学习笔记-装饰器

一. 知识铺垫

函数嵌套：

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

函数作为参数：

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

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 二. 装饰器

1.概念

　　装饰器是修改函数功能的函数

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()

 　　使用@符号生成被装饰函数

@a_new_decorator
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 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)

　　问题：打印被装饰函数名，会发现函数"a_function_requiring_decoration"被函数“warpTheFunction”代替了，即装饰器重写了原函数的名字和注释文档。

print(a_function_requiring_decoration.__name__)
# Output: wrapTheFunction

　　解决方法：使用functools.wraps函数

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():
    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

 2. 带参数的装饰器

　　在装饰器函数上加一层“带参数的包裹函数”

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

　　装饰器执行顺序：logit() ——> @logging_decorator ——> wrapped_function() ——> func() 即 myfunc1()/myfunc2() 

3.装饰器类

　　在装饰器的功能上加上类的“继承”优势，可以在子类中实现“新功能”，该“新功能”会被装饰到目标函数上。

　　以装饰器类的方式重构logit()

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

　　给logit创建子类，添加发送Email功能

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

4.类装饰器

5.使用场景

• 授权：

from functools import wraps
 
def requires_auth(f):
    @wraps(f)
    def decorated(*args, **kwargs):
        auth = request.authorization
        if not auth or not check_auth(auth.username, auth.password):
            authenticate()
        return f(*args, **kwargs)
    return decorated

• 日志：

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

• 多种参数：

 

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参考资料：

　　https://www.runoob.com/w3cnote/python-func-decorators.html