如果你不喜欢长篇大论的解释，请看保罗·贝尔甘蒂诺的答案。

装饰师基础知识

Python的函数是对象

要理解装饰器，您必须首先了解函数是Python中的对象。这具有重要的后果。让我们看看为什么用一个简单的例子：

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 as e:
    print(e)
    #outputs: "name 'shout' is not defined"

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

请记住这一点。我们很快就会回到它。

Python函数的另一个有趣的属性是它们可以在另一个函数中定义！

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

函数引用

好吧，还在这里吗？现在有趣的部分...

您已经看到函数是对象。因此，函数：

• 可以分配给变量
• 可以在另一个函数中定义

这意味着一个函数可以返回另一个函数。

def getTalk(kind="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 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！

如果可以执行函数，则可以将一个函数作为参数传递：return

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!

好吧，你只是拥有理解装饰者所需的一切。你看，装饰器是“包装器”，这意味着它们允许您在它们修饰的函数之前和之后执行代码，而无需修改函数本身。

手工装饰师

如何手动操作：

# 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，您可能希望每次调用 时都会调用 。这很简单，只需用返回的函数覆盖：a_stand_alone_functiona_stand_alone_function_decorateda_stand_alone_functionmy_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

# That’s EXACTLY what decorators do!

装饰者揭开神秘面纱

前面的示例，使用装饰器语法：

@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

是的，就是这样，就是这么简单。 只是以下各项的捷径：@decorator

another_stand_alone_function = my_shiny_new_decorator(another_stand_alone_function)

装饰器只是装饰器设计模式的pythonic变体。Python中嵌入了几种经典的设计模式来简化开发（如迭代器）。

当然，你可以积累装饰者：

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~
#<\______/>

您设置装饰器的顺序很重要：

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

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

现在：回答这个问题...

作为结论，您可以轻松了解如何回答问题：

# 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>

你现在可以快乐地离开，或者多烧一点你的大脑，看看装饰器的高级用途。

将装饰师提升到一个新的水平

将参数传递给修饰函数

# 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: {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

装饰方法

关于Python的一个漂亮的事情是方法和函数实际上是相同的。唯一的区别是，方法期望它们的第一个参数是对当前对象的引用（）。self

这意味着您可以以相同的方式为方法构建装饰器！请记住要考虑：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 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?

如果你正在制作通用的装饰器--一个你可以应用于任何函数或方法的装饰器，无论它的参数如何--那么只需使用：*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?

将参数传递给装饰器

太好了，现在你会怎么说关于将参数传递给装饰者本身？

这可能会有些扭曲，因为装饰器必须接受函数作为参数。因此，不能将修饰函数的参数直接传递给修饰器。

在急于找到解决方案之前，让我们写一点提醒：

# 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

这是完全一样的。“” 称为。因此，当您告诉Python调用函数“由变量”“标记”时。my_decorator@my_decoratormy_decorator

这很重要！您给出的标签可以直接指向装饰者，也可以不指向装饰者。

让我们变得邪恶。☺

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.

这并不奇怪。

让我们做完全相同的事情，但跳过所有讨厌的中间变量：

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.

让我们让它更短：

@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.

#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，你看到了吗？我们使用了一个带有“”语法的函数调用！ ：-）@

所以，回到装饰者与参数。如果我们可以使用函数来动态生成装饰器，我们可以将参数传递给该函数，对吧？

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: https://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

这里是：一个带有参数的装饰器。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 know about my arguments: Leslie Howard

如您所见，您可以使用此技巧将参数传递给装饰器，就像任何函数一样。如果您愿意，您甚至可以使用。但请记住，装饰者只被调用一次。就在Python导入脚本的时候。之后无法动态设置参数。当您执行“导入x”时，该功能已经装饰，因此您无法更改任何内容。*args, **kwargs

让我们练习：装饰一个装饰器

好吧，作为奖励，我会给你一个片段，让任何装饰者普遍接受任何论点。毕竟，为了接受参数，我们使用另一个函数创建了装饰器。

我们包装了装饰器。

我们最近还看到了包装函数吗？

哦，是的，装饰师！

让我们玩得开心，为装饰者写一个装饰器：

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
       

它可以按如下方式使用：

# 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!

我知道，你上一次有这种感觉，是在听一个人说：“在理解递归之前，你必须先理解递归”。但是现在，你对掌握这一点感觉不好吗？

最佳做法：装饰器

• 装饰器是在Python 2.4中引入的，因此请确保您的代码将在> = 2.4上运行。
• 装饰器减慢了函数调用的速度。请记住这一点。
• 不能取消修饰函数。（有一些技巧可以创建可以删除的装饰器，但没有人使用它们。因此，一旦一个函数被修饰，它就会被装饰为所有代码。
• 装饰器包装函数，这可能使它们难以调试。（Python>= 2.5;见下文。

该模块是在Python 2.5中引入的。它包括函数 ，它将修饰函数的名称，模块和文档字符串复制到其包装器中。functoolsfunctools.wraps()

（有趣的事实：是一个装饰者！ ☺functools.wraps()

# 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

装饰师如何有用？

现在最大的问题是：我可以使用装饰器做什么？

看起来很酷，功能强大，但一个实际的例子会很棒。好吧，有1000种可能性。经典用法是从外部库扩展函数行为（您无法修改它），或用于调试（您不想修改它，因为它是临时的）。

您可以使用它们以DRY的方式扩展多个功能，如下所示：

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，装饰器的好处是，您可以立即在几乎任何东西上使用它们而无需重写。干，我说：

@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本身提供了几个装饰器：，等。propertystaticmethod

• Django使用装饰器来管理缓存和查看权限。
• 扭曲为伪造的内联异步函数调用。

这真的是一个大型游乐场。

查看文档，了解装饰器的工作原理。以下是您的要求：

from functools import wraps

def makebold(fn):
    @wraps(fn)
    def wrapper(*args, **kwargs):
        return "<b>" + fn(*args, **kwargs) + "</b>"
    return wrapper

def makeitalic(fn):
    @wraps(fn)
    def wrapper(*args, **kwargs):
        return "<i>" + fn(*args, **kwargs) + "</i>"
    return wrapper

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

@makebold
@makeitalic
def log(s):
    return s

print hello()        # returns "<b><i>hello world</i></b>"
print hello.__name__ # with functools.wraps() this returns "hello"
print log('hello')   # returns "<b><i>hello</i></b>"