[Python-Dev] iterzip()

Tim Peters tim.one@comcast.net
Mon, 29 Apr 2002 15:35:37 -0400

> This suggests that zip() can be sped up considerably by using a hint
> for the input sequence sizes.  If they all respond properly to
> PySequence_Length(), zip can preallocate the result list to the
> correct size.  It shouldn't believe the numbers fully, but using them
> as a hint for initial allocation makes a lot of sense, and should
> greatly reduce the inefficiency.

I'm afraid I misanalyzed the cause.  Giving zip a good guess about the
result size and using PyList_SET_ITEM up until then leads (as expected) to
no list copying in the test case I posted, but only dropped the runtime from
7.87 to 7.31 seconds (which makes sense looking at the numbers more closely:
it doesn't take *that* long to copy a few dozen mebabytes of memory unless
you're doing it by hand <wink>).

Check this out:

from time import clock as now

n = 1000000

def juststore(x):
    for i in x: x[i] = 0

def justtups(x):
    for i in x: 0,

def storetups(x):
    for i in x: x[i] = 0,

def run(func):
    x = range(n)
    start = now()
    finish = now()
    print "%10s %6.2f" % (func.__name__, finish - start)


I get:

 juststore   0.93
  justtups   0.58
 storetups   7.61

list.append is out of the picture here.  Creating a million tuples goes fast
so long as they're recycled, and storing a million things goes fast, but
storing a million distinct tuples takes very much longer.  It's a Mystery to
me so far.  How does it act on Linux?