,告诉python一个函数被变量”my_decorator”标记这十分重要,因为你提供的标签直接指向装饰器…或者不是，继续
# 声明一个用于创建装饰器的函数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.# 创建一个装饰器，本质上只是一个函数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# 使用装饰器装饰函数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# 调用被装饰函数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.
我们跳过中间变量，做同样的事情
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.# 最后: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.
使用装饰器语法，更简短
@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.#最终: 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.
到这里，我们使用@调用一个函数
回到问题，向装饰器本身传递参数，如果我们可以通过函数去创建装饰器，那么我们可以传递参数给这个函数，对么？
def decorator_maker_with_arguments(decorator_arg1, decorator_arg2): print "I make decorators! And I accept arguments:", decorator_arg1, decorator_arg2 def my_decorator(func): # 这里能传递参数的能力，是闭包的特性 # 更多闭包的内容，参考 http://stackoverflow.com/questions/13857/can-you-explain-closures-as-they-relate-to-python print "I am the decorator. Somehow you passed me arguments:", decorator_arg1, decorator_arg2 # 不要搞混了装饰器参数和函数参数 def wrapped(function_arg1, function_arg2) : print ("I am the wrapper around the decorated function.\n" "I can access all the variables\n" "\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
好了，that’s it.参数可以设置为变量
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
你可以看到，你可以使用像其它函数一样使用这个方法向装饰器传递参数.如果你愿意你甚至可以使用 arg *kwargs.
但是记住，装饰器仅在Python代码导入时被调用一次,之后你不能动态地改变参数.当你使用”import x”,函数已经被装饰，所以你不能改变什么
练习：一个装饰装饰器的装饰器
作为奖励，我将展示创建可以处理任何参数的装饰器代码片段. 毕竟，为了接收参数，必须使用另一个函数来创建装饰器
让我们来给装饰器写一个装饰器:
# 装饰 装饰器 的装饰器 (好绕.....)def decorator_with_args(decorator_to_enhance): """ 这个函数将作为装饰器使用 它必须装饰另一个函数 它将允许任何接收任意数量参数的装饰器 方便你每次查询如何实现 """ # 同样的技巧传递参数 def decorator_maker(*args, **kwargs): # 创建一个只接收函数的装饰器 # 但是这里保存了从创建者传递过来的的参数 def decorator_wrapper(func): # 我们返回原始装饰器的结果 # 这是一个普通的函数，返回值是另一个函数 # 陷阱：装饰器必须有这个特殊的签名，否则不会生效 return decorator_to_enhance(func, *args, **kwargs) return decorator_wrapper return decorator_maker
使用：
# 你创建这个函数是作为一个装饰器，但是给它附加了一个装饰器# 别忘了，函数签名是： "decorator(func, *args, **kwargs)"@decorator_with_args def decorated_decorator(func, *args, **kwargs): def wrapper(function_arg1, function_arg2): print "Decorated with", args, kwargs return func(function_arg1, function_arg2) return wrapper# 然后，使用这个装饰器(your brand new decorated decorator)@decorated_decorator(42, 404, 1024)def decorated_function(function_arg1, function_arg2): print "Hello", function_arg1, function_arg2decorated_function("Universe and", "everything")#outputs:#Decorated with (42, 404, 1024) {}#Hello Universe and everything# Whoooot!
我知道，到现在你一定会有这种感觉，就像你听一个人说“在理解递归之前，你必须首先了解递归”，但是现在，掌握这儿你有没有觉得很棒？
装饰器使用最佳实践这是Python2.4的新特性，所以确保你的代码在2.4及之上的版本运行装饰器降低了函数调用的性能，记住这点You can not un-decorate a function. There are hacks to create decorators that can be removed but nobody uses them. So once a function is decorated, it’s done. For all the code.装饰器包装函数，所以很难debug
Python2.5解决了最后一个问题，它提供functools模块，包含functools.wraps.这个函数会将被装饰函数的名称，模块，文档字符串拷贝给封装函数,有趣的是，functools.wraps是一个装饰器:-)
# 调试，打印函数的名字def foo(): print "foo"print foo.__name__#outputs: foo# 但当你使用装饰器，这一切变得混乱def bar(func): def wrapper(): print "bar" return func() return wrapper@bardef foo(): print "foo"print foo.__name__#outputs: wrapper# "functools" 可以改变这点import functoolsdef bar(func): # 我们所说的 "wrapper", 封装 "func" @functools.wraps(func) def wrapper(): print "bar" return func() return wrapper@bardef foo(): print "foo"# 得到的是原始的名称, 而不是封装器的名称print foo.__name__#outputs: foo
装饰器为何那么有用
现在的问题是，我们用装饰器来坐什么？看起来很酷很强大，但是如果有实践的例子会更好.好了，有1000种可能。经典的用法是，在函数的外部，扩展一个函数的行为（你不需要改变这个函数），或者，为了调试的目的（我们不修改的原因是这是临时的），你可以使用装饰器扩展一些函数,而不用在这些函数中书写相同的函数实现一样的功能
DRY原则，例子：
def benchmark(func): """ 装饰器打印一个函数的执行时间 """ import time def wrapper(*args, **kwargs): t = time.clock() res = func(*args, **kwargs) print func.__name__, time.clock()-t return res return wrapperdef logging(func): """ 装饰器记录函数日志 """ def wrapper(*args, **kwargs): res = func(*args, **kwargs) print func.__name__, args, kwargs return res return wrapperdef counter(func): """ 记录并打印一个函数的执行次数 """ 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@loggingdef 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
装饰器意味着，你可以用正确的方法实现几乎所有的事情，而不必重写他们
@counter@benchmark@loggingdef get_random_futurama_quote(): import httplib conn = httplib.HTTPConnection("slashdot.org:80") conn.request("HEAD", "/index.html") for key, value in conn.getresponse().getheaders(): if key.startswith("x-b") or key.startswith("x-f"): return value 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本身提供了一些装饰器：property,staticmethod,等等，
Django使用装饰器去管理缓存和权限. Twisted to fake inlining asynchronous functions calls.用途广泛
EDIT: 鉴于这个回答的完美，人们希望我去回答metaclass,我这样做了
原文地址：[翻译]理解python中的装饰器, 感谢原作者分享。 明天的希望，让我们忘了今天的痛苦
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