装饰器
在stackoverflow上看到一篇讲python中decorator的回答,实在是受益匪浅,决定将其翻译成中文,分享给大家。
原文链接如下How to make a chain of function decorators in Python?
函数是对象
在python中,函数是对象。
以一个简单的函数为例。
def shout(word="yes"): return word.capitalize()+"!"print(shout())
会输出
Yes!
作为对象,是可以赋值给另外一个变量的。
scream = shoutprint(scream())
输出和上面是一样的。
更有意思的是,python中的函数是可以定义在另外一个函数内部的。
def talk(): def whisper(word="yes"): return word.lower()+"..." print(whisper()) talk()
输出
yes...
函数引用
通过上面的例子可以看到,函数是对象,所以
可以被赋值给另外一个变量
可以在另外一个函数中被定义。
这也就意味着,一个函数可以将另外一个函数作为返回值。
def getTalk(kind="shout"): def shout(word="yes"): return word.capitalize()+"!" def whisper(word="yes"): return word.lower()+"..." if kind == "shout": return shout else: return whisper talk = getTalk()print talk # 输出 <function shout at 0x105b61230>print talk() # 输出 Yes!print getTalk("whisper")() # 输出yes...
如果能够返回一个函数,也可以将一个函数作为参数传入,复用上面的scream函数
def doSomethingBefore(func): print("I do something before then I call the function you gave me") print(func) doSomethingBefore(scream)
输出
I do something before then I call the function you gave me Yes!
现在应该能够理解装饰器了吧,装饰器实际上就是对函数进行了包装,它能够在不改变函数的前提下,在这个函数被执行之前或者执行之后执行一段代码。
手写装饰器
# 装饰器将一个另外的函数作为参数传入def my_shiny_new_decorator(a_function_to_decorate): # 定义一个wrapper def the_wrapper_around_the_original_function(): # 在传入的函数被执行前执行 print("Before the function runs") a_function_to_decorate() # 在传入的函数被执行后执行 print("After the function runs") return the_wrapper_around_the_original_functiondef a_stand_alone_function(): print("I am a stand alone function, don't you dare modify me") a_stand_alone_function()# 输出: I am a stand alone function, don't you dare modify mea_stand_alone_function_decorated = my_shiny_new_decorator(a_stand_alone_function) a_stand_alone_function_decorated()# 输出 # Before the function runs# I am a stand alone function, don't you dare modify me# After the function runs
也许你想要每次调用a_stand_alone_function时,
a_stand_alone_function_decorated就会被调用,这很简单,只需要用a_stand_alone_function_decorated返回的函数覆盖之前的a_stand_alone_function就可以了。
使用装饰器
@my_shiny_new_decoratordef another_stand_alone_function(): print("Leave me alone") another_stand_alone_function() # 输出#Before the function runs#Leave me alone#After the function runs
是的,就是这么简单。 @decorator就是下面代码的简写
another_stand_alone_function = my_shiny_new_decorator(another_stand_alone_function)
装饰器就是Decorator patternpython式实现。
像下面的代码
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(food) sandwich()#outputs: --ham--sandwich = bread(ingredients(sandwich)) sandwich()
就可以写成
@bread@ingredientsdef sandwich(food="--ham--"): print(food) sandwich()#outputs:#</''''''\># #tomatoes## --ham--# ~salad~#<\______/>
装饰器的顺序很重要,如果改变上面的顺序,函数的行为就被改变了
@ingredients@breaddef sandwich(food="--ham--"): print(food) strange_sandwich()#outputs:##tomatoes##</''''''\># --ham--#<\______/># ~salad~
还是一个装饰器的例子
# The decorator to make it bolddef 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 italicdef makeitalic(fn): # The new function the decorator returns def wrapper(): # Insertion of some code before and after return "<i>" + fn() + "</i>" return wrapper@makebold@makeitalicdef say(): return "hello"print(say())#outputs: <b><i>hello</i></b># 等同于下面的函数 def say(): return "hello"say = makebold(makeitalic(say)) print(say())#outputs: <b><i>hello</i></b>
装饰器更高级的应用
向被装饰的函数传递参数
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# 因为最终被调用是被装饰器返回的函数,即wrapper,# 所以将参数传递给wrapper会将这些参数传递给被装饰的函数@a_decorator_passing_argumentsdef 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
装饰方法
python中方法和函数是一样的。唯一不同的是,方法期望传入的第一个参数是当前的对象(self)。
也就是说装饰方法和装饰函数没有差异,只需要在装饰方法的时候将第一个参数考虑进去就行
def method_friendly_decorator(method_to_decorate): def wrapper(self, lie): lie = lie - 3 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 {0}, what did you think?".format(self.age + lie)) l = Lucy() l.sayYourAge(-3)#outputs: I am 26, what did you think?
如果试图些一个通用的装饰器,可以用*args, **kwargs
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_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, c) function_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 {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?
向装饰器传递参数
那么问题来了,怎么向装饰器传递参数呢?
这有点让人挠头,因为装饰器必须接受一个函数作为参数。
因此可以直接向装饰器传递参数。
回想一下之前的代码
# Decorators are ORDINARY functionsdef 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_decoratordef lazy_function(): print("zzzzzzzz")#outputs: I am an ordinary function
这两个是一样的。my_decorator被调用了。
当写下@my_decorator时,python会调用被标注为my_decorator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.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 functiondef 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.
将代码中的中间变量去掉试试。
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.
再简化一次代码
@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.
回到之前的问题,如果我们能够随时生成装饰器,我们也能向那个生成的装饰器传递参数。
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 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
下面这个就是带参数的装饰器
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
用上面的方法可以向装饰器传递参数,也可以用 *args, **kwargs这样的参数形式。
但是要记住,这样的动态方法只能被使用一次,就是导入这个脚本的时候,后面不能再动态使用。
装饰一个装饰器
看下面的装饰器
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
他应该这样使用
# 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
装饰器在python2.4后被引入,使用的时候确认版本支持。
使用装饰器会增加函数调用的时间。
被装饰的函数不能取消装饰
装饰器使得代码更加难以调试
注意,使用装饰器会会有一些副作用,被装饰的函数其实已经是另外一个函数了。
为了消除这个副作用,可以使用functools.wraps这个方法。看下面的例子。
# 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@bardef foo(): print("foo") print(foo.__name__)#outputs: wrapper# "functools" can help for thatimport functoolsdef bar(func): # We say that "wrapper", is wrapping "func" # and the magic begins @functools.wraps(func) def wrapper(): print("bar") return func() return wrapper@bardef foo(): print("foo") print(foo.__name__)#outputs: foo
实际使用
装饰器可以在很多场景下使用。
比如倒入某个外部库的时候,可以使用装饰器扩展库中函数的行为。
或者在debug的时候使用。
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 wrapperdef 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 wrapperdef 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@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
使用装饰器可以少写很多重复的代码
@counter@benchmark@loggingdef 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提供了很多的内在装饰器,如property,staticmethod等等。
还有一些其它的库也用到了装饰器
Django用装饰器来管理缓存和视图函数的权限
Twisted用装饰器来伪造内联异步调用
作者:大蟒传奇
链接:https://www.jianshu.com/p/954736037176