5.装饰器进阶篇

接着上一篇来

1.使用装饰器来验证函数参数的类型是否正确：

# -*- coding: utf-8 -*-
#__author:jiangjing
#date:2018/1/5

import functools
# 构建装饰器
def params_chack(*types, **kwtypes):
    def outer(func):
        def inner(*args, **kwargs):
            result = [isinstance(_param, _type) for _param, _type in zip(args, types)]
            assert all(result), "params_chack: invalid parameters"
            result = [isinstance(kwargs[_param], kwtypes[_param]) for _param in kwargs if _param in kwtypes]
            assert all(result), "params_chack: invalid parameters"
            return func(*args, **kwargs)
        return inner
    return outer

# 使用装饰器
@params_chack(int, str, c=(int, str))
def test(a, b, c):
    print("in function test04, a=%s, b=%s, c=%s" % (a, b, c))
    return 1

# 测试用例
print(test(1, "str", 1))         # 参数正确
print(test(1, "str", "abc"))     # 参数正确
print(test("str", 1, "abc"))     # 参数错误

2.使用装饰器对一些计算非常耗时、复杂的结果进行缓存：

# -*- coding: utf-8 -*-
#__author:jiangjing
#date:2018/1/5
import time

def func_cache(func):
    cache = {}
    def wrapper(*args):
        if args not in cache:
            print('没有命中缓存')
            cache[args] = func(args)
        else:
            print('命中缓存')
        return cache[args]
    return wrapper

@func_cache
def func(*args):
    #中间省略复杂的计算
    sum = 0
    for i in range(args[0][0]):
        sum = sum + i
    return sum
print(func(100000000))
print(func(100000000))

　　输出结果为：

  　　没有命中缓存
  　　4999999950000000
  　　命中缓存
  　　4999999950000000

 3.使用装饰器来实现单例模式

# -*- coding: utf-8 -*-
#__author:jiangjing
#date:2018/1/5

def singleton(cls):
    instance = {}
    def inner(*args, **kargs):
        if cls not in instance:
            instance[cls] = cls(*args, **kargs)
        return instance[cls]
    return inner

@singleton
class Test(object):
    def __init__(self, x = 0):
        self.x = x

t1 = Test(2)
t2 = Test(3)
print(id(t1))
print(id(t2))
print(t1.x)
print(t2.x)

输出为：
10309248
10309248
2
2