thanks to everyone for the excellent suggestions. a few follow up q's:
1] is Try-Except really slower? my dict actually has two layers, so
my_dict[aKey][bKeys]. the aKeys are very small (less than 100) where
as the bKeys are the ones that are in the millions. so in that case,
doing a Try-Except o
hello
i have an optimization questions about python. i am iterating through
a file and counting the number of repeated elements. the file has on
the order
of tens of millions elements...
i create a dictionary that maps elements of the file that i want to
count
to their number of occurs. so i iter
cy so much...
thanks.
On Jan 13, 12:24 am, brent wrote:
> On Jan 12, 8:55 pm, Per Freem wrote:
>
>
>
> > On Jan 12, 10:58 pm, Steven D'Aprano
>
> > wrote:
> > > On Mon, 12 Jan 2009 14:49:43 -0800, Per Freem wrote:
> > > > thanks for your repli
i forgot to add, my naive_find is:
def naive_find(intervals, start, stop):
results = []
for interval in intervals:
if interval.start >= start and interval.stop <= stop:
results.append(interval)
return results
On Jan 12, 11:55 pm, Per Freem wrote:
> On Jan 12, 10:58 p
On Jan 12, 10:58 pm, Steven D'Aprano
wrote:
> On Mon, 12 Jan 2009 14:49:43 -0800, Per Freem wrote:
> > thanks for your replies -- a few clarifications and questions. the
> > is_within operation is containment, i.e. (a,b) is within (c,d) iff a
> >>= c and b <= d
thanks for your replies -- a few clarifications and questions. the
is_within operation is containment, i.e. (a,b) is within (c,d) iff a
>= c and b <= d. Note that I am not looking for intervals that
overlap... this is why interval trees seem to me to not be relevant,
as the overlapping interval pro
hello,
suppose I have two lists of intervals, one significantly larger than
the other.
For example listA = [(10, 30), (5, 25), (100, 200), ...] might contain
thousands
of elements while listB (of the same form) might contain hundreds of
thousands
or millions of elements.
I want to count how many i
