[英]python: slow timeit() function
When I run the code below outside of timeit(), it appears to complete instantaneously. 当我在timeit()之外运行下面的代码时,它似乎立即完成。 However when I run it within the timeit() function, it takes much longer.
但是当我在timeit()函数中运行它时,需要更长的时间。 Why?
为什么?
>>> import timeit
>>> t = timeit.Timer("3**4**5")
>>> t.timeit()
16.55522028637718
Using: Python 3.1 (x86) - AMD Athlon 64 X2 - WinXP (32 bit) 使用:Python 3.1(x86) - AMD Athlon 64 X2 - WinXP(32位)
The timeit()
function runs the code many times (default one million) and takes an average of the timings. timeit()
函数多次运行代码(默认为100万)并取平均值。
To run the code only once, do this: 要仅运行一次代码,请执行以下操作:
t.timeit(1)
but that will give you skewed results - it repeats for good reason. 但这会给你带来不正确的结果 - 它有充分的理由重复。
To get the per-loop time having let it repeat, divide the result by the number of loops. 为了让每个循环时间让它重复,将结果除以循环次数。 Use a smaller value for the number of repeats if one million is too many:
如果一百万个过多,则使用较小的重复次数值:
count = 1000
print t.timeit(count) / count
Because timeit defaults to running it one million times. 因为timeit默认运行它一百万次。 The point is to do micro-benchmarks, and the only way to get accurate timings of short events is to repeat them many times.
重点是做微观基准测试,获得短期事件准确时间的唯一方法是重复多次。
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