.. _unitofwork_cascades:

Cascades
========

Mappers support the concept of configurable :term:`cascade` behavior on
:func:`~sqlalchemy.orm.relationship` constructs.  This refers
to how operations performed on a "parent" object relative to a
particular :class:`.Session` should be propagated to items
referred to by that relationship (e.g. "child" objects), and is
affected by the :paramref:`.relationship.cascade` option.

The default behavior of cascade is limited to cascades of the
so-called :ref:`cascade_save_update` and :ref:`cascade_merge` settings.
The typical "alternative" setting for cascade is to add
the :ref:`cascade_delete` and :ref:`cascade_delete_orphan` options;
these settings are appropriate for related objects which only exist as
long as they are attached to their parent, and are otherwise deleted.

Cascade behavior is configured using the by changing the
:paramref:`~.relationship.cascade` option on
:func:`~sqlalchemy.orm.relationship`::

    class Order(Base):
        __tablename__ = 'order'

        items = relationship("Item", cascade="all, delete-orphan")
        customer = relationship("User", cascade="save-update")

To set cascades on a backref, the same flag can be used with the
:func:`~.sqlalchemy.orm.backref` function, which ultimately feeds
its arguments back into :func:`~sqlalchemy.orm.relationship`::

    class Item(Base):
        __tablename__ = 'item'

        order = relationship("Order",
                        backref=backref("items", cascade="all, delete-orphan")
                    )

.. sidebar:: The Origins of Cascade

    SQLAlchemy's notion of cascading behavior on relationships,
    as well as the options to configure them, are primarily derived
    from the similar feature in the Hibernate ORM; Hibernate refers
    to "cascade" in a few places such as in
    `Example: Parent/Child <https://docs.jboss.org/hibernate/orm/3.3/reference/en-US/html/example-parentchild.html>`_.
    If cascades are confusing, we'll refer to their conclusion,
    stating "The sections we have just covered can be a bit confusing.
    However, in practice, it all works out nicely."

The default value of :paramref:`~.relationship.cascade` is ``save-update, merge``.
The typical alternative setting for this parameter is either
``all`` or more commonly ``all, delete-orphan``.  The ``all`` symbol
is a synonym for ``save-update, merge, refresh-expire, expunge, delete``,
and using it in conjunction with ``delete-orphan`` indicates that the child
object should follow along with its parent in all cases, and be deleted once
it is no longer associated with that parent.

The list of available values which can be specified for
the :paramref:`~.relationship.cascade` parameter are described in the following subsections.

.. _cascade_save_update:

save-update
-----------

``save-update`` cascade indicates that when an object is placed into a
:class:`.Session` via :meth:`.Session.add`, all the objects associated
with it via this :func:`.relationship` should also be added to that
same :class:`.Session`.  Suppose we have an object ``user1`` with two
related objects ``address1``, ``address2``::

    >>> user1 = User()
    >>> address1, address2 = Address(), Address()
    >>> user1.addresses = [address1, address2]

If we add ``user1`` to a :class:`.Session`, it will also add
``address1``, ``address2`` implicitly::

    >>> sess = Session()
    >>> sess.add(user1)
    >>> address1 in sess
    True

``save-update`` cascade also affects attribute operations for objects
that are already present in a :class:`.Session`.  If we add a third
object, ``address3`` to the ``user1.addresses`` collection, it
becomes part of the state of that :class:`.Session`::

    >>> address3 = Address()
    >>> user1.append(address3)
    >>> address3 in sess
    >>> True

``save-update`` has the possibly surprising behavior which is that
persistent objects which were *removed* from a collection
or in some cases a scalar attribute
may also be pulled into the :class:`.Session` of a parent object; this is
so that the flush process may handle that related object appropriately.
This case can usually only arise if an object is removed from one :class:`.Session`
and added to another::

    >>> user1 = sess1.query(User).filter_by(id=1).first()
    >>> address1 = user1.addresses[0]
    >>> sess1.close()   # user1, address1 no longer associated with sess1
    >>> user1.addresses.remove(address1)  # address1 no longer associated with user1
    >>> sess2 = Session()
    >>> sess2.add(user1)   # ... but it still gets added to the new session,
    >>> address1 in sess2  # because it's still "pending" for flush
    True

The ``save-update`` cascade is on by default, and is typically taken
for granted; it simplifies code by allowing a single call to
:meth:`.Session.add` to register an entire structure of objects within
that :class:`.Session` at once.   While it can be disabled, there
is usually not a need to do so.

One case where ``save-update`` cascade does sometimes get in the way is in that
it takes place in both directions for bi-directional relationships, e.g.
backrefs, meaning that the association of a child object with a particular parent
can have the effect of the parent object being implicitly associated with that
child object's :class:`.Session`; this pattern, as well as how to modify its
behavior using the :paramref:`~.relationship.cascade_backrefs` flag,
is discussed in the section :ref:`backref_cascade`.

