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.. _metadata_constraints_toplevel:
.. _metadata_constraints:
.. module:: sqlalchemy.schema
=================================
Defining Constraints and Indexes
=================================
.. _metadata_foreignkeys:
This section will discuss SQL :term:`constraints` and indexes. In SQLAlchemy
the key classes include :class:`.ForeignKeyConstraint` and :class:`.Index`.
Defining Foreign Keys
---------------------
A *foreign key* in SQL is a table-level construct that constrains one or more
columns in that table to only allow values that are present in a different set
of columns, typically but not always located on a different table. We call the
columns which are constrained the *foreign key* columns and the columns which
they are constrained towards the *referenced* columns. The referenced columns
almost always define the primary key for their owning table, though there are
exceptions to this. The foreign key is the "joint" that connects together
pairs of rows which have a relationship with each other, and SQLAlchemy
assigns very deep importance to this concept in virtually every area of its
operation.
In SQLAlchemy as well as in DDL, foreign key constraints can be defined as
additional attributes within the table clause, or for single-column foreign
keys they may optionally be specified within the definition of a single
column. The single column foreign key is more common, and at the column level
is specified by constructing a :class:`~sqlalchemy.schema.ForeignKey` object
as an argument to a :class:`~sqlalchemy.schema.Column` object::
user_preference = Table('user_preference', metadata,
Column('pref_id', Integer, primary_key=True),
Column('user_id', Integer, ForeignKey("user.user_id"), nullable=False),
Column('pref_name', String(40), nullable=False),
Column('pref_value', String(100))
)
Above, we define a new table ``user_preference`` for which each row must
contain a value in the ``user_id`` column that also exists in the ``user``
table's ``user_id`` column.
The argument to :class:`~sqlalchemy.schema.ForeignKey` is most commonly a
string of the form *<tablename>.<columnname>*, or for a table in a remote
schema or "owner" of the form *<schemaname>.<tablename>.<columnname>*. It may
also be an actual :class:`~sqlalchemy.schema.Column` object, which as we'll
see later is accessed from an existing :class:`~sqlalchemy.schema.Table`
object via its ``c`` collection::
ForeignKey(user.c.user_id)
The advantage to using a string is that the in-python linkage between ``user``
and ``user_preference`` is resolved only when first needed, so that table
objects can be easily spread across multiple modules and defined in any order.
Foreign keys may also be defined at the table level, using the
:class:`~sqlalchemy.schema.ForeignKeyConstraint` object. This object can
describe a single- or multi-column foreign key. A multi-column foreign key is
known as a *composite* foreign key, and almost always references a table that
has a composite primary key. Below we define a table ``invoice`` which has a
composite primary key::
invoice = Table('invoice', metadata,
Column('invoice_id', Integer, primary_key=True),
Column('ref_num', Integer, primary_key=True),
Column('description', String(60), nullable=False)
)
And then a table ``invoice_item`` with a composite foreign key referencing
``invoice``::
invoice_item = Table('invoice_item', metadata,
Column('item_id', Integer, primary_key=True),
Column('item_name', String(60), nullable=False),
Column('invoice_id', Integer, nullable=False),
Column('ref_num', Integer, nullable=False),
ForeignKeyConstraint(['invoice_id', 'ref_num'], ['invoice.invoice_id', 'invoice.ref_num'])
)
It's important to note that the
:class:`~sqlalchemy.schema.ForeignKeyConstraint` is the only way to define a
composite foreign key. While we could also have placed individual
:class:`~sqlalchemy.schema.ForeignKey` objects on both the
``invoice_item.invoice_id`` and ``invoice_item.ref_num`` columns, SQLAlchemy
would not be aware that these two values should be paired together - it would
be two individual foreign key constraints instead of a single composite
foreign key referencing two columns.
.. _use_alter:
Creating/Dropping Foreign Key Constraints via ALTER
~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
In all the above examples, the :class:`~sqlalchemy.schema.ForeignKey` object
causes the "REFERENCES" keyword to be added inline to a column definition
within a "CREATE TABLE" statement when
:func:`~sqlalchemy.schema.MetaData.create_all` is issued, and
:class:`~sqlalchemy.schema.ForeignKeyConstraint` invokes the "CONSTRAINT"
keyword inline with "CREATE TABLE". There are some cases where this is
undesirable, particularly when two tables reference each other mutually, each
with a foreign key referencing the other. In such a situation at least one of
the foreign key constraints must be generated after both tables have been
built. To support such a scheme, :class:`~sqlalchemy.schema.ForeignKey` and
:class:`~sqlalchemy.schema.ForeignKeyConstraint` offer the flag
``use_alter=True``. When using this flag, the constraint will be generated
using a definition similar to "ALTER TABLE <tablename> ADD CONSTRAINT <name>
...". Since a name is required, the ``name`` attribute must also be specified.
