Preface
This is a redux of Python Performance Part 1, where the fastest method was using the reduce builtin function in Python2.5. December 3rd, Python 3000 final was released so I have downloaded it and gone over some of these scripts again. In Python 3000 the reduce function is no longer a builtin, and has moved to the module functools. When doing some general comparisons between Python2.5 and Python 3000, the later seemed to always run slightly slower. This is due to the new IO system and unicode indentifiers, as I was told in #python channel by Crys_. It was also recommended that I also compare my tests with List Comprehension, of which is new to me.
List Comprehension
from oids import oids as a c = 3 res = [a[x:x+c] for x in [c*x for x in range(int(round(len(a)/c)))]]
Python 3k Times
real 0m0.218s user 0m0.180s sys 0m0.016s real 0m0.262s user 0m0.204s sys 0m0.032s real 0m0.287s user 0m0.244s sys 0m0.008s
Python 2.5 Times
real 0m0.244s user 0m0.220s sys 0m0.016s real 0m0.229s user 0m0.208s sys 0m0.020s real 0m0.251s user 0m0.236s sys 0m0.020s
This makes it the fastest method, beating the previous fastest time of 0.34s. Even better, there is little difference between Python2.5 and Python3000 here.