.. _psycopg.rows: `rows` -- row factory implementations ===================================== .. module:: psycopg.rows The module exposes a few generic `~psycopg.RowFactory` implementation, which can be used to retrieve data from the database in more complex structures than the basic tuples. Check out :ref:`row-factories` for information about how to use these objects. .. autofunction:: tuple_row .. autofunction:: dict_row .. autofunction:: namedtuple_row .. autofunction:: class_row This is not a row factory, but rather a factory of row factories. Specifying `!row_factory=class_row(MyClass)` will create connections and cursors returning `!MyClass` objects on fetch. Example:: from dataclasses import dataclass import psycopg from psycopg.rows import class_row @dataclass class Person: first_name: str last_name: str age: int = None conn = psycopg.connect() cur = conn.cursor(row_factory=class_row(Person)) cur.execute("select 'John' as first_name, 'Smith' as last_name").fetchone() # Person(first_name='John', last_name='Smith', age=None) .. autofunction:: args_row .. autofunction:: kwargs_row Formal rows protocols --------------------- These objects can be used to describe your own rows adapter for static typing checks, such as mypy_. .. _mypy: https://mypy.readthedocs.io/ .. autoclass:: psycopg.rows.RowMaker() .. method:: __call__(values: Sequence[Any]) -> Row Convert a sequence of values from the database to a finished object. .. autoclass:: psycopg.rows.RowFactory() .. method:: __call__(cursor: Cursor[Row]) -> RowMaker[Row] Inspect the result on a cursor and return a `RowMaker` to convert rows. .. autoclass:: psycopg.rows.AsyncRowFactory() .. autoclass:: psycopg.rows.BaseRowFactory() Note that it's easy to implement an object implementing both `!RowFactory` and `!AsyncRowFactory`: usually, everything you need to implement a row factory is to access the cursor's `~psycopg.Cursor.description`, which is provided by both the cursor flavours.