For example::
node = Table('node', meta,
Column('node_id', Integer, primary_key=True),
Column('primary_element', Integer,
ForeignKey('element.element_id', use_alter=True, name='fk_node_element_id')
)
)
element = Table('element', meta,
Column('element_id', Integer, primary_key=True),
Column('parent_node_id', Integer),
ForeignKeyConstraint(
['parent_node_id'],
['node.node_id'],
use_alter=True,
name='fk_element_parent_node_id'
)
)
.. _on_update_on_delete:
ON UPDATE and ON DELETE
~~~~~~~~~~~~~~~~~~~~~~~
Most databases support *cascading* of foreign key values, that is the when a
parent row is updated the new value is placed in child rows, or when the
parent row is deleted all corresponding child rows are set to null or deleted.
In data definition language these are specified using phrases like "ON UPDATE
CASCADE", "ON DELETE CASCADE", and "ON DELETE SET NULL", corresponding to
foreign key constraints. The phrase after "ON UPDATE" or "ON DELETE" may also
other allow other phrases that are specific to the database in use. The
:class:`~sqlalchemy.schema.ForeignKey` and
:class:`~sqlalchemy.schema.ForeignKeyConstraint` objects support the
generation of this clause via the ``onupdate`` and ``ondelete`` keyword
arguments. The value is any string which will be output after the appropriate
"ON UPDATE" or "ON DELETE" phrase::
child = Table('child', meta,
Column('id', Integer,
ForeignKey('parent.id', onupdate="CASCADE", ondelete="CASCADE"),
primary_key=True
)
)
composite = Table('composite', meta,
Column('id', Integer, primary_key=True),
Column('rev_id', Integer),
Column('note_id', Integer),
ForeignKeyConstraint(
['rev_id', 'note_id'],
['revisions.id', 'revisions.note_id'],
onupdate="CASCADE", ondelete="SET NULL"
)
)
Note that these clauses are not supported on SQLite, and require ``InnoDB``
tables when used with MySQL. They may also not be supported on other
databases.
UNIQUE Constraint
-----------------
Unique constraints can be created anonymously on a single column using the
``unique`` keyword on :class:`~sqlalchemy.schema.Column`. Explicitly named
unique constraints and/or those with multiple columns are created via the
:class:`~sqlalchemy.schema.UniqueConstraint` table-level construct.
.. sourcecode:: python+sql
from sqlalchemy import UniqueConstraint
meta = MetaData()
mytable = Table('mytable', meta,
# per-column anonymous unique constraint
Column('col1', Integer, unique=True),
Column('col2', Integer),
Column('col3', Integer),
# explicit/composite unique constraint. 'name' is optional.
UniqueConstraint('col2', 'col3', name='uix_1')
)
CHECK Constraint
----------------
Check constraints can be named or unnamed and can be created at the Column or
Table level, using the :class:`~sqlalchemy.schema.CheckConstraint` construct.
The text of the check constraint is passed directly through to the database,
so there is limited "database independent" behavior. Column level check
constraints generally should only refer to the column to which they are
placed, while table level constraints can refer to any columns in the table.
Note that some databases do not actively support check constraints such as
MySQL.
.. sourcecode:: python+sql
from sqlalchemy import CheckConstraint
meta = MetaData()
mytable = Table('mytable', meta,
# per-column CHECK constraint
Column('col1', Integer, CheckConstraint('col1>5')),
Column('col2', Integer),
Column('col3', Integer),
# table level CHECK constraint. 'name' is optional.
CheckConstraint('col2 > col3 + 5', name='check1')
)
{sql}mytable.create(engine)
CREATE TABLE mytable (
col1 INTEGER CHECK (col1>5),
col2 INTEGER,
col3 INTEGER,
CONSTRAINT check1 CHECK (col2 > col3 + 5)
){stop}
PRIMARY KEY Constraint
----------------------
The primary key constraint of any :class:`.Table` object is implicitly
present, based on the :class:`.Column` objects that are marked with the
:paramref:`.Column.primary_key` flag. The :class:`.PrimaryKeyConstraint`
object provides explicit access to this constraint, which includes the
option of being configured directly::
from sqlalchemy import PrimaryKeyConstraint
my_table = Table('mytable', metadata,
Column('id', Integer),
Column('version_id', Integer),
Column('data', String(50)),
PrimaryKeyConstraint('id', 'version_id', name='mytable_pk')
)
.. seealso::
:class:`.PrimaryKeyConstraint` - detailed API documentation.
