Fastest way to apply a function to an iterable

[Shashank Singh]

On Thu, May 27, 2010 at 1:56 AM, Stefan Behnel <stefan_ml at behnel.de> wrote:

> If all items have the exact same type, you can get away with an unbound
> method:
>
>    class MyType(object):
>        ...
>        def safe(self):
>            ...
>
>    itemlist = [ MyType() for i in range(20) ]
>
>    # this is what you want:
>

   from itertools import imap
>    for _ in imap(MyType.save, itemlist): pass
>

Thanks Stefan,

I probably didn't state the problem properly. I was assuming the
availability of  a static method that could be passed on to map based
solution (or imap for that matter).

The question was, if one wants to apply a function on each member of list
and discard the return value, is it possible to do it more efficiently than
having a for loop in python and applying the function of each of the
members?

Take this run:

from itertools import imap
from timeit import Timer


def save(x): 2 * x

from itertools import imap
from timeit import Timer


def save(x): 2 * x

def f1(): map(save, range(1000)) #simple map

def f2():
  for _ in imap(save, range(1000)): pass #imap

def f3():
  for x in range(1000):save(x) #simple iteration

t1 = Timer("f1()", "from __main__ import f1")
print "f1", t1.timeit(number=1000)

t2 = Timer("f2()", "from __main__ import f2")
print "f2", t2.timeit(number=1000)

t3 = Timer("f3()", "from __main__ import f3")
print "f3", t3.timeit(number=1000)

The output for one run was:

f1 0.393015034034
f2 0.476230638252
f3 0.376324923978

=> simple for loop performs better than map/imap. Another problem with
map/imap is that the memory cost is dependent on the length of the list
(because of the intermediate mapped list stored) which is not the case for
simple for loop.

I hope I have explained it better this time.

-- 
Regards
Shashank Singh
Senior Undergraduate, Department of Computer Science and Engineering
Indian Institute of Technology Bombay
shashank.sunny.singh at gmail.com
http://www.cse.iitb.ac.in/~shashanksingh
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