how to measure running time of algorithms in python

The module timeit is useful for this and is included in the standard Python distribution.

Example:

import timeit
timeit.Timer('for i in xrange(10): oct(i)').timeit()

For small algorithms you can use the module timeit
from python documentation:

def test():
    "Stupid test function"
    L = []
    for i in range(100):
        L.append(i)

if __name__=='__main__':
    from timeit import Timer
    t = Timer("test()", "from __main__ import test")
    print t.timeit()

Less accurately but still valid you can use module time like this:

from time import time
t0 = time()
call_mifuntion_vers_1()
t1 = time()
call_mifunction_vers_2()
t2 = time()

print 'function vers1 takes %f' %(t1-t0)
print 'function vers2 takes %f' %(t2-t1)

The programming language doesn’t matter; measuring the runtime complexity of an algorithm works the same way regardless of the language. Analysis of Algorithms by Stanford on Google Code University is a very good resource for teaching yourself how to analyze the runtime complexity of algorithms and code.

If all you want to do is measure the elapsed time that a function or section of code took to run in Python, then you can use the timeit or time modules, depending on how long the code needs to run.

Using a decorator for measuring execution time for functions can be handy. There is an example at http://www.zopyx.com/blog/a-python-decorator-for-measuring-the-execution-time-of-methods.

Below I’ve shamelessly pasted the code from the site mentioned above so that the example exists at SO in case the site is wiped off the net.

import time                                                

def timeit(method):

    def timed(*args, **kw):
        ts = time.time()
        result = method(*args, **kw)
        te = time.time()

        print '%r (%r, %r) %2.2f sec' % 
              (method.__name__, args, kw, te-ts)
        return result

    return timed

class Foo(object):

    @timeit
    def foo(self, a=2, b=3):
        time.sleep(0.2)

@timeit
def f1():
    time.sleep(1)
    print 'f1'

@timeit
def f2(a):
    time.sleep(2)
    print 'f2',a

@timeit
def f3(a, *args, **kw):
    time.sleep(0.3)
    print 'f3', args, kw

f1()
f2(42)
f3(42, 43, foo=2)
Foo().foo()

// John