accurately measure time python function takes

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.

You could build a timing context (see PEP 343) to measure blocks of code pretty easily.

from __future__ import with_statement
import time

class Timer(object):
    def __enter__(self):
        self.__start = time.time()

    def __exit__(self, type, value, traceback):
        # Error handling here
        self.__finish = time.time()

    def duration_in_seconds(self):
        return self.__finish - self.__start

timer = Timer()

with timer:
    # Whatever you want to measure goes here
    time.sleep(2)

print timer.duration_in_seconds()    

I was annoyed too by the awful interface of timeit so i made a library for this, check it out its trivial to use

from pythonbenchmark import compare, measure
import time

a,b,c,d,e = 10,10,10,10,10
something = [a,b,c,d,e]

def myFunction(something):
    time.sleep(0.4)

def myOptimizedFunction(something):
    time.sleep(0.2)

# comparing test
compare(myFunction, myOptimizedFunction, 10, input)
# without input
compare(myFunction, myOptimizedFunction, 100)

https://github.com/Karlheinzniebuhr/pythonbenchmark

The timeit module looks like it's designed for doing performance testing of algorithms, rather than as simple monitoring of an application. Your best option is probably to use the time module, call time.time() at the beginning and end of the segment you're interested in, and subtract the two numbers. Be aware that the number you get may have many more decimal places than the actual resolution of the system timer.