The original queryset._next_is_sticky() call never had the intended effect as
no further filtering was applied internally after the pk__in lookup making it
a noop.
In order to be coherent with how related filters are applied when retrieving
objects from a related manager the effects of what calling _next_is_sticky()
prior to applying annotations and filters to the queryset provided for
prefetching are emulated by allowing the reuse of all pre-existing JOINs.
Thanks David Glenck and Thiago Bellini Ribeiro for the detailed reports and
tests.
Backport of 2598b371a93e21d84b7a2a99b2329535c8c0c138 from main.
Regression from f51c1f59 when using select_related then prefetch_related
on the reverse side of an O2O:
Author.objects.select_related('bio').prefetch_related('bio__books')
Thanks Aymeric Augustin for the report and tests. Refs #17001.
GenericRelation now supports an optional related_query_name argument.
Setting related_query_name adds a relation from the related object back to
the content type for filtering, ordering and other query operations.
Thanks to Loic Bistuer for spotting a couple of important issues in
his review.
The original patch for custom prefetches didn't allow usage of custom
queryset for single valued relations (along ForeignKey or OneToOneKey).
Allowing these enables calling performance oriented queryset methods like
select_related or defer/only.
Thanks @akaariai and @timgraham for the reviews. Refs #17001.
This patch introduces the Prefetch object which allows customizing prefetch
operations.
This enables things like filtering prefetched relations, calling select_related
from a prefetched relation, or prefetching the same relation multiple times
with different querysets.
When a Prefetch instance specifies a to_attr argument, the result is stored
in a list rather than a QuerySet. This has the fortunate consequence of being
significantly faster. The preformance improvement is due to the fact that we
save the costly creation of a QuerySet instance.
Thanks @akaariai for the original patch and @bmispelon and @timgraham
for the reviews.
