如何制作功能装饰器链?

如何在 Python 中制作两个装饰器,以完成以下工作?

@makebold
@makeitalic
def say():
   return "Hello"

... 应返回:

"<b><i>Hello</i></b>"

我并不是想在真实的应用程序中以这种方式制作HTML ,而是试图了解装饰器和装饰器链接的工作方式。

答案

如果您不做详细解释,请参阅Paolo Bergantino 的答案

装饰基础

Python 的函数是对象

要了解装饰器,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 as e:
    print(e)
    #outputs: "name 'shout' is not defined"

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

请记住这一点。我们很快会回头再说。

Python 函数的另一个有趣特性是可以在另一个函数中定义它们!

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

功能参考

好吧,还在吗?现在有趣的部分...

您已经看到函数是对象。因此,功能:

  • 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return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return一个函数,则可以传递一个作为参数:

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,您只需具备了解装饰器所需的一切。您会看到,装饰器是 “包装器”,这意味着它们使您可以在装饰函数之前和之后执行代码,而无需修改函数本身。

手工装饰

您将如何手动进行操作:

# 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,你可能想,每次你打电话时a_stand_alone_functiona_stand_alone_function_decorated被称为替代。这很简单,只需用a_stand_alone_function返回的函数覆盖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

# That’s EXACTLY what decorators do!

装饰者神秘化

上一个使用装饰器语法的示例:

@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,仅此而已。 @decorator只是以下操作的快捷方式:

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(例如迭代器)。

当然,您可以积累装饰器:

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~
#<\______/>

您设置装饰器重要事项的顺序:

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

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

现在:回答问题...

作为结论,您可以轻松地看到如何回答该问题:

# 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>

现在,您可以放开心心,或者多动脑筋,看看装饰器的高级用法。


将装饰者提升到一个新的水平

将参数传递给装饰函数

# 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

装饰方式

关于 Python 的一件事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( self )的引用。

这意味着您可以以相同的方式为方法构建装饰器!只要记住要考虑一下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?

如果要制作通用装饰器(无论其参数如何,都将其应用于任何函数或方法),则只需使用*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,关于将参数传递给装饰器本身,您会说什么?

因为装饰器必须接受一个函数作为参数,所以这可能会有些扭曲。因此,您不能将装饰函数的参数直接传递给装饰器。

在寻求解决方案之前,让我们写一些提醒:

# 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

完全一样。调用了 “ my_decorator ”。因此,当您使用@my_decorator ,您在告诉 Python 调用函数 “由变量 “ my_decorator ” 标记”。

这个很重要!你给的标签可以直接指向 decorator- 与否

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.

毫不奇怪。

让我们做完全相同的事情,但是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.

让我们把它变得更短

@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?我们使用了带有 “ @ ” 语法的函数调用! :-)

因此,回到带有参数的装饰器。如果我们可以使用函数即时生成装饰器,则可以将参数传递给该函数,对吗?

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

它是:带参数的装饰器。可以将参数设置为变量:

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,可以使用此技巧像其他任何函数一样将参数传递给装饰器。如果愿意*args, **kwargs您甚至可以使用*args, **kwargs 。但是请记住,装饰器被调用一次 。就在 Python 导入脚本时。之后,您将无法动态设置参数。当您执行 “import x” 时, 该函数已被修饰 ,因此您无法进行任何更改。


练习:装饰装饰器

好的,作为奖励,我将向您提供一个片段,以使任何装饰器通常接受任何参数。毕竟,为了接受参数,我们使用了另一个函数来创建装饰器。

我们包装了装饰器。

我们最近看到的还有其他包装功能吗?

哦,是的,装饰品!

让我们玩得开心,为装饰者写一个装饰者:

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

可以如下使用:

# 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,上一次您有这种感觉时,是在听一个人说:“了解递归之前,您必须先了解递归”。但是现在,您是否对掌握这一点感到满意?


最佳做法:装饰

  • 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。
  • 装饰器使函数调用变慢。记住这一点。
  • 您不能取消装饰功能。 (有一些技巧可以创建可以删除的装饰器,但是没有人使用它们。)因此,一旦装饰了函数,就对所有代码进行装饰。
  • 装饰器包装函数,这会使它们难以调试。 (这在 Python> = 2.5 时会更好;请参见下文。)

functools模块是 Python 2.5 中引入的。它包括函数functools.wraps() ,该函数将修饰后的函数的名称,模块和文档字符串复制到其包装器中。

(有趣的事实: functools.wraps()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

装饰器如何发挥作用?

现在有个大问题:我可以使用装饰器做什么?

