More likely the cost of the two dynamic lookups of builtin functions is your cost. On Fri, Sep 4, 2009 at 12:56 PM, Gerald Britton<gerald.britton@gmail.com> wrote:
Interesting that your return(next()) example runs about 60% slower than the "for x in l: return x" example. Must be the function call overhead.
On Fri, Sep 4, 2009 at 3:36 PM, Stefan Behnel<stefan_ml@behnel.de> wrote:
Guido van Rossum wrote:
On Fri, Sep 4, 2009 at 2:35 AM, Stefan Behnel wrote:
I just had a discussion with a co-worker, and we noticed that there are use cases where you just want the only element in a data structure, or just any of the elements in a data structure because you know that they all contain the same information (with respect to what you are looking for, at least).
If you want all items, you can iterate, but if you just want any item or the only item, it's inefficient (and not very explicit code) to create an iterator and take the element out.
I assure you it's not slow.
Not in absolute numbers, but certainly slower than necessary:
$ python2.6 -m timeit -s 'l=[1]' 'l[0]' 10000000 loops, best of 3: 0.0977 usec per loop
$ python2.6 -m timeit -s 'l=[1]' 'next(iter(l))' 1000000 loops, best of 3: 0.523 usec per loop
next(iter(x)) is probably as good as it gets -- I don't think we need another way to say that in fewer words.
I'm fine with such a decision, given that it's trivial to wrap this into your own function. That doesn't make it much faster:
$ python2.6 -m timeit -s 'l=[1]' -s 'def getany(l):' -s ' return l[0]' 'getany(l)' 1000000 loops, best of 3: 0.34 usec per loop
$ python2.6 -m timeit -s 'l=[1]' -s 'def getany(l):' \ -s ' for x in l:' \ -s ' return x' \ 'getany(l)' 1000000 loops, best of 3: 0.454 usec per loop
$ python2.6 -m timeit -s 'l=[1]' -s 'def getany(l):' \ -s ' return next(iter(l))' \ 'getany(l)' 1000000 loops, best of 3: 0.743 usec per loop
but, admittedly, that's still not slow in absolute numbers.
Stefan
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