.. _cascade_delete:

delete
------

The ``delete`` cascade indicates that when a "parent" object
is marked for deletion, its related "child" objects should also be marked
for deletion.   If for example we we have a relationship ``User.addresses``
with ``delete`` cascade configured::

    class User(Base):
        # ...

        addresses = relationship("Address", cascade="save-update, merge, delete")

If using the above mapping, we have a ``User`` object and two
related ``Address`` objects::

    >>> user1 = sess.query(User).filter_by(id=1).first()
    >>> address1, address2 = user1.addresses

If we mark ``user1`` for deletion, after the flush operation proceeds,
``address1`` and ``address2`` will also be deleted:

.. sourcecode:: python+sql

    >>> sess.delete(user1)
    >>> sess.commit()
    {opensql}DELETE FROM address WHERE address.id = ?
    ((1,), (2,))
    DELETE FROM user WHERE user.id = ?
    (1,)
    COMMIT

Alternatively, if our ``User.addresses`` relationship does *not* have
``delete`` cascade, SQLAlchemy's default behavior is to instead de-associate
``address1`` and ``address2`` from ``user1`` by setting their foreign key
reference to ``NULL``.  Using a mapping as follows::

    class User(Base):
        # ...

        addresses = relationship("Address")

Upon deletion of a parent ``User`` object, the rows in ``address`` are not
deleted, but are instead de-associated:

.. sourcecode:: python+sql

    >>> sess.delete(user1)
    >>> sess.commit()
    {opensql}UPDATE address SET user_id=? WHERE address.id = ?
    (None, 1)
    UPDATE address SET user_id=? WHERE address.id = ?
    (None, 2)
    DELETE FROM user WHERE user.id = ?
    (1,)
    COMMIT

``delete`` cascade is more often than not used in conjunction with
:ref:`cascade_delete_orphan` cascade, which will emit a DELETE for the related
row if the "child" object is deassociated from the parent.  The combination
of ``delete`` and ``delete-orphan`` cascade covers both situations where
SQLAlchemy has to decide between setting a foreign key column to NULL versus
deleting the row entirely.

.. topic:: ORM-level "delete" cascade vs. FOREIGN KEY level "ON DELETE" cascade

    The behavior of SQLAlchemy's "delete" cascade has a lot of overlap with the
    ``ON DELETE CASCADE`` feature of a database foreign key, as well
    as with that of the ``ON DELETE SET NULL`` foreign key setting when "delete"
    cascade is not specified.   Database level "ON DELETE" cascades are specific to the
    "FOREIGN KEY" construct of the relational database; SQLAlchemy allows
    configuration of these schema-level constructs at the :term:`DDL` level
    using options on :class:`.ForeignKeyConstraint` which are described
    at :ref:`on_update_on_delete`.

    It is important to note the differences between the ORM and the relational
    database's notion of "cascade" as well as how they integrate:

    * A database level ``ON DELETE`` cascade is configured effectively
      on the **many-to-one** side of the relationship; that is, we configure
      it relative to the ``FOREIGN KEY`` constraint that is the "many" side
      of a relationship.  At the ORM level, **this direction is reversed**.
      SQLAlchemy handles the deletion of "child" objects relative to a
      "parent" from the "parent" side, which means that ``delete`` and
      ``delete-orphan`` cascade are configured on the **one-to-many**
      side.

    * Database level foreign keys with no ``ON DELETE`` setting
      are often used to **prevent** a parent
      row from being removed, as it would necessarily leave an unhandled
      related row present.  If this behavior is desired in a one-to-many
      relationship, SQLAlchemy's default behavior of setting a foreign key
      to ``NULL`` can be caught in one of two ways:

        * The easiest and most common is just to set the
          foreign-key-holding column to ``NOT NULL`` at the database schema
          level.  An attempt by SQLAlchemy to set the column to NULL will
          fail with a simple NOT NULL constraint exception.

        * The other, more special case way is to set the :paramref:`~.relationship.passive_deletes`
          flag to the string ``"all"``.  This has the effect of entirely
          disabling SQLAlchemy's behavior of setting the foreign key column
          to NULL, and a DELETE will be emitted for the parent row without
          any affect on the child row, even if the child row is present
          in memory. This may be desirable in the case when
          database-level foreign key triggers, either special ``ON DELETE`` settings
          or otherwise, need to be activated in all cases when a parent row is deleted.

    * Database level ``ON DELETE`` cascade is **vastly more efficient**
      than that of SQLAlchemy.  The database can chain a series of cascade
      operations across many relationships at once; e.g. if row A is deleted,
      all the related rows in table B can be deleted, and all the C rows related
      to each of those B rows, and on and on, all within the scope of a single
      DELETE statement.  SQLAlchemy on the other hand, in order to support
      the cascading delete operation fully, has to individually load each
      related collection in order to target all rows that then may have further
      related collections.  That is, SQLAlchemy isn't sophisticated enough
      to emit a DELETE for all those related rows at once within this context.

