2019最新小白搭建ss

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2019最新小白搭建ss

我爱科学 2018-10-18 10:44:30 浏览11079
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转载www.shenrenshequ.com
为了理解装饰器,你首先必须知道 Python 中的函数都是 object 对象。 这非常重要。让我们通过一个例子来看看原因。

Python

def shout(word='yes'):

return word.capitalize() + '!'

print shout()

outputs : 'Yes!'

作为一个 object 对象,你可以把一个函数分配给一个变量,就像是

其他 object 对象一样

scream = shout

请注意我们并没有使用括号:因此我们没有调用函数,我们只是把函数 shout 赋值给变量 scream

这意味着我们可以通过 scream 调用 shout 函数

print scream()

outputs : 'Yes!'

除了这些,这还意味着你可以移除旧的函数名 shout,

之后依然可以通过 scream 访问函数

del shout
try:

print shout()

except NameError as e:

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

print scream()

outputs: 'Yes!'

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def shout(word='yes'):

return word.capitalize() + '!'

print shout()

outputs : 'Yes!'

作为一个 object 对象,你可以把一个函数分配给一个变量,就像是

其他 object 对象一样

scream = shout

请注意我们并没有使用括号:因此我们没有调用函数,我们只是把函数 shout 赋值给变量 scream

这意味着我们可以通过 scream 调用 shout 函数

print scream()

outputs : 'Yes!'

除了这些,这还意味着你可以移除旧的函数名 shout,

之后依然可以通过 scream 访问函数

del shout
try:

print shout()

except NameError as e:

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

print scream()

outputs: 'Yes!'

记住上面的内容,一会我们还会用得到。

Python 函数另一个有趣的性质在于它们可以。。。在另一个函数内部定义!

Python

def talk():

# 你可以在 `talk` 函数临时定义一个函数
def whisper(word='yes'):
    return word.lower() + '...'

# ... 之后直接使用这个函数

print whisper()

你可以调用 talk 函数,每次调用这个函数都会定义 whisper 函数,并且

talk 函数中调用 whisper 函数

talk()

outputs:

"yes..."

但是 whisper 函数在 talk 函数外部并不存在:

try:

print whisper()

except NameError as e:

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

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def talk():

# 你可以在 `talk` 函数临时定义一个函数
def whisper(word='yes'):
    return word.lower() + '...'

# ... 之后直接使用这个函数

print whisper()

你可以调用 talk 函数,每次调用这个函数都会定义 whisper 函数,并且

talk 函数中调用 whisper 函数

talk()

outputs:

"yes..."

但是 whisper 函数在 talk 函数外部并不存在:

try:

print whisper()

except NameError as e:

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

函数引用
现在是比较有趣的部分。。。

你已经知道了函数是 object 对象。此外,函数还:

可以像变量一样赋值
可以在另一个函数内部定义
这表示 函数可以 return 另一个函数。看下面吧!

Python

def getTalk(kind='shout'):

# 我们临时定义一个函数
def shout(word='yes'):
    return word.capitalize() + '!'

def whisper(word='yes'):
    return word.lower() + '...'

# 然后我们返回上面两个函数中的一个
if kind == 'shout':
    # 我们并没有使用 '()' 。因此我们并没有调用函数; 
    # 相反,我们返回了函数对象  
    return shout  
else:
    return whisper

你该怎样使用这个奇怪的功能呢?

调用这个函数,然后把结果赋值给一个变量

talk = getTalk()

你可以看到 talk 是一个函数对象:

print talk

outputs :

The object is the one returned by the function:

这个对象是由一个函数返回的

print talk()

outputs : Yes!

如果你觉得奇怪的话,你甚至可以直接使用它

print getTalk('whisper')()

outputs : yes...

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def getTalk(kind='shout'):

# 我们临时定义一个函数
def shout(word='yes'):
    return word.capitalize() + '!'

def whisper(word='yes'):
    return word.lower() + '...'

