原文：How can I make a chain of function decorators in Python?
1. Python里函数是对象
为了理解装饰器(decorator)，你必须首先理解函数是对象。我们来看一个简单的例子：
def shout(word="yes"):
return word.capitalize()+"!"
print shout()
# outputs : 'Yes!'
# 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()
# outputs : 'Yes!'
# 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!'
好的，记住它，我们很快会回来。另一个关于Python函数有趣的特性是你可以在另一函数里定义函数。
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"*
2. 函数引用
OK，你还在看吗？现在进入有趣的部分，你将看到函数是对象，因此：
- 可以把它赋值给一个变量
- 可以在另一个函数里定义
这意味着，一个函数可以返回另一个函数 :-)，看：
def getTalk(type="shout"):
# We define functions on the fly
def shout(word="yes"):
return word.capitalize()+"!"
def whisper(word="yes") :
return word.lower()+"...";
# Then we return one of them
if type == "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...
如果你可以返回一个函数，那么你也可以作为参数传递它。
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!
你已经拥有理解装饰器的全部知识了。你看，装饰器就是一个包装，让你在函数前后做一些事情，而你不用改变这个函数。
3. 手写装饰器
# 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，你每次调用a_stand_alone_function，a_stand_alone_function_decorated会被调用。很简单，仅仅是覆盖a_stand_alone_function，返回my_shiny_new_decorator。
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
# And guess what? That's EXACTLY what decorators do!
4. 装饰器解密
上一个例子，使用了装饰器语法：
@my_shiny_new_decorator
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
@decorator就是一个简写：
another_stand_alone_function = my_shiny_new_decorator(another_stand_alone_function)
装饰器只是装饰器设计模式在Python中的变体。Python自带了许多经典设计模式来方便开发，比如迭代器。
当然，你可以叠加装饰器：
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~
#<\______/>
使用Python装饰器语法：
@bread
@ingredients
def sandwich(food="--ham--"):
print food
sandwich()
#outputs:
#</''''''\>
# #tomatoes#
# --ham--
# ~salad~
#<\______/>
装饰器的顺序是有影响的：
@ingredients
@bread
def strange_sandwich(food="--ham--"):
print food
strange_sandwich()
#outputs:
##tomatoes#
#</''''''\>
# --ham--
#<\______/>
# ~salad~
5. 向装饰器函数传递参数
# 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:", 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", first_name, last_name
print_full_name("Peter", "Venkman")
# outputs:
#I got args! Look: Peter Venkman
#My name is Peter Venkman
6. 装饰方法
Python有一个很棒的地方就是方法和函数是一样的，除了方法地一个参数是当前对象的引用（self）。这意味着你可以用同样的方式给方法添加装饰器，记住把self考虑在内。
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 %s, what did you think?" % (self.age + lie)
l = Lucy()
l.sayYourAge(-3)
#outputs: I am 26, what did you think?
当然，如果你想写一个通用的装饰器，那就不用管参数，只要写*args,**kwargs就可以了：
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 %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?
Passing arguments to the decorator
7. 给装饰器传递参数
装饰器必须接受一个函数作为参数，因此你不能直接给装饰器传递参数。
# Decorators are ORDINARY functions
def my_decorator(func):
print "I am a 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 a ordinary function
# It outputs "I am a ordinary function", because that's just what you do:
# calling a function. Nothing magic.
@my_decorator
def lazy_function():
print "zzzzzzzz"
#outputs: I am a ordinary function
It's exactly the same. "my_decorator" is called. So when you @my_decorator, you are telling Python to call the function 'labeled by the variable "my_decorator"'. It's important, because the label you give can point directly to the decorator... or not! Let's start to be evil!
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.
我们做了同样的事情，只是跳过了中间变量：
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.
再来一遍短一点的：
@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.
看到了吗？我们使用了“@”语法 :-)
我们回头看带参数的装饰器。如果我们能使用函数去创建装饰器，我们也可以给那个函数传递参数，是吧？
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):
# 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:", 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
这就是带参数的装饰器。参数可以是一个变量。
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
正如你所见，你可以给装饰器传递参数，就像函数一样。你甚至可以使用*args,**kwargs。但是记住，装饰器只会调用一次。在当Pythonimport这个脚本的时候。你不能动态的设置变量。当你import x的时候，函数已经被调用了，你什么也改变不了。
8. 让我们实践一下：写一个装饰器来装饰另一个装饰器
作为奖励，我会给你一段代码来让任意装饰器接受任意参数。然后，为了接受参数，我们使用另一个函数来创建我们的装饰器。我们包装这个装饰器。
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
你可以这样使用：
# 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", 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", function_arg1, function_arg2
decorated_function("Universe and", "everything")
#outputs:
#Decorated with (42, 404, 1024) {}
#Hello Universe and everything
# Whoooot!
我知道，你会有这种感觉，就像一个家伙对你说：“在理解递归之前，你先要理解递归”。现在，你还会感觉你掌握这写了吗？
9. 最佳实践
- 需要Python 2.4及以上的版本
- 装饰器会让函数调用变慢。谨记。
- 你不能取消装饰器。尽管有一些方法可以创建可以移除的装饰器，但没人这么干。
- 被装饰器包装的函数，这会让你很难调试。
Python 2.5解决了这个调试问题，通过functools模块里的functools.wraps，你可以复制被装饰的函数名称，模块和文档。有趣的是，functools.wraps也是一个装饰器。
# 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
10. 装饰器有什么用？
现在的问题是：我能用装饰器做什么？看起来很酷很强大，但是实践的例子更有用。这有1000中可能性。经典的用法是继承一个外部函数的行为（你不能修改它）或者用于调试（你不能修改因为它是临时的）。你可以使用它来扩展N多函数，又不用每次重写，遵循DRY原则，例如：
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 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 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
当然装饰器最好的用途就是避免重复，DRY。
@counter
@benchmark
@logging
def 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提供了很多装饰器：property,staticmethod,等等。Django使用装饰器来管理缓存和视图权限。Twisted来做异步函数调用。这有很大的应用场景。