.. highlight:: pycon+sql

.. |prev| replace:: :doc:`relationships`
.. |next| replace:: :doc:`query`

.. include:: queryguide_nav_include.rst


=============================
ORM API Features for Querying
=============================

ORM Loader Options
-------------------

Loader options are objects which, when passed to the
:meth:`_sql.Select.options` method of a :class:`.Select` object or similar SQL
construct, affect the loading of both column and relationship-oriented
attributes. The majority of loader options descend from the :class:`_orm.Load`
hierarchy. For a complete overview of using loader options, see the linked
sections below.

.. seealso::

    * :ref:`loading_columns` - details mapper and loading options that affect
      how column and SQL-expression mapped attributes are loaded

    * :ref:`loading_toplevel` - details relationship and loading options that
      affect how :func:`_orm.relationship` mapped attributes are loaded

.. _orm_queryguide_execution_options:

ORM Execution Options
---------------------

ORM-level execution options are keyword options that may be associated with a
statement execution using either the
:paramref:`_orm.Session.execute.execution_options` parameter, which is a
dictionary argument accepted by :class:`_orm.Session` methods such as
:meth:`_orm.Session.execute` and :meth:`_orm.Session.scalars`, or by
associating them directly with the statement to be invoked itself using the
:meth:`_sql.Executable.execution_options` method, which accepts them as
arbitrary keyword arguments.

ORM-level options are distinct from the Core level execution options
documented at :meth:`_engine.Connection.execution_options`.
It's important to note that the ORM options
discussed below are **not** compatible with Core level methods
:meth:`_engine.Connection.execution_options` or
:meth:`_engine.Engine.execution_options`; the options are ignored at this
level, even if the :class:`.Engine` or :class:`.Connection` is associated
with the :class:`_orm.Session` in use.

Within this section, the :meth:`_sql.Executable.execution_options` method
style will be illustrated for examples.

.. _orm_queryguide_populate_existing:

Populate Existing
^^^^^^^^^^^^^^^^^^

The ``populate_existing`` execution option ensures that, for all rows
loaded, the corresponding instances in the :class:`_orm.Session` will
be fully refreshed – erasing any existing data within the objects
(including pending changes) and replacing with the data loaded from the
result.

Example use looks like::

    >>> stmt = select(User).execution_options(populate_existing=True)
    >>> result = session.execute(stmt)
    {execsql}SELECT user_account.id, user_account.name, user_account.fullname
    FROM user_account
    ...

Normally, ORM objects are only loaded once, and if they are matched up
to the primary key in a subsequent result row, the row is not applied to the
object.  This is both to preserve pending, unflushed changes on the object
as well as to avoid the overhead and complexity of refreshing data which
is already there.   The :class:`_orm.Session` assumes a default working
model of a highly isolated transaction, and to the degree that data is
expected to change within the transaction outside of the local changes being
made, those use cases would be handled using explicit steps such as this method.

Using ``populate_existing``, any set of objects that matches a query
can be refreshed, and it also allows control over relationship loader options.
E.g. to refresh an instance while also refreshing a related set of objects:

.. sourcecode:: python

    stmt = (
        select(User)
        .where(User.name.in_(names))
        .execution_options(populate_existing=True)
        .options(selectinload(User.addresses))
    )
    # will refresh all matching User objects as well as the related
    # Address objects
    users = session.execute(stmt).scalars().all()

Another use case for ``populate_existing`` is in support of various
attribute loading features that can change how an attribute is loaded on
a per-query basis.   Options for which this apply include:

* The :func:`_orm.with_expression` option

* The :meth:`_orm.PropComparator.and_` method that can modify what a loader
  strategy loads

* The :func:`_orm.contains_eager` option

* The :func:`_orm.with_loader_criteria` option

* The :func:`_orm.load_only` option to select what attributes to refresh

The ``populate_existing`` execution option is equvialent to the
:meth:`_orm.Query.populate_existing` method in :term:`1.x style` ORM queries.