# 然后我们返回上面两个函数中的一个
if kind == 'shout':
    # 我们并没有使用 '()' 。因此我们并没有调用函数; 
    # 相反,我们返回了函数对象  
    return shout  
else:
    return whisper

你该怎样使用这个奇怪的功能呢?

调用这个函数,然后把结果赋值给一个变量

talk = getTalk()

你可以看到 talk 是一个函数对象:

print talk

outputs :

The object is the one returned by the function:

这个对象是由一个函数返回的

print talk()

outputs : Yes!

如果你觉得奇怪的话,你甚至可以直接使用它

print getTalk('whisper')()

outputs : yes...

但等等…还有一些内容!

如果你可以 return 一个函数,那么你也可以把函数当作参数传递:

Python

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!

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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,你已经掌握了装饰器所需的全部知识。正如你所见,装饰器是“包装器”,也就是说 它们允许你在它们装饰的函数的前面和后面运行其他代码 ,而不必修改函数本身。

动手制作装饰器
你应该怎样动手制作:

Python

装饰器是把其他函数作为参数的函数

def my_shiny_new_decorator(a_function_to_decorate):

# 在装饰器内部,装饰器临时创建了一个函数: 包装器。
# 这个函数把原来的函数包装起来
# 因此它可以在原函数的前面和后面执行其他代码。  
def the_wrapper_around_the_original_function():
    # 把你想在原函数被调用前执行的代码写在这里
    print 'Before the function runs'

    # 在这里调用原函数(使用括号)
    a_function_to_decorate()

    # 把你想在原函数调用后执行的代码写在这里
    print 'After the function runs'

# 到目前为止,`a_function_to_decorate` 还从未执行过。
# 我们返回刚刚创建的包装器
# 包装器中包含了原函数和在原函数之前/之后执行的代码。现在已经可以使用了!  
return the_wrapper_around_the_original_function

现在想象一下你创建了一个函数,你不想再改动它了。

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

好的,你可以装饰这个函数来扩展它的功能

只需要把它传递给装饰器,之后就会动态地包装在你需要的任何代码中,然后返回一个满足你需求的新函数:

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

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装饰器是把其他函数作为参数的函数

def my_shiny_new_decorator(a_function_to_decorate):

# 在装饰器内部,装饰器临时创建了一个函数: 包装器。
# 这个函数把原来的函数包装起来
# 因此它可以在原函数的前面和后面执行其他代码。  
def the_wrapper_around_the_original_function():
    # 把你想在原函数被调用前执行的代码写在这里
    print 'Before the function runs'

    # 在这里调用原函数(使用括号)
    a_function_to_decorate()

    # 把你想在原函数调用后执行的代码写在这里
    print 'After the function runs'

# 到目前为止,`a_function_to_decorate` 还从未执行过。
# 我们返回刚刚创建的包装器
# 包装器中包含了原函数和在原函数之前/之后执行的代码。现在已经可以使用了!  
return the_wrapper_around_the_original_function

现在想象一下你创建了一个函数,你不想再改动它了。

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

好的,你可以装饰这个函数来扩展它的功能

只需要把它传递给装饰器,之后就会动态地包装在你需要的任何代码中,然后返回一个满足你需求的新函数:

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,你希望每次你调用 a_stand_alone_function 的时候,实际上 a_stand_alone_function_decorated 会被调用。也就是说,这只是用 my_shiny_new_decorator 返回的函数重写了 a_stand_alone_function 函数:

Python

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

你猜怎样着?这实际上就是装饰器的原理!

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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

你猜怎样着?这实际上就是装饰器的原理!

