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Since the geometry you’re measuring distance to is on UserProfile
, it makes sense to query for UserProfile
objects and then handle each Item
object they own. (The distance is the same for all items owned by a profile.)
For example:
all_profiles = UserProfile.objects.all()
for profile in all_profiles.distance(p).order_by('distance'):
for item in profile.item_set.all():
process(item, profile.distance)
You may be able to make this more efficient with prefetch_related:
all_profiles = UserProfile.objects.all()
all_profiles = all_profiles.prefetch_related('item_set') # we'll need these
for profile in all_profiles.distance(p).order_by('distance'):
for item in profile.item_set.all(): # items already prefetched
process(item, profile.distance)
If it’s important for some reason to query directly for Item
objects, try using extra:
items = Item.objects.all()
items = items.select_related('owner')
distance_select = "st_distance_sphere(core_userprofile.location, ST_GeomFromEWKT('%s'))" % p.wkt
items = items.extra({'distance': distance_select})
items = items.order_by('distance')
Raw queries are another option, which let you get model objects from a raw SQL query:
items = Item.objects.raw("SELECT core_item.* FROM core_item JOIN core_userprofile ...")
Source:stackexchange.com