timeit与时序装饰器 [英] timeit versus timing decorator
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问题描述
我正在尝试计时一些代码.首先,我使用了一个定时装饰器:
I'm trying to time some code. First I used a timing decorator:
#!/usr/bin/env python
import time
from itertools import izip
from random import shuffle
def timing_val(func):
def wrapper(*arg, **kw):
'''source: http://www.daniweb.com/code/snippet368.html'''
t1 = time.time()
res = func(*arg, **kw)
t2 = time.time()
return (t2 - t1), res, func.__name__
return wrapper
@timing_val
def time_izip(alist, n):
i = iter(alist)
return [x for x in izip(*[i] * n)]
@timing_val
def time_indexing(alist, n):
return [alist[i:i + n] for i in range(0, len(alist), n)]
func_list = [locals()[key] for key in locals().keys()
if callable(locals()[key]) and key.startswith('time')]
shuffle(func_list) # Shuffle, just in case the order matters
alist = range(1000000)
times = []
for f in func_list:
times.append(f(alist, 31))
times.sort(key=lambda x: x[0])
for (time, result, func_name) in times:
print '%s took %0.3fms.' % (func_name, time * 1000.)
收益
% test.py
time_indexing took 73.230ms.
time_izip took 122.057ms.
在这里我使用timeit:
And here I use timeit:
% python - m timeit - s '' 'alist=range(1000000);[alist[i:i+31] for i in range(0, len(alist), 31)]'
10 loops, best of 3:
64 msec per loop
% python - m timeit - s 'from itertools import izip' 'alist=range(1000000);i=iter(alist);[x for x in izip(*[i]*31)]'
10 loops, best of 3:
66.5 msec per loop
使用时间,结果实际上是相同的,但是使用定时修饰器,它显示time_indexing
的速度比time_izip
快.
Using timeit the results are virtually the same, but using the timing decorator it appears time_indexing
is faster than time_izip
.
造成这种差异的原因是什么?
What accounts for this difference?
应该相信这两种方法吗?
Should either method be believed?
如果是,哪个?
推荐答案
使用timeit.多次运行测试会给我带来更好的结果.
Use timeit. Running the test more than once gives me much better results.
func_list=[locals()[key] for key in locals().keys()
if callable(locals()[key]) and key.startswith('time')]
alist=range(1000000)
times=[]
for f in func_list:
n = 10
times.append( min( t for t,_,_ in (f(alist,31) for i in range(n))))
for (time,func_name) in zip(times, func_list):
print '%s took %0.3fms.' % (func_name, time*1000.)
->
<function wrapper at 0x01FCB5F0> took 39.000ms.
<function wrapper at 0x01FCB670> took 41.000ms.
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