看起来很酷而且功能强大,但是一个实际的例子将是很好的。好吧,这里有 1000 种可能性。经典用法是从外部库扩展功能行为(您不能对其进行修改),或者用于调试(您不希望对其进行修改,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,您几乎可以在几乎所有内容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 本身提供了几种装饰器: propertystaticmethod等。

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

这真的是一个大操场。

查看文档,以了解装饰器如何工作。这是您要求的:

from functools import wraps

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

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

@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>"

另外,您可以编写一个工厂函数,该函数返回一个装饰器,该装饰器将装饰后的函数的返回值包装在传递给工厂函数的标记中。例如:

from functools import wraps

def wrap_in_tag(tag):
    def factory(func):
        @wraps(func)
        def decorator():
            return '<%(tag)s>%(rv)s</%(tag)s>' % (
                {'tag': tag, 'rv': func()})
        return decorator
    return factory

这使您可以编写:

@wrap_in_tag('b')
@wrap_in_tag('i')
def say():
    return 'hello'

要么

makebold = wrap_in_tag('b')
makeitalic = wrap_in_tag('i')

@makebold
@makeitalic
def say():
    return 'hello'

就个人而言,我会以不同的方式编写装饰器:

from functools import wraps

def wrap_in_tag(tag):
    def factory(func):
        @wraps(func)
        def decorator(val):
            return func('<%(tag)s>%(val)s</%(tag)s>' %
                        {'tag': tag, 'val': val})
        return decorator
    return factory

这将产生:

@wrap_in_tag('b')
@wrap_in_tag('i')
def say(val):
    return val
say('hello')

不要忘记装饰器语法是其速记形式的构造:

say = wrap_in_tag('b')(wrap_in_tag('i')(say)))

看来其他人已经告诉您如何解决问题。希望这可以帮助您了解什么是装饰器。

装饰器只是语法糖。

这个

@decorator
def func():
    ...

扩展到

def func():
    ...
func = decorator(func)

当然,您也可以从装饰器函数返回 lambda:

def makebold(f): 
    return lambda: "<b>" + f() + "</b>"
def makeitalic(f): 
    return lambda: "<i>" + f() + "</i>"

@makebold
@makeitalic
def say():
    return "Hello"

print say()

Python 装饰器为其他功能添加了额外的功能

斜体装饰器可能像

def makeitalic(fn):
    def newFunc():
        return "<i>" + fn() + "</i>"
    return newFunc

请注意,函数是在函数内部定义的。它的主要作用是用新定义的功能替换功能。例如我有这个课

class foo:
    def bar(self):
        print "hi"
    def foobar(self):
        print "hi again"

现在说,我希望两个函数在完成之前和之后都打印 “---”。我可以在每个打印语句之前和之后添加打印 “---”。但是因为我不喜欢重复自己,所以我会做一个装饰工

def addDashes(fn): # notice it takes a function as an argument
    def newFunction(self): # define a new function
        print "---"
        fn(self) # call the original function
        print "---"
    return newFunction
    # Return the newly defined function - it will "replace" the original

所以现在我可以将课程更改为

class foo:
    @addDashes
    def bar(self):
        print "hi"

    @addDashes
    def foobar(self):
        print "hi again"

有关装饰器的更多信息,请访问 http://www.ibm.com/developerworks/linux/library/l-cpdecor.html。

可以制作两个单独的装饰器,按您的意愿进行操作,如下所示。请注意,在wrapped()函数的声明中使用了*args, **kwargs ,该声明支持具有多个参数的修饰函数(对于示例say()函数而言,这实际上不是必需的,但出于一般性考虑而包括在内)。

出于类似的原因, functools.wraps装饰器用于将包装函数的元属性更改为要装饰的函数的元属性。这使得错误消息和嵌入式功能文档( func.__doc__ )成为修饰后的功能的消息,而不是被wrapped()的。

from functools import wraps

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

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

@makebold
@makeitalic
def say():
    return 'Hello'

print(say())  # -> <b><i>Hello</i></b>

细化

如您所见,这两个装饰器中有很多重复的代码。鉴于这种相似性,您最好改成一个实际上是装饰工厂的通用产品,换句话说,就是制造其他装饰的装饰器功能。这样,代码重复将更少,并允许遵循DRY原则。

def html_deco(tag):
    def decorator(fn):
        @wraps(fn)
        def wrapped(*args, **kwargs):
            return '<%s>' % tag + fn(*args, **kwargs) + '</%s>' % tag
        return wrapped
    return decorator

@html_deco('b')
@html_deco('i')
def greet(whom=''):
    return 'Hello' + (' ' + whom) if whom else ''

print(greet('world'))  # -> <b><i>Hello world</i></b>

为了使代码更具可读性,可以为工厂生成的装饰器分配一个更具描述性的名称:

makebold = html_deco('b')
makeitalic = html_deco('i')

@makebold
@makeitalic
def greet(whom=''):
    return 'Hello' + (' ' + whom) if whom else ''

print(greet('world'))  # -> <b><i>Hello world</i></b>

甚至像这样组合它们:

makebolditalic = lambda fn: makebold(makeitalic(fn))

@makebolditalic
def greet(whom=''):
    return 'Hello' + (' ' + whom) if whom else ''

print(greet('world'))  # -> <b><i>Hello world</i></b>

效率

尽管上面的示例可以完成所有工作,但是当同时应用多个装饰器时,生成的代码会以大量的函数调用形式涉及大量开销。这可能无关紧要,具体取决于确切的用法(例如,可能受 I / O 限制)。

