Python-如何制作一个功能装饰链？
发布于 2021-02-02 23:24:44
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HTML在实际的应用程序中采用这种方式-只是想了解装饰器和装饰器链接是如何工作的。
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1 个回答
-
查看文档，以了解装饰器如何工作。
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>" -
Python的函数是对象
要了解装饰器，你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…
你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
这意味着一个功能可以return另一个功能。
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使用函数，则可以将其作为参数传递：
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，你只需具备了解装饰器所需的一切。你会看到，装饰器是“包装器”，这意味着它们使你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
你将如何手动操作：
# 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，你可能希望每次调用
a_stand_alone_function时a_stand_alone_function_decorated都调用。这很简单，只需a_stand_alone_function用以下方法返回的函数覆盖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只是以下方面的捷径：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，你可以积累装饰器：
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~ #<\______/>你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，你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，你可以放开心心，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。这意味着你可以以相同的方式为方法构建装饰器！只要记住要self考虑：
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，你会说什么？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，你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
“ my_decorator”被调用。因此，当你使用时@my_decorator，你是在告诉Python调用“由变量“my_decorator”标记的”函数。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.让我们做完全一样的事情，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如你所见，你可以像使用此技巧的任何函数一样将参数传递给装饰器。你甚至可以
*args, **kwargs根据需要使用。但是请记住，装饰器仅被调用一次。就在Python导入脚本时。之后，你将无法动态设置参数。当你执行“import x”时，该函数已经被修饰，因此你无法进行任何更改。练习：装饰装饰器
好的，作为奖励，我将向你提供一个片段，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。
我们最近看到了包装功能吗？
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，上一次你有这种感觉时，是在听一个人说：“了解递归之前，你必须先了解递归”。但是现在，你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，因此请确保你的代码将在> = 2.4上运行。
- 装饰器使函数调用变慢。记住这一点。
- 你不能取消装饰功能。（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，一旦装饰了一个函数，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。）
该functools模块是在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！）# 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（你不能对其进行修改），或者用于调试（你不希望对其进行修改，因为它是临时的）。
你可以使用它们以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，使用装饰器的好处是你可以立即在几乎所有内容上使用它们而无需重写。
@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本身提供了一些装饰：property，staticmethod，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。
