Index classes ease creating database indexes. They can be added using the\nMeta.indexes option. This document\nexplains the API references of Index which includes the index\noptions.
Index optionsLink to this heading#Creates an index (B-Tree) in the database.
\nexpressionsLink to this heading#Positional argument *expressions allows creating functional indexes on\nexpressions and database functions.
For example:
\nIndex(Lower("title").desc(), "pub_date", name="lower_title_date_idx")\ncreates an index on the lowercased value of the title field in descending\norder and the pub_date field in the default ascending order.
Another example:
\nIndex(F("height") * F("weight"), Round("weight"), name="calc_idx")\ncreates an index on the result of multiplying fields height and weight\nand the weight rounded to the nearest integer.
Index.name is required when using *expressions.
fieldsLink to this heading#A list or tuple of the name of the fields on which the index is desired.
\nBy default, indexes are created with an ascending order for each column. To\ndefine an index with a descending order for a column, add a hyphen before the\nfield’s name.
\nFor example Index(fields=['headline', '-pub_date']) would create SQL with\n(headline, pub_date DESC).
nameLink to this heading#The name of the index. If name isn’t provided Django will auto-generate a\nname. For compatibility with different databases, index names cannot be longer\nthan 30 characters and shouldn’t start with a number (0-9) or underscore (_).
db_tablespaceLink to this heading#The name of the database tablespace to use for\nthis index. For single field indexes, if db_tablespace isn’t provided, the\nindex is created in the db_tablespace of the field.
If Field.db_tablespace isn’t specified (or if the index uses multiple\nfields), the index is created in tablespace specified in the\ndb_tablespace option inside the model’s\nclass Meta. If neither of those tablespaces are set, the index is created\nin the same tablespace as the table.
opclassesLink to this heading#The names of the PostgreSQL operator classes to use for\nthis index. If you require a custom operator class, you must provide one for\neach field in the index.
\nFor example, GinIndex(name='json_index', fields=['jsonfield'],\nopclasses=['jsonb_path_ops']) creates a gin index on jsonfield using\njsonb_path_ops.
opclasses are ignored for databases besides PostgreSQL.
Index.name is required when using opclasses.
conditionLink to this heading#If the table is very large and your queries mostly target a subset of rows,\nit may be useful to restrict an index to that subset. Specify a condition as a\nQ. For example, condition=Q(pages__gt=400)\nindexes records with more than 400 pages.
Index.name is required when using condition.
includeLink to this heading#A list or tuple of the names of the fields to be included in the covering index\nas non-key columns. This allows index-only scans to be used for queries that\nselect only included fields (include) and filter only by indexed\nfields (fields).
For example:
\nIndex(name="covering_index", fields=["headline"], include=["pub_date"])\nwill allow filtering on headline, also selecting pub_date, while\nfetching data only from the index.
Using include will produce a smaller index than using a multiple column\nindex but with the drawback that non-key columns can not be used for sorting or\nfiltering.
include is ignored for databases besides PostgreSQL.
Index.name is required when using include.
See the PostgreSQL documentation for more details about covering indexes.
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