python study 实例总结 - “装饰器”（Decorator）

1.请设计一个decorator，它可作用于任何函数上，并打印该函数的执行时间：

# -*- coding: utf-8 -*-
import time, functools
import functools

   def metric(fn):
    @functools.wraps(fn)
    def wrapper(*args, **kw):
        t0 = time.time()
        result = fn(*args, **kw)
        print('%s executed in %.4f ms' % (fn.__name__, time.time() - t0))
        return result
    return wrapper

# 测试
@metric
def fast(x, y):
    time.sleep(0.0012)
    return x + y;

@metric
def slow(x, y, z):
    time.sleep(0.1234)
    return x * y * z;

f = fast(11, 22)
s = slow(11, 22, 33)
if f != 33:
    print('测试失败!')
elif s != 7986:
    print('测试失败!')
 Run

#结果：
fast executed in 0.0020 ms 
slow executed in 0.1240 ms

2.打印时间

import functools

def log(func):
    @functools.wraps(func)
    def wrapper(*args, **kw):
        print('call %s():' % func.__name__)
        return func(*args, **kw)
    return wrapper

@log
def now():
    print('2015-3-25')

now()

def logger(text):
    def decorator(func):
        @functools.wraps(func)
        def wrapper(*args, **kw):
            print('%s %s():' % (text, func.__name__))
            return func(*args, **kw)
        return wrapper
    return decorator

@logger('DEBUG')
def today():
    print('2015-3-25')

today()
print(today.__name__)

3.请编写一个decorator，能在函数调用的前后打印出’begin call’和’end call’的日志。
再思考一下能否写出一个@log的decorator，使它既支持：

@log
def f():
    pass

又支持：

@log('execute')
def f():
    pass

---

def log(arg):
    def inner_log(text='call'):
        def decorator(func):
            @functools.wraps(func)
            def wrapper(*args, **kw):
                print('begin call')
                print('%s %s():' % (text, func.__name__))
                print('end call')
                return func(*args, **kw)
            return wrapper
        return decorator

#########################################
@log
def f():
    pass


@log('execute')
def f2():
    pass


f()  # call f():
f2()  # execute f2():