装饰器解密
和前面相同的例子,但是使用了装饰器语法:

Python

@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

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@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

就是这样,装饰器就是这么简单。 @decorator 只是下面形式的简写:

Python

another_stand_alone_function = my_shiny_new_decorator(another_stand_alone_function)
1
another_stand_alone_function = my_shiny_new_decorator(another_stand_alone_function)
装饰器只是一个 pythonic 的装饰器设计模式的变种。Python 中内置了许多种传统的设计模式来简化开发过程(例如迭代器)。

当然,你可以叠加多个装饰器:

Python

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~

<______/>

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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 的装饰器语法:

Python

@bread
@ingredients
def sandwich(food='--ham--'):

print food

sandwich()

outputs:

''''''>

tomatoes

--ham--

~salad~

<______/>

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@bread
@ingredients
def sandwich(food='--ham--'):

print food

sandwich()

outputs:

''''''>

tomatoes

--ham--

~salad~

<______/>

你设置装饰器的顺序很重要:

Python

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

print food

strange_sandwich()

outputs:

tomatoes

''''''>

--ham--

<______/>

~salad~

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

print food

strange_sandwich()

outputs:

tomatoes

''''''>

--ham--

<______/>

~salad~

现在:是时候回答问题了。。。
现在你很容易就知道怎样回答这个问题了:

Python

生成粗体(bold)的装饰器

def makebold(fn):

# 装饰器返回的新函数
def wrapper():
    # 在之前和之后插入其他代码
    return '<b>' + fn() + '</b>'
return wrapper

生成斜体的装饰器

def makeitalic(fn):

# 装饰器返回的新函数
def wrapper():
    # 在函数执行前后插入一些代码
    return '<i>' + fn() + '</i>'
return wrapper

@makebold
@makeitalic
def say():

return 'hello'

print say()

outputs: hello

和上面完全等价的形式

def say():

return 'hello'

say = makebold(makeitalic(say))

print say()

outputs: hello

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生成粗体(bold)的装饰器

def makebold(fn):

# 装饰器返回的新函数
def wrapper():
    # 在之前和之后插入其他代码
    return '<b>' + fn() + '</b>'
return wrapper

生成斜体的装饰器

def makeitalic(fn):

# 装饰器返回的新函数
def wrapper():
    # 在函数执行前后插入一些代码
    return '<i>' + fn() + '</i>'
return wrapper

@makebold
@makeitalic
def say():

return 'hello'

print say()

outputs: hello

和上面完全等价的形式

def say():

return 'hello'

say = makebold(makeitalic(say))

print say()

outputs: hello

现在你该放下轻松的心态,好好看看装饰器的高级使用方法了。

把装饰器传到下一层去
把参数传递给被装饰的函数
Python

这并不是黑魔法,你只是让包装器传递参数而已

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

因为当你调用装饰器返回的函数时,实际上你在调用包装器,把参数传递给包装器,这也就完成了把参数传递给装饰器函数

@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

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这并不是黑魔法,你只是让包装器传递参数而已

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

因为当你调用装饰器返回的函数时,实际上你在调用包装器,把参数传递给包装器,这也就完成了把参数传递给装饰器函数

@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

装饰器方法
关于 Python 的一个优点就是方法和函数本质本质上是一样的。二者唯一的区别就是方法的第一个参数是对当前对象的引用 (self)。

这意味着你可以按照同样的方式为方法创建装饰器!只要记得考虑 self 就可以了:

Python

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?

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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?

如果你在创建通用的装饰器 — 一个适用于任何函数或者方法的装饰器,无论参数是什么 — 那么只要使用 args, *kwargs就可以了:

Python

def a_decorator_passing_arbitrary_arguments(function_to_decorate):

# 包装器接受任何参数
def a_wrapper_accepting_arbitrary_arguments(*args, **kwargs):
    print 'Do I have args?:'
    print args
    print kwargs

    # 接下来解包参数,也就是这里的 *args, **kwargs
    # 如果你不熟悉解包,可以浏览这个:
    # 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): #你可以在这里添加默认值
    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?

