Sybren Stuvel wrote:
> Steven D'Aprano enlightened us with:
>
>>he says that every time you try to append to a list that is already
>>full, Python doubles the size of the list. This wastes no more than
<snip>
> If, on the other hand, you double the memory every time you run out,
> you have to copy much less data, and in the end it turns out you need
> roughly N steps to add N items to the list. That's a lot better, isn't
> it?
This begs a different question along the same lines.
If I have a generator or other iterable producing a vast number of
items, and use it like this:
s = [k for k in iterable]
if I know beforehand how many items iterable would possibly yield, would
a construct like this be faster and "use" less memory?
s = [0] * len(iterable)
for i in xrange(len(iterable)):
s[i] = iterable.next()
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Lasse Vågsæther Karlsen
http://usinglvkblog.blogspot.com/
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