Setting up Constraints when using the Declarative ORM Extension
----------------------------------------------------------------
The :class:`.Table` is the SQLAlchemy Core construct that allows one to define
table metadata, which among other things can be used by the SQLAlchemy ORM
as a target to map a class. The :ref:`Declarative <declarative_toplevel>`
extension allows the :class:`.Table` object to be created automatically, given
the contents of the table primarily as a mapping of :class:`.Column` objects.
To apply table-level constraint objects such as :class:`.ForeignKeyConstraint`
to a table defined using Declarative, use the ``__table_args__`` attribute,
described at :ref:`declarative_table_args`.
.. _constraint_naming_conventions:
Configuring Constraint Naming Conventions
-----------------------------------------
Relational databases typically assign explicit names to all constraints and
indexes. In the common case that a table is created using ``CREATE TABLE``
where constraints such as CHECK, UNIQUE, and PRIMARY KEY constraints are
produced inline with the table definition, the database usually has a system
in place in which names are automatically assigned to these constraints, if
a name is not otherwise specified. When an existing database table is altered
in a database using a command such as ``ALTER TABLE``, this command typically
needs to specify expicit names for new constraints as well as be able to
specify the name of an existing constraint that is to be dropped or modified.
Constraints can be named explicitly using the :paramref:`.Constraint.name` parameter,
and for indexes the :paramref:`.Index.name` parameter. However, in the
case of constraints this parameter is optional. There are also the use
cases of using the :paramref:`.Column.unique` and :paramref:`.Column.index`
parameters which create :class:`.UniqueConstraint` and :class:`.Index` objects
without an explicit name being specified.
The use case of alteration of existing tables and constraints can be handled
by schema migration tools such as `Alembic <http://http://alembic.readthedocs.org/>`_.
However, neither Alembic nor SQLAlchemy currently create names for constraint
objects where the name is otherwise unspecified, leading to the case where
being able to alter existing constraints means that one must reverse-engineer
the naming system used by the relational database to auto-assign names,
or that care must be taken to ensure that all constraints are named.
In contrast to having to assign explicit names to all :class:`.Constraint`
and :class:`.Index` objects, automated naming schemes can be constructed
using events. This approach has the advantage that constraints will get
a consistent naming scheme without the need for explicit name parameters
throughout the code, and also that the convention takes place just as well
for those constraints and indexes produced by the :paramref:`.Column.unique`
and :paramref:`.Column.index` parameters. As of SQLAlchemy 0.9.2 this
event-based approach is included, and can be configured using the argument
:paramref:`.MetaData.naming_convention`.
:paramref:`.MetaData.naming_convention` refers to a dictionary which accepts
the :class:`.Index` class or individual :class:`.Constraint` classes as keys,
and Python string templates as values. It also accepts a series of
string-codes as alternative keys, ``"fk"``, ``"pk"``,
``"ix"``, ``"ck"``, ``"uq"`` for foreign key, primary key, index,
check, and unique constraint, respectively. The string templates in this
dictionary are used whenever a constraint or index is associated with this
:class:`.MetaData` object that does not have an existing name given (including
one exception case where an existing name can be further embellished).
An example naming convention that suits basic cases is as follows::
convention = {
"ix": 'ix_%(column_0_label)s',
"uq": "uq_%(table_name)s_%(column_0_name)s",
"ck": "ck_%(table_name)s_%(constraint_name)s",
"fk": "fk_%(table_name)s_%(column_0_name)s_%(referred_table_name)s",
"pk": "pk_%(table_name)s"
}
metadata = MetaData(naming_convention=convention)
The above convention will establish names for all constraints within
the target :class:`.MetaData` collection.
For example, we can observe the name produced when we create an unnamed
:class:`.UniqueConstraint`::
>>> user_table = Table('user', metadata,
... Column('id', Integer, primary_key=True),
... Column('name', String(30), nullable=False),
... UniqueConstraint('name')
... )
>>> list(user_table.constraints)[1].name
'uq_user_name'
This same feature takes effect even if we just use the :paramref:`.Column.unique`
flag::
>>> user_table = Table('user', metadata,
... Column('id', Integer, primary_key=True),
... Column('name', String(30), nullable=False, unique=True)
... )
>>> list(user_table.constraints)[1].name
'uq_user_name'
A key advantage to the naming convention approach is that the names are established
at Python construction time, rather than at DDL emit time. The effect this has
when using Alembic's ``--autogenerate`` feature is that the naming convention
will be explicit when a new migration script is generated::
def upgrade():
op.create_unique_constraint("uq_user_name", "user", ["name"])
The above ``"uq_user_name"`` string was copied from the :class:`.UniqueConstraint`
object that ``--autogenerate`` located in our metadata.