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def a_decorator_passing_arbitrary_arguments(function_to_decorate):

# 包装器接受任何参数
def a_wrapper_accepting_arbitrary_arguments(*args, **kwargs):
    print 'Do I have args?:'
    print args
    print kwargs

    # 接下来解包参数,也就是这里的 *args, **kwargs
    # 如果你不熟悉解包,可以浏览这个:
    # 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): #你可以在这里添加默认值
    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?

把参数传递给装饰器
太棒了,现在你对于把参数传递给装饰器本身有什么看法呢?

这可能有点奇怪,因为装饰器必须接收一个函数作为参数。因此,你可能无法直接把装饰器函数作为参数传递给另一个装饰器。

在得到答案之前,让我们写一个小的例子:

Python

装饰器是普通函数

def my_decorator(func):

print 'I am an ordinary function'
def wrapper():
    print 'I am function returned by the decorator'
    func()
return wrapper

因此你可以在没有任何 '@' 的情况下调用它

def lazy_function():

print 'zzzzzzzz'

decorated_function = my_decorator(lazy_function)

outputs: I am an ordinary function

上面的函数输出 'I am an ordinary function' ,因为这实际上就是我们直接调用函数的结果。没什么好奇怪的。

@my_decorator
def lazy_function():

print 'zzzzzzzz'

outputs: I am an ordinary function

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装饰器是普通函数

def my_decorator(func):

print 'I am an ordinary function'
def wrapper():
    print 'I am function returned by the decorator'
    func()
return wrapper

因此你可以在没有任何 '@' 的情况下调用它

def lazy_function():

print 'zzzzzzzz'

decorated_function = my_decorator(lazy_function)

outputs: I am an ordinary function

上面的函数输出 'I am an ordinary function' ,因为这实际上就是我们直接调用函数的结果。没什么好奇怪的。

@my_decorator
def lazy_function():

print 'zzzzzzzz'

outputs: I am an ordinary function

结果是一模一样的:my_decorator 被调用了。因此当你使用 @my_decorator 时,Python 会调用 “my_decorator” 变量所代表的函数。

这很重要!你提供的这个变量可以指向装饰器,也可以不指向。

让我们增加点难度。

Python

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

让我们创建一个装饰器。本质上是一个新函数

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

然后我们装饰下面这个函数

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

调用这个函数

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.

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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

让我们创建一个装饰器。本质上是一个新函数

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

然后我们装饰下面这个函数

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

调用这个函数

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.

没什么意料之外的事情发生。

我们再做一次上面的事情,只不过这一次取消掉所有的中间变量:

Python

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.

最后:

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.

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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.

最后:

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.

让它更短一下:

Python

@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.

最后:

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.

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@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.

最后:

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.

你注意到了吗?我们调用了一个 @ 语法的函数! :-)

所以,回到装饰器的参数上面来。如果我们可以使用函数生成一个临时的装饰器,我们也可以把参数传递给那个函数,对吗?

Python

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):
    # 传递参数的能力来自于闭包
    # 如果你不了解闭包,那也没关系,
    # 或者你也可以阅读 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

    # 不要混淆装饰器参数和函数参数!  
    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

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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):
    # 传递参数的能力来自于闭包
    # 如果你不了解闭包,那也没关系,
    # 或者你也可以阅读 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

    # 不要混淆装饰器参数和函数参数!  
    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

最后得到的就是:带参数的装饰器。参数可以设置为变量:

Python

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

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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

如你所见,你可以使用这个技巧向装饰器传递参数,就像是向普通函数传递一样。如果你愿意的话,你甚至可以使用 args, *kwargs。但记住,装饰器只会被调用一次。只在 Python 导入脚本的时候运行。在这之后你就无法动态设置参数了。当你执行 import x 之后,函数已经被装饰了,因此之后你无法改变任何东西。

练习: 装饰一个装饰器
好的,作为奖励,我会提供你一段代码允许装饰器接收任何参数。毕竟,为了接收参数,我们会用另一个函数创建装饰器。

我们包装一下装饰器。

我们最近看到的有包装函数的还有什么呢?

