Erik Max Francis wrote: > Ron Adam wrote: > >> In this case sum and product fulfill 90% (estimate of course) of >> reduces use cases. It may actually be as high as 99% for all I know. >> Or it may be less. Anyone care to try and put a real measurement on it? > > Well, reduce covers 100% of them, and it's one function, and it's > already there.
And it's almost two times slower: $ python -m timeit -s "x = xrange(1000)" "sum(x)" 10000 loops, best of 3: 92.5 usec per loop $ python -m timeit -s "from operator import add; x = xrange(1000)" "reduce(add, x)" 10000 loops, best of 3: 157 usec per loop And that's only if I have the sense to import from operator: $ python -m timeit -s "x = xrange(1000); add = lambda x, y: x + y" "reduce(add, x)" 1000 loops, best of 3: 587 usec per loop Note that the simple for-loop beats the case where you define your own function because it doesn't have the repeated overhead of function calls (which are expensive in Python): $ python -m timeit -s "sum = 0; x = xrange(1000)" "for i in x: sum += i" 10000 loops, best of 3: 291 usec per loop What would really help here is if you could identify the cases where you think reduce is really a gain. A lot of them are actually not good practice in Python because of the function-call overhead. However, I'm willing to be convinced otherwise with a few good examples. STeVe -- http://mail.python.org/mailman/listinfo/python-list
