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 = shout
print(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_function
def 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 me
a_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_decorator
def 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 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()
就可以写成
@bread
@ingredients
def 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
@bread
def 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 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>
# 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_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
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 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_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 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
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 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.
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
@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
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 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
使用装饰器可以少写很多重复的代码
@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