如果装饰函数的速度很重要,则可以通过编写稍有不同的装饰器工厂函数(可一次添加所有标记)来将开销保持在一个额外的函数调用中,因此它可以生成避免发生附加函数调用的代码通过为每个标签使用单独的装饰器。

这需要装饰器本身中的更多代码,但这仅在将其应用于函数定义时才运行,而不是在调用它们本身时才运行。当通过使用lambda函数创建更具可读性的名称时,这同样适用。样品:

def multi_html_deco(*tags):
    start_tags, end_tags = [], []
    for tag in tags:
        start_tags.append('<%s>' % tag)
        end_tags.append('</%s>' % tag)
    start_tags = ''.join(start_tags)
    end_tags = ''.join(reversed(end_tags))

    def decorator(fn):
        @wraps(fn)
        def wrapped(*args, **kwargs):
            return start_tags + fn(*args, **kwargs) + end_tags
        return wrapped
    return decorator

makebolditalic = multi_html_deco('b', 'i')

@makebolditalic
def greet(whom=''):
    return 'Hello' + (' ' + whom) if whom else ''

print(greet('world'))  # -> <b><i>Hello world</i></b>

做同样事情的另一种方式:

class bol(object):
  def __init__(self, f):
    self.f = f
  def __call__(self):
    return "<b>{}</b>".format(self.f())

class ita(object):
  def __init__(self, f):
    self.f = f
  def __call__(self):
    return "<i>{}</i>".format(self.f())

@bol
@ita
def sayhi():
  return 'hi'

或者,更灵活:

class sty(object):
  def __init__(self, tag):
    self.tag = tag
  def __call__(self, f):
    def newf():
      return "<{tag}>{res}</{tag}>".format(res=f(), tag=self.tag)
    return newf

@sty('b')
@sty('i')
def sayhi():
  return 'hi'

如何在 Python 中制作两个装饰器,以完成以下工作?

调用时需要以下函数:

@makebold
@makeitalic
def say():
    return "Hello"

返回:

<b><i>Hello</i></b>

简单的解决方案

为了最简单地执行此操作,请使装饰器返回关闭函数(闭包)的 lambda(匿名函数)并调用它:

def makeitalic(fn):
    return lambda: '<i>' + fn() + '</i>'

def makebold(fn):
    return lambda: '<b>' + fn() + '</b>'

现在根据需要使用它们:

@makebold
@makeitalic
def say():
    return 'Hello'

现在:

>>> say()
'<b><i>Hello</i></b>'

简单解决方案的问题

但是我们似乎几乎失去了原来的功能。

>>> say
<function <lambda> at 0x4ACFA070>

为了找到它,我们需要深入研究每个 lambda 的闭包,其中一个埋藏在另一个中:

>>> say.__closure__[0].cell_contents
<function <lambda> at 0x4ACFA030>
>>> say.__closure__[0].cell_contents.__closure__[0].cell_contents
<function say at 0x4ACFA730>

因此,如果我们在此函数上放上文档,或者希望能够装饰带有多个参数的函数,或者我们只想知道在调试会话中要查看的函数,则需要对我们做更多的事情包装纸。

功能齐全的解决方案 - 克服了大多数此类问题

我们在标准库中提供了functools模块中的装饰器wraps

from functools import wraps

def makeitalic(fn):
    # must assign/update attributes from wrapped function to wrapper
    # __module__, __name__, __doc__, and __dict__ by default
    @wraps(fn) # explicitly give function whose attributes it is applying
    def wrapped(*args, **kwargs):
        return '<i>' + fn(*args, **kwargs) + '</i>'
    return wrapped

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

不幸的是,仍然有一些样板,但这大约很简单。

在 Python 3 中,默认情况下__annotations__分配__qualname____annotations__

所以现在:

@makebold
@makeitalic
def say():
    """This function returns a bolded, italicized 'hello'"""
    return 'Hello'

现在:

>>> say
<function say at 0x14BB8F70>
>>> help(say)
Help on function say in module __main__:

say(*args, **kwargs)
    This function returns a bolded, italicized 'hello'

结论

因此,我们看到, wraps包裹函数几乎可以执行所有操作,除了确切告诉我们该函数将其用作参数的情况。

还有其他模块可以尝试解决该问题,但是标准库中尚未提供该解决方案。

装饰器采用函数定义并创建一个新函数,该函数执行该函数并转换结果。

@deco
def do():
    ...

等效于:

do = deco(do)

例:

def deco(func):
    def inner(letter):
        return func(letter).upper()  #upper
    return inner

这个

@deco
def do(number):
    return chr(number)  # number to letter

相当于这个

def do2(number):
    return chr(number)

do2 = deco(do2)

65 <=>'a'

print(do(65))
print(do2(65))
>>> B
>>> B

要了解装饰器,必须注意,装饰器创建了一个新的函数 do,该函数在内部执行函数并转换结果。