Django filter queryset __in for *every* item in list

Solution 1:

Summary:

One option is, as suggested by jpic and sgallen in the comments, to add .filter() for each category. Each additional filter adds more joins, which should not be a problem for small set of categories.

There is the aggregation approach. This query would be shorter and perhaps quicker for a large set of categories.

You also have the option of using custom queries.

Some examples

Test setup:

class Photo(models.Model):
    tags = models.ManyToManyField('Tag')

class Tag(models.Model):
    name = models.CharField(max_length=50)

    def __unicode__(self):
        return self.name

In [2]: t1 = Tag.objects.create(name='holiday')
In [3]: t2 = Tag.objects.create(name='summer')
In [4]: p = Photo.objects.create()
In [5]: p.tags.add(t1)
In [6]: p.tags.add(t2)
In [7]: p.tags.all()
Out[7]: [<Tag: holiday>, <Tag: summer>]

Using chained filters approach:

In [8]: Photo.objects.filter(tags=t1).filter(tags=t2)
Out[8]: [<Photo: Photo object>]

Resulting query:

In [17]: print Photo.objects.filter(tags=t1).filter(tags=t2).query
SELECT "test_photo"."id"
FROM "test_photo"
INNER JOIN "test_photo_tags" ON ("test_photo"."id" = "test_photo_tags"."photo_id")
INNER JOIN "test_photo_tags" T4 ON ("test_photo"."id" = T4."photo_id")
WHERE ("test_photo_tags"."tag_id" = 3  AND T4."tag_id" = 4 )

Note that each filter adds more JOINS to the query.

Using annotation approach:

In [29]: from django.db.models import Count
In [30]: Photo.objects.filter(tags__in=[t1, t2]).annotate(num_tags=Count('tags')).filter(num_tags=2)
Out[30]: [<Photo: Photo object>]

Resulting query:

In [32]: print Photo.objects.filter(tags__in=[t1, t2]).annotate(num_tags=Count('tags')).filter(num_tags=2).query
SELECT "test_photo"."id", COUNT("test_photo_tags"."tag_id") AS "num_tags"
FROM "test_photo"
LEFT OUTER JOIN "test_photo_tags" ON ("test_photo"."id" = "test_photo_tags"."photo_id")
WHERE ("test_photo_tags"."tag_id" IN (3, 4))
GROUP BY "test_photo"."id", "test_photo"."id"
HAVING COUNT("test_photo_tags"."tag_id") = 2

ANDed Q objects would not work:

In [9]: from django.db.models import Q
In [10]: Photo.objects.filter(Q(tags__name='holiday') & Q(tags__name='summer'))
Out[10]: []
In [11]: from operator import and_
In [12]: Photo.objects.filter(reduce(and_, [Q(tags__name='holiday'), Q(tags__name='summer')]))
Out[12]: []

Resulting query:

In [25]: print Photo.objects.filter(Q(tags__name='holiday') & Q(tags__name='summer')).query
SELECT "test_photo"."id"
FROM "test_photo"
INNER JOIN "test_photo_tags" ON ("test_photo"."id" = "test_photo_tags"."photo_id")
INNER JOIN "test_tag" ON ("test_photo_tags"."tag_id" = "test_tag"."id")
WHERE ("test_tag"."name" = holiday  AND "test_tag"."name" = summer )

Solution 2:

Another approach that works, although PostgreSQL only, is using django.contrib.postgres.fields.ArrayField:

Example copied from docs:

>>> Post.objects.create(name='First post', tags=['thoughts', 'django'])
>>> Post.objects.create(name='Second post', tags=['thoughts'])
>>> Post.objects.create(name='Third post', tags=['tutorial', 'django'])

>>> Post.objects.filter(tags__contains=['thoughts'])
<QuerySet [<Post: First post>, <Post: Second post>]>

>>> Post.objects.filter(tags__contains=['django'])
<QuerySet [<Post: First post>, <Post: Third post>]>

>>> Post.objects.filter(tags__contains=['django', 'thoughts'])
<QuerySet [<Post: First post>]>

ArrayField has some more powerful features such as overlap and index transforms.

Solution 3:

This also can be done by dynamic query generation using Django ORM and some Python magic :)

from operator import and_
from django.db.models import Q

categories = ['holiday', 'summer']
res = Photo.filter(reduce(and_, [Q(tags__name=c) for c in categories]))

The idea is to generate appropriate Q objects for each category and then combine them using AND operator into one QuerySet. E.g. for your example it'd be equal to

res = Photo.filter(Q(tags__name='holiday') & Q(tags__name='summer'))