#一、无参数
#!/usr/bin/env python
# -*- coding:utf-8 -*-
# log 函数定义
# def log(f):
# def fn(x):
# print 'call '+ f.__name__ +'()...'#双下划线
# return f(x)
# return fn
# 要让 @log 自适应任何参数定义的函数，可以利用Python的 *args 和 **kw，保证任意个数的参数总是能正常调用：
def log(f):
def fn(*args, **kw):
print 'call ' + f.__name__ + '()...'
return f(*args, **kw)
return fn
@log
def factorial(n):
return reduce(lambda x,y:x*y,range(1,n+1))
print factorial(10)
@log
def add(x,y):
return x+y
print add(2,4)
#请编写一个@performance，它可以打印出函数调用的时间。
import time
def performance(f):
def fn(*args,**kwargs):
print 'call '+f.__name__+'()... at '+time.strftime('%Y-%m-%d %H:%M:%S',time.localtime(time.time()))
return f(*args,**kwargs)
return fn
@performance
def factorial(n):
return reduce(lambda x,y: x*y, range(1, n+1))
print factorial(10)
#二、带参数
#!/usr/bin/env python
# -*- coding:utf-8 -*-
#python中编写带参数decorator
import time
import functools
def performance(unit):
def perf_decorator(f):
@functools.wraps(f)
def wrapper(*args, **kw):
t1 = time.time()
r = f(*args, **kw)
t2 = time.time()
t = (t2 - t1) * 1000 if unit=='ms' else (t2 - t1)
print 'call %s() in %f %s' % (f.__name__, t, unit)
return r
return wrapper
return perf_decorator
@performance('ms')
def factorial(n):
return reduce(lambda x,y: x*y, range(1, n+1))
print factorial(10)
print factorial.__name__
