在Python中使用哪个更好?Time.clock()还是time.time()?哪一种更准确?

例如:

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

vs.

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

当前回答

在Linux上,time()比clock()具有更好的精度。Clock()的精度小于10毫秒。而time()提供完美的精度。 我的测试用的是CentOS 6.4和python 2.6

using time():

1 requests, response time: 14.1749382019 ms
2 requests, response time: 8.01301002502 ms
3 requests, response time: 8.01491737366 ms
4 requests, response time: 8.41021537781 ms
5 requests, response time: 8.38804244995 ms

使用时钟():

1 requests, response time: 10.0 ms
2 requests, response time: 0.0 ms 
3 requests, response time: 0.0 ms
4 requests, response time: 10.0 ms
5 requests, response time: 0.0 ms 
6 requests, response time: 0.0 ms
7 requests, response time: 0.0 ms 
8 requests, response time: 0.0 ms

其他回答

据我所知,time.clock()具有系统所允许的最大精度。

从3.3开始,time.clock()已弃用,建议使用time.process_time()或time.perf_counter()。

在2.7之前,根据time模块docs:

time.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.

此外,还有timeit模块用于对代码段进行基准测试。

在Linux上,time()比clock()具有更好的精度。Clock()的精度小于10毫秒。而time()提供完美的精度。 我的测试用的是CentOS 6.4和python 2.6

using time():

1 requests, response time: 14.1749382019 ms
2 requests, response time: 8.01301002502 ms
3 requests, response time: 8.01491737366 ms
4 requests, response time: 8.41021537781 ms
5 requests, response time: 8.38804244995 ms

使用时钟():

1 requests, response time: 10.0 ms
2 requests, response time: 0.0 ms 
3 requests, response time: 0.0 ms
4 requests, response time: 10.0 ms
5 requests, response time: 0.0 ms 
6 requests, response time: 0.0 ms
7 requests, response time: 0.0 ms 
8 requests, response time: 0.0 ms

简单回答:在Python中使用time.clock()进行计时。

在*nix系统上,clock()返回处理器时间为浮点数,以秒表示。在Windows上,它以浮点数的形式返回自第一次调用此函数以来所经过的秒数。

time()返回自纪元以来的秒数,以UTC为单位,作为浮点数。不能保证您将获得比1秒更好的精度(即使time()返回一个浮点数)。还要注意,如果在两次调用该函数之间设置了系统时钟,那么第二次函数调用将返回一个较低的值。

简单的答案是:大多数时候time.clock()会更好。 然而,如果你正在为某些硬件计时(例如你在GPU中放入的某些算法),那么time.clock()将摆脱这个时间,而time.time()是唯一剩下的解决方案。

注意:无论使用何种方法,计时将取决于您无法控制的因素(进程何时切换,频率如何,……),这对于time.time()来说更糟糕,但对于time.clock()也存在,因此您永远不应该只运行一个计时测试,而是始终运行一系列测试并查看时间的均值/方差。