.. seealso::

    :ref:`faq_session_identity` - in :doc:`/faq/index`

    :ref:`session_expire` - in the ORM :class:`_orm.Session`
    documentation

.. _orm_queryguide_autoflush:

Autoflush
^^^^^^^^^

This option, when passed as ``False``, will cause the :class:`_orm.Session`
to not invoke the "autoflush" step.  It is equivalent to using the
:attr:`_orm.Session.no_autoflush` context manager to disable autoflush::

    >>> stmt = select(User).execution_options(autoflush=False)
    >>> session.execute(stmt)
    {execsql}SELECT user_account.id, user_account.name, user_account.fullname
    FROM user_account
    ...

This option will also work on ORM-enabled :class:`_sql.Update` and
:class:`_sql.Delete` queries.

The ``autoflush`` execution option is equvialent to the
:meth:`_orm.Query.autoflush` method in :term:`1.x style` ORM queries.

.. seealso::

    :ref:`session_flushing`

.. _orm_queryguide_yield_per:

Fetching Large Result Sets with Yield Per
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^

The ``yield_per`` execution option is an integer value which will cause the
:class:`_engine.Result` to buffer only a limited number of rows and/or ORM
objects at a time, before making data available to the client.

Normally, the ORM will fetch **all** rows immediately, constructing ORM objects
for each and assembling those objects into a single buffer, before passing this
buffer to the :class:`_engine.Result` object as a source of rows to be
returned. The rationale for this behavior is to allow correct behavior for
features such as joined eager loading, uniquifying of results, and the general
case of result handling logic that relies upon the identity map maintaining a
consistent state for every object in a result set as it is fetched.

The purpose of the ``yield_per`` option is to change this behavior so that the
ORM result set is optimized for iteration through very large result sets (e.g.
> 10K rows), where the user has determined that the above patterns don't apply.
When ``yield_per`` is used, the ORM will instead batch ORM results into
sub-collections and yield rows from each sub-collection individually as the
:class:`_engine.Result` object is iterated, so that the Python interpreter
doesn't need to declare very large areas of memory which is both time consuming
and leads to excessive memory use. The option affects both the way the database
cursor is used as well as how the ORM constructs rows and objects to be passed
to the :class:`_engine.Result`.

.. tip::

    From the above, it follows that the :class:`_engine.Result` must be
    consumed in an iterable fashion, that is, using iteration such as
    ``for row in result`` or using partial row methods such as
    :meth:`_engine.Result.fetchmany` or :meth:`_engine.Result.partitions`.
    Calling :meth:`_engine.Result.all` will defeat the purpose of using
    ``yield_per``.

Using ``yield_per`` is equivalent to making use
of both the :paramref:`_engine.Connection.execution_options.stream_results`
execution option, which selects for server side cursors to be used
by the backend if supported, and the :meth:`_engine.Result.yield_per` method
on the returned :class:`_engine.Result` object,
which establishes a fixed size of rows to be fetched as well as a
corresponding limit to how many ORM objects will be constructed at once.

.. tip::

    ``yield_per`` is now available as a Core execution option as well,
    described in detail at :ref:`engine_stream_results`.  This section details
    the use of ``yield_per`` as an execution option with an ORM
    :class:`_orm.Session`.  The option behaves as similarly as possible
    in both contexts.

When used with the ORM, ``yield_per`` must be established either
via the :meth:`.Executable.execution_options` method on the given statement
or by passing it to the :paramref:`_orm.Session.execute.execution_options`
parameter of :meth:`_orm.Session.execute` or other similar :class:`_orm.Session`
method such as :meth:`_orm.Session.scalars`.  Typical use for fetching
ORM objects is illustrated below::

    >>> stmt = select(User).execution_options(yield_per=10)
    >>> for user_obj in session.scalars(stmt):
    ...     print(user_obj)
    {execsql}SELECT user_account.id, user_account.name, user_account.fullname
    FROM user_account
    [...] ()
    {stop}User(id=1, name='spongebob', fullname='Spongebob Squarepants')
    User(id=2, name='sandy', fullname='Sandy Cheeks')
    ...
    >>> # ... rows continue ...

