slice notation as values?
apardon at forel.vub.ac.be
Mon Dec 12 11:03:49 CET 2005
Op 2005-12-11, Bengt Richter schreef <bokr at oz.net>:
> On 10 Dec 2005 12:07:12 -0800, "Devan L" <devlai at gmail.com> wrote:
>>Antoon Pardon wrote:
>>> On 2005-12-10, Duncan Booth <duncan.booth at invalid.invalid> wrote:
>>> >> I also think that other functions could benefit. For instance suppose
>>> >> you want to iterate over every second element in a list. Sure you
>>> >> can use an extended slice or use some kind of while. But why not
>>> >> extend enumerate to include an optional slice parameter, so you could
>>> >> do it as follows:
>>> >> for el in enumerate(lst,::2)
>>> > 'Why not'? Because it makes for a more complicated interface for something
>>> > you can already do quite easily.
>>> Do you think so? This IMO should provide (0,lst), (2,lst),
>>> (4,lst) ...
>>> I haven't found a way to do this easily. Except for something like:
>>> start = 0:
>>> while start < len(lst):
>>> yield start, lst[start]
>>> start += 2
>>> But if you accept this, then there was no need for enumerate in the
>>> first place. So eager to learn something new, how do you do this
>>> quite easily?
>>>>> lst = ['ham','eggs','bacon','spam','foo','bar','baz']
>>[(0, 'ham'), (2, 'bacon'), (4, 'foo'), (6, 'baz')]
>>No changes to the language necessary.
> Or, without creating the full list intermediately,
> >>> lst = ['ham','eggs','bacon','spam','foo','bar','baz']
> >>> import itertools
> >>> list(itertools.islice(enumerate(lst), 0, None, 2))
> [(0, 'ham'), (2, 'bacon'), (4, 'foo'), (6, 'baz')]
As far as I understand use of this idiom can turn an O(n)
algorithm into an O(n^2) algorithm.
Suppose I have a list with 10 000 elements and I want
the sum of the first 100, the sum of the second 100 ...
One way to do that would be:
for i in xrange(0,10000,100):
sum(itertools.islice(lst, i, i+100))
But itertools.islice would each time start from the begining
of the list and iterate over i elements before giving 100
elements to sum. Which would make this implementation O(n^2)
instead of O(n).
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