Here’s another cautionary performance tale, wherein I thought I was clever but was not.

A table (“Vital”) holds widget information. Another table (“Furball”) holds other information, with an M:M relationship to Vital.

We want to do inferential computations on filtered Furball rows. So we generate a pk list from a Vital QuerySet, and call this function:

def _get_top(vitals):
    from django.db.models import Count

    TOP_NUMBER = 5

    vitalids = [x.id for x in vitals]
    top_balls = Furball.objects.filter(vital__id__in=vitalids)\
                            .annotate(count=Count('id'))\
                            .order_by('-count')[:TOP_NUMBER]
    top_list = [(x.name, x.count)for x in top_balls]

    return top_list

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At work, we’ve contracted with PostgreSQL Experts to help us improve our Postgres performance. After analyzing our system, one of their consultants, Christophe Pettus, found glaring problems in how some of my code accessed our database.

I consider myself well-informed about good database access practices in Django, and in general. I might not exactly hit the bull’s-eye, but I’m sufficiently savvy to avoid making a “WTF” mistake, right?

Nope!
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One interesting tidbit from last night’s PostgreSQL BOF session was the news that Postgres’ site would be migrated to Django within the next year. This came from Josh Berkus.

Postgres’ site now is apparently generated from a bespoke PHP script mishmash. Josh said that tasks like creating new forms was much harder than they ought to be. So…they’re moving it to Django.