The above code is equivalent to the example below, which uses
:paramref:`_engine.Connection.execution_options.stream_results`
and :paramref:`_engine.Connection.execution_options.max_row_buffer` Core-level
execution options in conjunction with the :meth:`_engine.Result.yield_per`
method of :class:`_engine.Result`::

    # equivalent code
    >>> stmt = select(User).execution_options(stream_results=True, max_row_buffer=10)
    >>> for user_obj in session.scalars(stmt).yield_per(10):
    ...     print(user_obj)
    {execsql}SELECT user_account.id, user_account.name, user_account.fullname
    FROM user_account
    [...] ()
    {stop}User(id=1, name='spongebob', fullname='Spongebob Squarepants')
    User(id=2, name='sandy', fullname='Sandy Cheeks')
    ...
    >>> # ... rows continue ...

``yield_per`` is also commonly used in combination with the
:meth:`_engine.Result.partitions` method, which will iterate rows in grouped
partitions. The size of each partition defaults to the integer value passed to
``yield_per``, as in the below example::

    >>> stmt = select(User).execution_options(yield_per=10)
    >>> for partition in session.scalars(stmt).partitions():
    ...     for user_obj in partition:
    ...         print(user_obj)
    {execsql}SELECT user_account.id, user_account.name, user_account.fullname
    FROM user_account
    [...] ()
    {stop}User(id=1, name='spongebob', fullname='Spongebob Squarepants')
    User(id=2, name='sandy', fullname='Sandy Cheeks')
    ...
    >>> # ... rows continue ...


The ``yield_per`` execution option **is not compatible** with
:ref:`"subquery" eager loading <subquery_eager_loading>` loading or
:ref:`"joined" eager loading <joined_eager_loading>` when using collections. It
is potentially compatible with :ref:`"select in" eager loading
<selectin_eager_loading>` , provided the database driver supports multiple,
independent cursors.

Additionally, the ``yield_per`` execution option is not compatible
with the :meth:`_engine.Result.unique` method; as this method relies upon
storing a complete set of identities for all rows, it would necessarily
defeat the purpose of using ``yield_per`` which is to handle an arbitrarily
large number of rows.

.. versionchanged:: 1.4.6  An exception is raised when ORM rows are fetched
   from a :class:`_engine.Result` object that makes use of the
   :meth:`_engine.Result.unique` filter, at the same time as the ``yield_per``
   execution option is used.

When using the legacy :class:`_orm.Query` object with
:term:`1.x style` ORM use, the :meth:`_orm.Query.yield_per` method
will have the same result as that of the ``yield_per`` execution option.


.. seealso::

    :ref:`engine_stream_results`

.. _queryguide_identity_token:

Identity Token
^^^^^^^^^^^^^^

.. doctest-disable:

.. deepalchemy::   This option is an advanced-use feature mostly intended
   to be used with the :ref:`horizontal_sharding_toplevel` extension. For
   typical cases of loading objects with identical primary keys from different
   "shards" or partitions, consider using individual :class:`_orm.Session`
   objects per shard first.


The "identity token" is an arbitrary value that can be associated within
the :term:`identity key` of newly loaded objects.   This element exists
first and foremost to support extensions which perform per-row "sharding",
where objects may be loaded from any number of replicas of a particular
database table that nonetheless have overlapping primary key values.
The primary consumer of "identity token" is the
:ref:`horizontal_sharding_toplevel` extension, which supplies a general
framework for persisting objects among multiple "shards" of a particular
database table.

The ``identity_token`` execution option may be used on a per-query basis
to directly affect this token.   Using it directly, one can populate a
:class:`_orm.Session` with multiple instances of an object that have the
same primary key and source table, but different "identities".

