python模块化、对象比较与拷贝、函数装饰传递、装饰器.zip

# coding:utf-8 # 第17课 强大的装饰器 import functools import time if __name__ == "__main__": # 函数作为变量 def func(message): print("收到一个消息:{}".format(message)) send_message = func send_message("hello world") # 函数作为参数 def root_call(fun, message): print(fun(message)) root_call(func, "函数参数") # 函数嵌套 def fund(message): def get_message(message): print("收到一个消息:{}".format(message)) return get_message(message) fund("函数嵌套") # 闭包 def func_closure(): def get_message(message): print("收到一个消息:{}".format(message)) return get_message send_message = func_closure() send_message("返回函数对象(闭包)") # 简单装饰器例子 def my_decorator(func): def wrapper(): print("装饰器") func() return wrapper def greet(): print("你好") greet = my_decorator(greet) greet() # 原函数还是原函数吗？ print(greet.__name__) print(help(greet)) # 使用functools.wrap def my_decorator2(func): @functools.wraps(func) def wrapper(*args, **kwargs): print("functools的装饰器") func(*args, **kwargs) return wrapper @my_decorator2 def greet2(message): print(message) greet2("functools") print(greet2.__name__) # 类装饰器 class Count(): def __init__(self, func): self.func = func self.num_calls = 0 def __call__(self, *args, **kwargs): self.num_calls += 1 print("num of call is: {}".format(self.num_calls)) return self.func(*args, **kwargs) @Count def example(): print("类装饰器") example() example() # 装饰器嵌套 def my_decorator_a(func): @functools.wraps(func) def wrapper(*args, **kwargs): print("functools的装饰器a") func(*args, **kwargs) return wrapper def my_decorator_b(func): @functools.wraps(func) def wrapper(*args, **kwargs): print("functools的装饰器b") func(*args, **kwargs) return wrapper @my_decorator_a @my_decorator_b def greet3(message): print(message) greet3("functools") print(greet3.__name__) # 应用举例 给函数加上计时功能 def log_execution_time(func): @functools.wraps(func) def wrapper(*args, **kwargs): start = time.perf_counter() res = func(*args, **kwargs) end = time.perf_counter() print("函数{}运行耗时{}秒".format(func.__name__, end-start)) return res return wrapper @log_execution_time def add(n): s = 0 for i in range(n): s += i return s res = add(10000) print(res) @log_execution_time def multiply(n): s = 1 for i in range(n): s = s*(i+1) return s res = multiply(10000) print(res)