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Posts Tagged ‘timeit’

Python:time.clock() vs. time.time()

Posted by Ross Wan 于 2008/09/19

有时候,我们需要知道程序或者当中的一段代码的执行速度,于是就会加入一段计时的代码,如下:

start = time.clock()
... do something
elapsed = (time.clock() - start)

又或者

start = time.time()
... do something
elapsed = (time.time() - start)

那究竟 time.clock() 跟 time.time(),谁比较精确呢?带着疑问,查了 Python 的 time 模块文档,当中 clock() 方法有这样的解释:

clock()

On
Unix, return the current processor time as a floating point number
expressed in seconds. The precision, and in fact the very definition of
the meaning of “processor time”, depends on that of the C function of
the same name, but in any case, this is the function to use for
benchmarking Python or timing algorithms.

On Windows, this
function returns wall-clock seconds elapsed since the first call to
this function, as a floating point number, based on the Win32 function
QueryPerformanceCounter(). The resolution is typically better than one
microsecond.

可见,time.clock() 返回的是处理器时间,而因为 Unix 中 jiffy 的缘故,所以精度不会太高。

总结

究竟是使用 time.clock() 精度高,还是使用 time.time() 精度更高,要视乎所在的平台来决定。总概来讲,在 Unix 系统中,建议使用 time.time(),在 Windows 系统中,建议使用 time.clock()。

这个结论也可以在 Python 的 timtit 模块中(用于简单测量程序代码执行时间的内建模块)得到论证:

if sys.platform == "win32":
# On Windows, the best timer is time.clock()
default_timer = time.clock
else:
# On most other platforms the best timer is time.time()
default_timer = time.time

使用 timeit 代替 time,这样就可以实现跨平台的精度性:

start = timeit.default_timer()
... do something
elapsed = (timeit.default_timer() - start)

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