On Sat, 03 May 2008 17:43:57 -0700, George Sakkis wrote: > On May 3, 7:12 pm, Ivan Illarionov <[EMAIL PROTECTED]> wrote: >> On Sun, 04 May 2008 00:31:01 +0200, Thomas Dybdahl Ahle wrote: >> > On Sat, 2008-05-03 at 21:37 +0000, Ivan Illarionov wrote: >> >> On Sat, 03 May 2008 20:44:19 +0200, Szabolcs Horvát wrote: >> >> >> > Arnaud Delobelle wrote: >> >> >> >> sum() works for any sequence of objects with an __add__ method, >> >> >> not just floats! Your algorithm is specific to floats. >> >> >> > This occurred to me also, but then I tried >> >> >> > sum(['abc', 'efg'], '') >> >> >> Interesting, I always thought that sum is like shortcut of >> >> reduce(operator.add, ...), but I was mistaken. >> >> >> reduce() is more forgiving: >> >> reduce(operator.add, ['abc', 'efg'], '' ) # it works 'abcefg' >> > Hm, it works for lists: >> > sum(([1], [2]), []) >> > [1, 2] > > So it's not reduce() that is more forgiving, it's sum() that makes an > exception for strings only. > > >> > However I find the seccond argument hack ugly. Does the sum way have >> > any performance advantages over the reduce way? >> >> Yes, sum() is faster: >> >> $ python -m timeit "" "sum([[1], [2], [3, 4]], [])" 100000 loops, best >> of 3: 6.16 usec per loop >> >> $ python -m timeit "import operator" \ "reduce(operator.add, [[1], [2], >> [3, 4]])" 100000 loops, best of 3: 11.9 usec per loop > > Not really; you measure the import and the attribute access time in the > second case. sum() is 2x faster for adding numbers only: > > # Adding integers > python -mtimeit --setup="x=[1]*100" "sum(x)" 100000 loops, best of 3: > 4.87 usec per loop python -mtimeit --setup="from operator import add; > x=[1]*100" "reduce(add,x)" > 100000 loops, best of 3: 10.1 usec per loop > > # Adding floats > python -mtimeit --setup="x=[1.0]*100" "sum(x)" 100000 loops, best of 3: > 5.14 usec per loop python -mtimeit --setup="from operator import add; > x=[1.0]*100" "reduce(add,x)" > 100000 loops, best of 3: 10.1 usec per loop > > # Adding tuples > python -mtimeit --setup="x=[(1,)]*100" "sum(x,())" 10000 loops, best of > 3: 61.6 usec per loop python -mtimeit --setup="from operator import add; > x=[(1,)]*100" "reduce(add,x,())" > 10000 loops, best of 3: 66.3 usec per loop > > # Adding lists > python -mtimeit --setup="x=[[1]]*100" "sum(x,[])" 10000 loops, best of > 3: 79.9 usec per loop python -mtimeit --setup="from operator import add; > x=[[1]]*100" "reduce(add,x,[])" > 10000 loops, best of 3: 84.3 usec per loop > > George
Thanks for correction. Forget about --setup. -- Ivan -- http://mail.python.org/mailman/listinfo/python-list
