Python 函数的装饰器是修改其他函数功能的函数

Introduction

首先,我们需要将 Python 中的函数作为函数对象来理解。

函数名只是引用标识名

def hi(name="yasoob"):
    return "hi " + name
 
print(hi())
# output: 'hi yasoob'
 
# 我们甚至可以将一个函数赋值给一个变量,比如
greet = hi
# 我们这里没有在使用小括号,因为我们并不是在调用hi函数
# 而是在将它放在greet变量里头。我们尝试运行下这个
 
print(greet())
# output: 'hi yasoob'
 
# 如果我们删掉旧的hi函数,看看会发生什么!
del hi
print(hi())
#outputs: NameError
 
print(greet())
#outputs: 'hi yasoob'

函数的返回值可以是函数对象

def hi(name="yasoob"):
	def greet():
        return "now you are in the greet() function"
    
	def welcome():
        return "now you are in the welcome() function"
    
    if name == "yasoob":
        return greet
    else:
        return welcome
    
a = hi()
print(a)
#outputs: <function greet at 0x7f2143c01500>
 
#上面清晰地展示了`a`现在指向到hi()函数中的greet()函数
#现在试试这个
 
print(a())
#outputs: now you are in the greet() function

函数的参数可以是函数对象

def hi():
    return "hi yasoob!"
 
def doSomethingBeforeHi(func):
    print("I am doing some boring work before executing hi()")
    print(func())

doSomethingBeforeHi(hi)
#outputs:I am doing some boring work before executing hi()
#        hi yasoob!

So what is a decorator?

def a_new_decorator(a_func):

    def wrapTheFunction():
        print("I am doing some boring work before executing a_func()")

        a_func()

        print("I am doing some boring work after executing a_func()")

    return wrapTheFunction
 
def a_function_requiring_decoration():
    print("I am the function which needs some decoration to remove my foul smell")

a_function_requiring_decoration()
#outputs: "I am the function which needs some decoration to remove my foul smell"
 
a_function_requiring_decoration = a_new_decorator(a_function_requiring_decoration)
#now a_function_requiring_decoration is wrapped by wrapTheFunction()
 
a_function_requiring_decoration()
#outputs:I am doing some boring work before executing a_func()
#        I am the function which needs some decoration to remove my foul smell
#        I am doing some boring work after executing a_func()

这段代码等价于…

@a_new_decorator
def a_function_requiring_decoration():
    """Hey you! Decorate me!"""
    print("I am the function which needs some decoration to "
          "remove my foul smell")

a_function_requiring_decoration()
#outputs: I am doing some boring work before executing a_func()
#         I am the function which needs some decoration to remove my foul smell
#         I am doing some boring work after executing a_func()
 
#the @a_new_decorator is just a short way of saying:
a_function_requiring_decoration = a_new_decorator(a_function_requiring_decoration)

但是,这样的代码存在的问题有,比如,__name__获取不到正确的函数名。

于是稍加修改,我们有了以下解释器函数的编写模板:

from functools import wraps
 
def a_new_decorator(a_func):
    @wraps(a_func)
    def wrapTheFunction():
        print("I am doing some boring work before executing a_func()")
        a_func()
        print("I am doing some boring work after executing a_func()")
    return wrapTheFunction
 
@a_new_decorator
def a_function_requiring_decoration():
    """Hey yo! Decorate me!"""
    print("I am the function which needs some decoration to "
          "remove my foul smell")

print(a_function_requiring_decoration.__name__)
# Output: a_function_requiring_decoration

Example 1

from functools import wraps
 
def logit(func):
    @wraps(func)
    def with_logging(*args, **kwargs):
        print(func.__name__ + " was called")
        return func(*args, **kwargs)
    return with_logging
 
@logit
def addition_func(x):
    """Do some math."""
   	return x + x
 

result = addition_func(4)
# Output: addition_func was called

Decorators with parameters

from functools import wraps
 
def logit(logfile='out.log'):
    def logging_decorator(func):
        @wraps(func)
        def wrapped_function(*args, **kwargs):
            log_string = func.__name__ + " was called"
            print(log_string)
            # 打开logfile,并写入内容
            with open(logfile, 'a') as opened_file:
                # 现在将日志打到指定的logfile
                opened_file.write(log_string + '\n')
            return func(*args, **kwargs)
        return wrapped_function
    return logging_decorator
 
@logit()
def myfunc1():
    pass
 
myfunc1()
# Output: myfunc1 was called
# 现在一个叫做 out.log 的文件出现了,里面的内容就是上面的字符串
 
@logit(logfile='func2.log')
def myfunc2():
    pass
 
myfunc2()
# Output: myfunc2 was called
# 现在一个叫做 func2.log 的文件出现了,里面的内容就是上面的字符串

Class of Decorator

By means of class inheritance, we could implement effects of different kinds of decorations.

from functools import wraps
 
class logit(object):
    def __init__(self, logfile='out.log'):
        self.logfile = logfile

    def __call__(self, func):
            @wraps(func)
            def wrapped_function(*args, **kwargs):
                log_string = func.__name__ + " was called"
                print(log_string)
                # 打开logfile并写入
                with open(self.logfile, 'a') as opened_file:
                    # 现在将日志打到指定的文件
                    opened_file.write(log_string + '\n')
                # 现在,发送一个通知
                self.notify()
                return func(*args, **kwargs)
            return wrapped_function

    def notify(self):
            # logit只打日志,不做别的
            pass
    
class email_logit(logit):
    '''
    一个logit的实现版本,可以在函数调用时发送email给管理员
    '''
    def __init__(self, email='admin@myproject.com', *args, **kwargs):
        self.email = email
        super(email_logit, self).__init__(*args, **kwargs)

    def notify(self):
        # 发送一封email到self.email
        # 这里就不做实现了
        pass

@logit
def myfunc1():
    pass

@email_logit
def myfunc2():
    pass

Reference