One such example is to populate a :class:`_orm.Session` with objects that
come from same-named tables in different schemas, using the
:ref:`schema_translating` feature which can affect the choice of schema
within the scope of queries.  Given a mapping as:

.. sourcecode:: python

    from sqlalchemy.orm import DeclarativeBase
    from sqlalchemy.orm import Mapped
    from sqlalchemy.orm import mapped_column


    class Base(DeclarativeBase):
        pass


    class MyTable(Base):
        __tablename__ = "my_table"

        id: Mapped[int] = mapped_column(primary_key=True)
        name: Mapped[str]

The default "schema" name for the class above is ``None``, meaning, no
schema qualification will be written into SQL statements.  However,
if we make use of :paramref:`_engine.Connection.execution_options.schema_translate_map`,
mapping ``None`` to an alternate schema, we can place instances of
``MyTable`` into two different schemas:

.. sourcecode:: python

    engine = create_engine(
        "postgresql+psycopg://scott:tiger@localhost/test",
    )

    with Session(
        engine.execution_options(schema_translate_map={None: "test_schema"})
    ) as sess:
        sess.add(MyTable(name="this is schema one"))
        sess.commit()

    with Session(
        engine.execution_options(schema_translate_map={None: "test_schema_2"})
    ) as sess:
        sess.add(MyTable(name="this is schema two"))
        sess.commit()

The above two blocks create a :class:`_orm.Session` object linked to a different
schema translate map each time, and an instance of ``MyTable`` is persisted
into both ``test_schema.my_table`` as well as ``test_schema_2.my_table``.

The :class:`_orm.Session` objects above are independent.  If we wanted to
persist both objects in one transaction, we would need to use the
:ref:`horizontal_sharding_toplevel` extension to do this.

However, we can illustrate querying for these objects in one session as follows:

.. sourcecode:: python

    with Session(engine) as sess:
        obj1 = sess.scalar(
            select(MyTable)
            .where(MyTable.id == 1)
            .execution_options(
                schema_translate_map={None: "test_schema"},
                identity_token="test_schema",
            )
        )
        obj2 = sess.scalar(
            select(MyTable)
            .where(MyTable.id == 1)
            .execution_options(
                schema_translate_map={None: "test_schema_2"},
                identity_token="test_schema_2",
            )
        )

Both ``obj1`` and ``obj2`` are distinct from each other.  However, they both
refer to primary key id 1 for the ``MyTable`` class, yet are distinct.
This is how the ``identity_token`` comes into play, which we can see in the
inspection of each object, where we look at :attr:`_orm.InstanceState.key`
to view the two distinct identity tokens::

    >>> from sqlalchemy import inspect
    >>> inspect(obj1).key
    (<class '__main__.MyTable'>, (1,), 'test_schema')
    >>> inspect(obj2).key
    (<class '__main__.MyTable'>, (1,), 'test_schema_2')


The above logic takes place automatically when using the
:ref:`horizontal_sharding_toplevel` extension.

.. versionadded:: 2.0.0rc1 - added the ``identity_token`` ORM level execution
   option.

.. seealso::

    :ref:`examples_sharding` - in the :ref:`examples_toplevel` section.
    See the script ``separate_schema_translates.py`` for a demonstration of
    the above use case using the full sharding API.


.. doctest-enable:

.. _queryguide_inspection:

Inspecting entities and columns from ORM-enabled SELECT and DML statements
==========================================================================

The :func:`_sql.select` construct, as well as the :func:`_sql.insert`, :func:`_sql.update`
and :func:`_sql.delete` constructs (for the latter DML constructs, as of SQLAlchemy
1.4.33), all support the ability to inspect the entities in which these
statements are created against, as well as the columns and datatypes that would
be returned in a result set.