    * SQLAlchemy doesn't **need** to be this sophisticated, as we instead provide
      smooth integration with the database's own ``ON DELETE`` functionality,
      by using the :paramref:`~.relationship.passive_deletes` option in conjunction
      with properly configured foreign key constraints.   Under this behavior,
      SQLAlchemy only emits DELETE for those rows that are already locally
      present in the :class:`.Session`; for any collections that are unloaded,
      it leaves them to the database to handle, rather than emitting a SELECT
      for them.  The section :ref:`passive_deletes` provides an example of this use.

    * While database-level ``ON DELETE`` functionality works only on the "many"
      side of a relationship, SQLAlchemy's "delete" cascade
      has **limited** ability to operate in the *reverse* direction as well,
      meaning it can be configured on the "many" side to delete an object
      on the "one" side when the reference on the "many" side is deleted.  However
      this can easily result in constraint violations if there are other objects
      referring to this "one" side from the "many", so it typically is only
      useful when a relationship is in fact a "one to one".  The
      :paramref:`~.relationship.single_parent` flag should be used to establish
      an in-Python assertion for this case.


When using a :func:`.relationship` that also includes a many-to-many
table using the :paramref:`~.relationship.secondary` option, SQLAlchemy's
delete cascade handles the rows in this many-to-many table automatically.
Just like, as described in :ref:`relationships_many_to_many_deletion`,
the addition or removal of an object from a many-to-many collection
results in the INSERT or DELETE of a row in the many-to-many table,
the ``delete`` cascade, when activated as the result of a parent object
delete operation, will DELETE not just the row in the "child" table but also
in the many-to-many table.

.. _cascade_delete_orphan:

delete-orphan
-------------

``delete-orphan`` cascade adds behavior to the ``delete`` cascade,
such that a child object will be marked for deletion when it is
de-associated from the parent, not just when the parent is marked
for deletion.   This is a common feature when dealing with a related
object that is "owned" by its parent, with a NOT NULL foreign key,
so that removal of the item from the parent collection results
in its deletion.

``delete-orphan`` cascade implies that each child object can only
have one parent at a time, so is configured in the vast majority of cases
on a one-to-many relationship.   Setting it on a many-to-one or
many-to-many relationship is more awkward; for this use case,
SQLAlchemy requires that the :func:`~sqlalchemy.orm.relationship`
be configured with the :paramref:`~.relationship.single_parent` argument,
establishes Python-side validation that ensures the object
is associated with only one parent at a time.

.. _cascade_merge:

merge
-----

``merge`` cascade indicates that the :meth:`.Session.merge`
operation should be propagated from a parent that's the subject
of the :meth:`.Session.merge` call down to referred objects.
This cascade is also on by default.

.. _cascade_refresh_expire:

refresh-expire
--------------

``refresh-expire`` is an uncommon option, indicating that the
:meth:`.Session.expire` operation should be propagated from a parent
down to referred objects.   When using :meth:`.Session.refresh`,
the referred objects are expired only, but not actually refreshed.

.. _cascade_expunge:

expunge
-------

``expunge`` cascade indicates that when the parent object is removed
from the :class:`.Session` using :meth:`.Session.expunge`, the
operation should be propagated down to referred objects.

.. _backref_cascade:

Controlling Cascade on Backrefs
-------------------------------

The :ref:`cascade_save_update` cascade by default takes place on attribute change events
emitted from backrefs.  This is probably a confusing statement more
easily described through demonstration; it means that, given a mapping such as this::

    mapper(Order, order_table, properties={
        'items' : relationship(Item, backref='order')
    })

If an ``Order`` is already in the session, and is assigned to the ``order``
attribute of an ``Item``, the backref appends the ``Order`` to the ``items``
collection of that ``Order``, resulting in the ``save-update`` cascade taking
place::

    >>> o1 = Order()
    >>> session.add(o1)
    >>> o1 in session
    True

    >>> i1 = Item()
    >>> i1.order = o1
    >>> i1 in o1.items
    True
    >>> i1 in session
    True

This behavior can be disabled using the :paramref:`~.relationship.cascade_backrefs` flag::

    mapper(Order, order_table, properties={
        'items' : relationship(Item, backref='order',
                                    cascade_backrefs=False)
    })

So above, the assignment of ``i1.order = o1`` will append ``i1`` to the ``items``
collection of ``o1``, but will not add ``i1`` to the session.   You can, of
course, :meth:`~.Session.add` ``i1`` to the session at a later point.   This
option may be helpful for situations where an object needs to be kept out of a
session until it's construction is completed, but still needs to be given
associations to objects which are already persistent in the target session.
