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.. _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.
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