Matlab timeit equivalent in Python for scripts

Question

In Matlab there is

"timeit(F), which measures the typical time (in seconds) required to run the function specified by the function handle F that takes no input argument."

This method returns the median of (I think 13) runs of the function.

Having looked at the methods time and timeit in Python, I can't quite find anything that will let me call from an IPython console, time my script (not function) a number of times, and return either an average or median.

Is there an easy way to do this? or at least time 1 execution, whereby I can make my own loop and average? Thanks

epx · Accepted Answer · 2015-03-05 18:21:06Z

1

You may want to look at this link and consider the %timeit magic from IPython

link

Example:

Say you define a function you want to test:

def logtest1(N):
tr=0.
for i in xrange(N):
    T= 40. + 10.*random()
    tr = tr + -log(random())/T

from timeit import Timer, timeit, repeat
runningtime = repeat("logtest1(int(10e5))", setup="from __main__ import logtest1", repeat=5, number=1)
print (runningtime)

That will run my function logtest1(int(10e5)) 1 time and store the time in the list runningtime then it will repeat the same thing 5 times and store the results in the same list. You can then take the average of the median of that list.

edited Mar 5, 2015 at 18:21

answered Mar 5, 2015 at 18:11

epx

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3 Comments

mdj15 Over a year ago

Having looked at it, there is no specification about running scripts from this? Or would I be implementing this within the script?

epx Over a year ago

Yes, you should do from within the script. Or at least load the script into IPython, make it a function and run it like that. Another alternative would be chaining the Ipython magics %timeit %run test.py (you can customize the timeit magic options if needed)

mdj15 Over a year ago

I used %timeit -n10 %run test which runs for 10 loops and 3(default, but changed by adding -r after -n) times, and takes the best of the 3 runs of 10

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