accurately measure time python function takes

hoju picture hoju · Nov 6, 2009 · Viewed 33.5k times · Source

I need to measure the time certain parts of my program take (not for debugging but as a feature in the output). Accuracy is important because the total time will be a fraction of a second.

I was going to use the time module when I came across timeit, which claims to avoid a number of common traps for measuring execution times. Unfortunately it has an awful interface, taking a string as input which it then eval's.

So, do I need to use this module to measure time accurately, or will time suffice? And what are the pitfalls it refers to?

Thanks

Answer

Sean Vieira picture Sean Vieira · Nov 6, 2009

According to the Python documentation, it has to do with the accuracy of the time function in different operating systems:

The default timer function is platform dependent. On Windows, time.clock() has microsecond granularity but time.time()‘s granularity is 1/60th of a second; on Unix, time.clock() has 1/100th of a second granularity and time.time() is much more precise. On either platform, the default timer functions measure wall clock time, not the CPU time. This means that other processes running on the same computer may interfere with the timing ... On Unix, you can use time.clock() to measure CPU time.

To pull directly from timeit.py's code:

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

In addition, it deals directly with setting up the runtime code for you. If you use time you have to do it yourself. This, of course saves you time

Timeit's setup:

def inner(_it, _timer):
    #Your setup code
    %(setup)s
    _t0 = _timer()
    for _i in _it:
        #The code you want to time
        %(stmt)s
    _t1 = _timer()
    return _t1 - _t0

Python 3:

Since Python 3.3 you can use time.perf_counter() (system-wide timing) or time.process_time() (process-wide timing), just the way you used to use time.clock():

from time import process_time

t = process_time()
#do some stuff
elapsed_time = process_time() - t

The new function process_time will not include time elapsed during sleep.

Python 3.7+:

Since Python 3.7 you can also use process_time_ns() which is similar to process_time()but returns time in nanoseconds.