On Mon, 22 Apr 2013 15:15:19 +0100, Blind Anagram wrote:
> But when using a sub-sequence, I do suffer a significant reduction in
> speed for a count when compared with count on the full list. When the
> list is small enough not to cause memory allocation issues this is about
> 30% on 100,000,000 items. But when the list is 1,000,000,000 items, OS
> memory allocation becomes an issue and the cost on my system rises to
> over 600%.
Buy more memory :-)
> I agree that this is not a big issue but it seems to me a high price to
> pay for the lack of a sieve.count(value, limit), which I feel is a
> useful function (given that memoryview operations are not available for
> lists).
There is no need to complicate the count method for such a specialised
use-case. A more general solution would be to provide list views.
Another solution might be to use arrays rather than lists. Since your
sieve list is homogeneous, you could possibly use an array of 1 or 0
bytes rather than a list of True or False bools. That would reduce the
memory overhead by a factor of four, and similarly reduce the overhead of
any copying:
py> from array import array
py> from sys import getsizeof
py> L = [True, False, False, True]*1000
py> A = array('b', L)
py> getsizeof(L)
16032
py> getsizeof(A)
4032
--
Steven
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