装饰器函数和装饰器类

1.装饰器函数就是把函数作为参数传给一个函数

# def a_new_decorater(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()
# a_function_requiring_decoration = a_new_decorater(a_function_requiring_decoration)
# a_function_requiring_decoration()
# @a_new_decorater
# 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()
#
# a_function_requiring_decoration = a_new_decorater(a_function_requiring_decoration)
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__)
# def decorator_name(f):
#     @wraps(f)
#     def decorated(*args,**kwargs):
#         if not can_run:
#             return "Function will not run"
#         return f(*args,**kwargs)
#     return decorated
# @decorator_name
# def fun():
#     return ("Function is running")
# can_run = True
# print(fun())
# can_run = False
# print(fun())
#认证
# 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(0)
#         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)
# print(result)
#一个类实例也可以变成一个可调用对象，只需要实现一个特殊方法__call__()。
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
# 这个实现有一个附加优势，在于比嵌套函数的方式更加整洁，而且包裹一个函数还是使用跟以前一样的语法：
@logit()
def myfunc1():
    pass
# 现在，我们给logit创建子类，来添加email的功能(虽然email这个话题不会在这里展开)。
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
# 从现在起，@email_logit将会和@logit产生同样的效果，但是在打日志的基础上，还会多发送一封邮件给管理员。