My experience with Django debug toolbar is that it makes things
slow all by itself.

I have done a couple of apps that use the equivalent query, using PostgreSQL,
without noticing a performance issue, with everything running on a Linux server.

1. Have you tried timing the query by hand?  That is, run the manage.py shell,
import your model, and type a sample version of the query, wrapped in a list()
operation to force the query to evaluate right away.  If it's slow,
then you problem
is at least mostly in your DB/query choice.

2. Is the machine in question tight on memory?  That could make things slower
that it would be on a production instance.

3.  You might look at the "range" field lookup instead of pairs of
gte, lte.  I doubt
that it makes a performance difference, and I don't know if SQLite supports
BETWEEN, but it's easy to try.

4. You show x and y as integers, but if that was just by way of example, and
they are really some complex (non-scalar) data type, the comparisons may not
be cheap on the database.

Bill

On Mon, Nov 1, 2010 at 8:13 AM, Javier Guerra Giraldez
<jav...@guerrag.com> wrote:
> On Mon, Nov 1, 2010 at 5:55 AM, Cal Leeming [Simplicity Media Ltd]
> <cal.leem...@simplicitymedialtd.co.uk> wrote:
>> 9 out of 10 times, the bottleneck is usually the database
>
> true, but 8.7 of those 9 are about how the database is used, and not
> about the engine choice.  simply changing SQLite won't improve
> significantly the one-user case.
>
> the trick is: 1) get as few db queries as possible for each page.  2)
> use appropriate indices for those queries
>
> but first of all, you have to identify if it is really the DB where
> you're spending time.  the easiest way to be sure is to install
> django_debug_toolbar app, it's great to tell you exactly what's going
> on with the time and the DB accesses.
>
> --
> Javier
>
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