For a :class:`.Select` object, this information is available from the
:attr:`.Select.column_descriptions` attribute. This attribute operates in the
same way as the legacy :attr:`.Query.column_descriptions` attribute. The format
returned is a list of dictionaries::

    >>> from pprint import pprint
    >>> user_alias = aliased(User, name="user2")
    >>> stmt = select(User, User.id, user_alias)
    >>> pprint(stmt.column_descriptions)
    [{'aliased': False,
      'entity': <class 'User'>,
      'expr': <class 'User'>,
      'name': 'User',
      'type': <class 'User'>},
     {'aliased': False,
      'entity': <class 'User'>,
      'expr': <....InstrumentedAttribute object at ...>,
      'name': 'id',
      'type': Integer()},
     {'aliased': True,
      'entity': <AliasedClass ...; User>,
      'expr': <AliasedClass ...; User>,
      'name': 'user2',
      'type': <class 'User'>}]


When :attr:`.Select.column_descriptions` is used with non-ORM objects
such as plain :class:`.Table` or :class:`.Column` objects, the entries
will contain basic information about individual columns returned in all
cases::

    >>> stmt = select(user_table, address_table.c.id)
    >>> pprint(stmt.column_descriptions)
    [{'expr': Column('id', Integer(), table=<user_account>, primary_key=True, nullable=False),
      'name': 'id',
      'type': Integer()},
     {'expr': Column('name', String(), table=<user_account>, nullable=False),
      'name': 'name',
      'type': String()},
     {'expr': Column('fullname', String(), table=<user_account>),
      'name': 'fullname',
      'type': String()},
     {'expr': Column('id', Integer(), table=<address>, primary_key=True, nullable=False),
      'name': 'id_1',
      'type': Integer()}]

.. versionchanged:: 1.4.33 The :attr:`.Select.column_descriptions` attribute now returns
   a value when used against a :class:`.Select` that is not ORM-enabled.  Previously,
   this would raise ``NotImplementedError``.


For :func:`_sql.insert`, :func:`.update` and :func:`.delete` constructs, there are
two separate attributes. One is :attr:`.UpdateBase.entity_description` which
returns information about the primary ORM entity and database table which the
DML construct would be affecting::

    >>> from sqlalchemy import update
    >>> stmt = update(User).values(name="somename").returning(User.id)
    >>> pprint(stmt.entity_description)
    {'entity': <class 'User'>,
     'expr': <class 'User'>,
     'name': 'User',
     'table': Table('user_account', ...),
     'type': <class 'User'>}

.. tip::  The :attr:`.UpdateBase.entity_description` includes an entry
   ``"table"`` which is actually the **table to be inserted, updated or
   deleted** by the statement, which is **not** always the same as the SQL
   "selectable" to which the class may be mapped. For example, in a
   joined-table inheritance scenario, ``"table"`` will refer to the local table
   for the given entity.

The other is :attr:`.UpdateBase.returning_column_descriptions` which
delivers information about the columns present in the RETURNING collection
in a manner roughly similar to that of :attr:`.Select.column_descriptions`::

    >>> pprint(stmt.returning_column_descriptions)
    [{'aliased': False,
      'entity': <class 'User'>,
      'expr': <sqlalchemy.orm.attributes.InstrumentedAttribute ...>,
      'name': 'id',
      'type': Integer()}]

.. versionadded:: 1.4.33 Added the :attr:`.UpdateBase.entity_description`
   and :attr:`.UpdateBase.returning_column_descriptions` attributes.


.. highlight:: python3

.. _queryguide_additional:

Additional ORM API Constructs
=============================


.. autofunction:: sqlalchemy.orm.aliased

.. autoclass:: sqlalchemy.orm.util.AliasedClass

.. autoclass:: sqlalchemy.orm.util.AliasedInsp

.. autoclass:: sqlalchemy.orm.Bundle
    :members:

.. autofunction:: sqlalchemy.orm.with_loader_criteria

.. autofunction:: sqlalchemy.orm.join

.. autofunction:: sqlalchemy.orm.outerjoin

.. autofunction:: sqlalchemy.orm.with_parent


..  Setup code, not for display

    >>> session.close()
    >>> conn.close()
    ROLLBACK
