# sqlite3 --- DB-API 2.0 interface for SQLite databases — How to create and use row factories

> ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ By default, !sqlite3 represents each row as a tuple.

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^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^

By default, !sqlite3 represents each row as a tuple. If a !tuple does not suit your needs, you can use the sqlite3.Row class or a custom ~Cursor.row_factory.

While !row_factory exists as an attribute both on the Cursor and the Connection, it is recommended to set Connection.row_factory, so all cursors created from the connection will use the same row factory.

!Row provides indexed and case-insensitive named access to columns, with minimal memory overhead and performance impact over a !tuple. To use !Row as a row factory, assign it to the !row_factory attribute

&gt;&gt;&gt; con = sqlite3.connect(":memory:") &gt;&gt;&gt; con.row_factory = sqlite3.Row

Queries now return !Row objects

&gt;&gt;&gt; res = con.execute("SELECT 'Earth' AS name, 6378 AS radius") &gt;&gt;&gt; row = res.fetchone() &gt;&gt;&gt; row.keys() ['name', 'radius'] &gt;&gt;&gt; row[0] # Access by index. 'Earth' &gt;&gt;&gt; row["name"] # Access by name. 'Earth' &gt;&gt;&gt; row["RADIUS"] # Column names are case-insensitive. 6378 &gt;&gt;&gt; con.close()

You can create a custom ~Cursor.row_factory that returns each row as a dict, with column names mapped to values

def dict_factory(cursor, row): fields = [column[0] for column in cursor.description] return {key: value for key, value in zip(fields, row)}

Using it, queries now return a !dict instead of a !tuple

&gt;&gt;&gt; con = sqlite3.connect(":memory:") &gt;&gt;&gt; con.row_factory = dict_factory &gt;&gt;&gt; for row in con.execute("SELECT 1 AS a, 2 AS b"): ... print(row) {'a': 1, 'b': 2} &gt;&gt;&gt; con.close()

The following row factory returns a named tuple

from collections import namedtuple

def namedtuple_factory(cursor, row): fields = [column[0] for column in cursor.description] cls = namedtuple("Row", fields) return cls._make(row)

!namedtuple_factory can be used as follows

&gt;&gt;&gt; con = sqlite3.connect(":memory:") &gt;&gt;&gt; con.row_factory = namedtuple_factory &gt;&gt;&gt; cur = con.execute("SELECT 1 AS a, 2 AS b") &gt;&gt;&gt; row = cur.fetchone() &gt;&gt;&gt; row Row(a=1, b=2) &gt;&gt;&gt; row[0] # Indexed access. 1 &gt;&gt;&gt; row.b # Attribute access. 2 &gt;&gt;&gt; con.close()

With some adjustments, the above recipe can be adapted to use a ~dataclasses.dataclass, or any other custom class, instead of a ~collections.namedtuple.

Attribution: Adapted from Python Documentation under PSF-2.0. Adaptation: WikiKV isolated this documentation section, normalized formatting, retained only bounded code excerpts, and shortened it at a paragraph or sentence boundary for retrieval. Verify version-sensitive details at the source.