对了,就是装饰器!

让我们做点有趣的事,写一个装饰器的装饰器:

Python

def decorator_with_args(decorator_to_enhance):

"""
这个函数是被用作装饰器。
它会装饰其他函数,被装饰的函数也是一个装饰器。
喝杯咖啡吧。
它允许任何装饰器接收任意个参数,
这样你就不会为每次都要考虑怎样处理而头疼了
"""

# 我们使用同样的技巧来传递参数
def decorator_maker(*args, **kwargs):
    # 我们创建一个仅可以接收一个函数的临时装饰器
    # 但无法从 maker 传递参数 
    def decorator_wrapper(func):
        # 原装饰器返回的结果
        # 其实只是一个普通函数(这个函数返回一个函数)。
        # 唯一的陷阱是: 装饰器必须有特定的格式,否则无法运行:   
        return decorator_to_enhance(func, *args, **kwargs)
    return decorator_wrapper
return decorator_maker

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def decorator_with_args(decorator_to_enhance):

"""
这个函数是被用作装饰器。
它会装饰其他函数,被装饰的函数也是一个装饰器。
喝杯咖啡吧。
它允许任何装饰器接收任意个参数,
这样你就不会为每次都要考虑怎样处理而头疼了
"""

# 我们使用同样的技巧来传递参数
def decorator_maker(*args, **kwargs):
    # 我们创建一个仅可以接收一个函数的临时装饰器
    # 但无法从 maker 传递参数 
    def decorator_wrapper(func):
        # 原装饰器返回的结果
        # 其实只是一个普通函数(这个函数返回一个函数)。
        # 唯一的陷阱是: 装饰器必须有特定的格式,否则无法运行:   
        return decorator_to_enhance(func, *args, **kwargs)
    return decorator_wrapper
return decorator_maker

可以像下面这样使用:

Python

创建一个用作装饰器的函数。然后加上一个装饰器 :-)

不要忘记,格式是 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

然后用全新的装饰器装饰你的函数。

@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!

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创建一个用作装饰器的函数。然后加上一个装饰器 :-)

不要忘记,格式是 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

然后用全新的装饰器装饰你的函数。

@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,上次你有这种感觉,是在听一个人说:“在理解递归之前,你必须首先理解递归” 时。但现在,掌握了这个之后你不觉得很棒吗?

最佳实践: 装饰器
装饰器在 Python 2.4 引进,因此确保你的代码运行的 Python 版本 >=2.4
装饰器会拖慢函数调用速度。请牢记
你无法解除装饰一个函数。 (确实 有 一些技巧可以创建允许解除装饰的装饰器,但是没人会使用它们。)因此一旦函数被装饰了,所有这个函数的代码就都装饰了。
装饰器包装函数,会使得函数更难调试。 (从 Python >=2.5 有所好转;看下文。)
functools 模块在 Python 2.5 引进。模块中包含了函数 functools.wraps() ,这个函数会把被装饰函数的名字,模块名,docstring 都复制到它的包装器中。

(有趣的事情是: functools.wraps() 是个装饰器!)

Python

至于调试,stacktrace 输出函数的 name

def foo():

print 'foo'

print foo.__name__

outputs: foo

有了装饰器之后,有点混乱

def bar(func):

def wrapper():
    print 'bar'
    return func()
return wrapper

@bar
def foo():

print 'foo'

print foo.__name__

outputs: wrapper

functools 可以改善上面的情况

import functools

def bar(func):

# 我们认为 `wrapper` 正在包装 `func` 
# 神奇的事情发生了 
@functools.wraps(func)
def wrapper():
    print 'bar'
    return func()
return wrapper

@bar
def foo():

print 'foo'

print foo.__name__

outputs: foo

@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: property ,staticmethod,等

Django 使用装饰器来管理缓存,查看权限。
Twisted 用它来伪造内联异步函数调用。
装饰器的用途确实很广。

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