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Model index reference

Index classes ease creating database indexes. They can be added using the Meta.indexes option. This document explains the API references of Index which includes the index options.

Referencing built-in indexes

Indexes are defined in django.db.models.indexes, but for convenience they’re imported into django.db.models. The standard convention is to use from django.db import models and refer to the indexes as models.<IndexClass>.

Index options

class Index(fields=(), name=None, db_tablespace=None, opclasses=(), condition=None, include=None)

Creates an index (B-Tree) in the database.



A list or tuple of the name of the fields on which the index is desired.

By default, indexes are created with an ascending order for each column. To define an index with a descending order for a column, add a hyphen before the field’s name.

For example Index(fields=['headline', '-pub_date']) would create SQL with (headline, pub_date DESC). Index ordering isn’t supported on MySQL. In that case, a descending index is created as a normal index.



The name of the index. If name isn’t provided Django will auto-generate a name. For compatibility with different databases, index names cannot be longer than 30 characters and shouldn’t start with a number (0-9) or underscore (_).

Partial indexes in abstract base classes

You must always specify a unique name for an index. As such, you cannot normally specify a partial index on an abstract base class, since the Meta.indexes option is inherited by subclasses, with exactly the same values for the attributes (including name) each time. To work around name collisions, part of the name may contain '%(app_label)s' and '%(class)s', which are replaced, respectively, by the lowercased app label and class name of the concrete model. For example Index(fields=['title'], name='%(app_label)s_%(class)s_title_index').



The name of the database tablespace to use for this index. For single field indexes, if db_tablespace isn’t provided, the index is created in the db_tablespace of the field.

If Field.db_tablespace isn’t specified (or if the index uses multiple fields), the index is created in tablespace specified in the db_tablespace option inside the model’s class Meta. If neither of those tablespaces are set, the index is created in the same tablespace as the table.

See also

For a list of PostgreSQL-specific indexes, see django.contrib.postgres.indexes.



The names of the PostgreSQL operator classes to use for this index. If you require a custom operator class, you must provide one for each field in the index.

For example, GinIndex(name='json_index', fields=['jsonfield'], opclasses=['jsonb_path_ops']) creates a gin index on jsonfield using jsonb_path_ops.

opclasses are ignored for databases besides PostgreSQL.

Index.name is required when using opclasses.



If the table is very large and your queries mostly target a subset of rows, it may be useful to restrict an index to that subset. Specify a condition as a Q. For example, condition=Q(pages__gt=400) indexes records with more than 400 pages.

Index.name is required when using condition.

Restrictions on PostgreSQL

PostgreSQL requires functions referenced in the condition to be marked as IMMUTABLE. Django doesn’t validate this but PostgreSQL will error. This means that functions such as Date functions and Concat aren’t accepted. If you store dates in DateTimeField, comparison to datetime objects may require the tzinfo argument to be provided because otherwise the comparison could result in a mutable function due to the casting Django does for lookups.

Restrictions on SQLite

SQLite imposes restrictions on how a partial index can be constructed.


Oracle does not support partial indexes. Instead, partial indexes can be emulated using functional indexes. Use a migration to add the index using RunSQL.

MySQL and MariaDB

The condition argument is ignored with MySQL and MariaDB as neither supports conditional indexes.


New in Django Development version.

A list or tuple of the names of the fields to be included in the covering index as non-key columns. This allows index-only scans to be used for queries that select only included fields (include) and filter only by indexed fields (fields).

For example:

Index(name='covering_index', fields=['headline'], include=['pub_date'])

will allow filtering on headline, also selecting pub_date, while fetching data only from the index.

Using include will produce a smaller index than using a multiple column index but with the drawback that non-key columns can not be used for sorting or filtering.

include is ignored for databases besides PostgreSQL.

Index.name is required when using include.

See the PostgreSQL documentation for more details about covering indexes.

Restrictions on PostgreSQL

PostgreSQL 11+ only supports covering B-Tree indexes, and PostgreSQL 12+ also supports covering GiST indexes.

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