Python基础：Python中的装饰器和实现通用的装饰器，实现对任意函数的性能统计测试

# 装饰器

# 定义装饰器
def decorator(f):
    def innerfunc():
        print("调用前")
        f()
        print("调用后")
        pass
    return innerfunc  # 外部函数 要返回内部函数
    pass

@decorator
def calSum():
    print("执行函数代码")
    pass

calSum() # 调用的时候还是调用原函数

# 装饰器传参
# 带普通参数的装饰器
def deco2(f):
    def innerFunc(x, y):
        print("传入了参数：")
        result = f(x, y)
        print("哈哈")
        return result
        pass
    return innerFunc
    pass

@deco2
def cal(x, y):
    print(x + y)
    return x+y
    pass

r = cal(10, 20)
print(r)

# 如果不用装饰器 也是python的必考笔试题
import time
def func1(a, b):
    startTime = time.clock()
    a = 1
    b = 2
    c = a + b
    d = 10000*10000
    time.sleep(0.1)
    endTime = time.clock()
    print(endTime - startTime)
    pass

def func2(a, b, c):
    startTime = time.clock() # 代码是侵入式
    a = 1
    b = 2
    c = a + b
    d = 10000*10000
    time.sleep(0.2)
    endTime = time.clock()
    print(endTime - startTime)
    pass

def func3(a, b, x=10, **kw,):
    startTime = time.clock()
    a = 1
    b = 2
    c = a + b
    d = 10000*10000
    time.sleep(0.3)
    endTime = time.clock()
    print(endTime - startTime)
    pass

# AOP 装饰器实现性能测试 优秀的代码
def performance(f):
    def innerfunc(*argv, **kw):
        startTime = time.clock()
        f(*argv, **kw)
        endTime = time.clock()
        print("函数" + f.__str__() + "执行了：", endTime - startTime)
        pass
    return innerfunc
    pass

@performance
def func4(a, b):
    a = 1
    b = 2
    c = a + b
    d = 10000*10000
    time.sleep(0.1)
    pass

@performance
def func5(a, b, c, *argv):
    print(a + b)
    a = 1
    b = 2
    c = a + b
    d = 10000*10000
    time.sleep(0.2)
    pass

@performance
def func6(a, b, x=10, **kw):
    a = 1
    b = 2
    c = a + b
    d = 10000*10000
    time.sleep(0.3)
    pass

func4(10, 20)
func5(10, 20, 30, 1, 2, 3, 4, 5)
func6(1,2,x=20, y=1)