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 -- http://mail.python.org/mailman/listinfo/python-list