The default value for :paramref:`.MetaData.naming_convention` handles
the long-standing SQLAlchemy behavior of assigning a name to a :class:`.Index`
object that is created using the :paramref:`.Column.index` parameter::
>>> from sqlalchemy.sql.schema import DEFAULT_NAMING_CONVENTION
>>> DEFAULT_NAMING_CONVENTION
immutabledict({'ix': 'ix_%(column_0_label)s'})
The tokens available include ``%(table_name)s``,
``%(referred_table_name)s``, ``%(column_0_name)s``, ``%(column_0_label)s``,
``%(column_0_key)s``, ``%(referred_column_0_name)s``, and ``%(constraint_name)s``;
the documentation for :paramref:`.MetaData.naming_convention` describes each
individually. New tokens can also be added, by specifying an additional
token and a callable within the naming_convention dictionary. For example,
if we wanted to name our foreign key constraints using a GUID scheme,
we could do that as follows::
import uuid
def fk_guid(constraint, table):
str_tokens = [
table.name,
] + [
element.parent.name for element in constraint.elements
] + [
element.target_fullname for element in constraint.elements
]
guid = uuid.uuid5(uuid.NAMESPACE_OID, "_".join(str_tokens).encode('ascii'))
return str(guid)
convention = {
"fk_guid": fk_guid,
"ix": 'ix_%(column_0_label)s',
"fk": "fk_%(fk_guid)s",
}
Above, when we create a new :class:`.ForeignKeyConstraint`, we will get a
name as follows::
>>> metadata = MetaData(naming_convention=convention)
>>> user_table = Table('user', metadata,
... Column('id', Integer, primary_key=True),
... Column('version', Integer, primary_key=True),
... Column('data', String(30))
... )
>>> address_table = Table('address', metadata,
... Column('id', Integer, primary_key=True),
... Column('user_id', Integer),
... Column('user_version_id', Integer)
... )
>>> fk = ForeignKeyConstraint(['user_id', 'user_version_id'],
... ['user.id', 'user.version'])
>>> address_table.append_constraint(fk)
>>> fk.name
fk_0cd51ab5-8d70-56e8-a83c-86661737766d
.. seealso::
:paramref:`.MetaData.naming_convention` - for additional usage details
as well as a listing of all available naming components.
:ref:`alembic:tutorial_constraint_names` - in the Alembic documentation.
.. versionadded:: 0.9.2 Added the :paramref:`.MetaData.naming_convention` argument.
Constraints API
---------------
.. autoclass:: Constraint
:members:
.. autoclass:: CheckConstraint
:members:
:inherited-members:
.. autoclass:: ColumnCollectionConstraint
:members:
.. autoclass:: ForeignKey
:members:
:inherited-members:
.. autoclass:: ForeignKeyConstraint
:members:
:inherited-members:
.. autoclass:: PrimaryKeyConstraint
:members:
:inherited-members:
.. autoclass:: UniqueConstraint
:members:
:inherited-members:
.. autofunction:: sqlalchemy.schema.conv
.. _schema_indexes:
Indexes
-------
Indexes can be created anonymously (using an auto-generated name ``ix_<column
label>``) for a single column using the inline ``index`` keyword on
:class:`~sqlalchemy.schema.Column`, which also modifies the usage of
``unique`` to apply the uniqueness to the index itself, instead of adding a
separate UNIQUE constraint. For indexes with specific names or which encompass
more than one column, use the :class:`~sqlalchemy.schema.Index` construct,
which requires a name.
Below we illustrate a :class:`~sqlalchemy.schema.Table` with several
:class:`~sqlalchemy.schema.Index` objects associated. The DDL for "CREATE
INDEX" is issued right after the create statements for the table:
.. sourcecode:: python+sql
meta = MetaData()
mytable = Table('mytable', meta,
# an indexed column, with index "ix_mytable_col1"
Column('col1', Integer, index=True),
# a uniquely indexed column with index "ix_mytable_col2"
Column('col2', Integer, index=True, unique=True),
Column('col3', Integer),
Column('col4', Integer),
Column('col5', Integer),
Column('col6', Integer),
)
# place an index on col3, col4
Index('idx_col34', mytable.c.col3, mytable.c.col4)
# place a unique index on col5, col6
Index('myindex', mytable.c.col5, mytable.c.col6, unique=True)
{sql}mytable.create(engine)
CREATE TABLE mytable (
col1 INTEGER,
col2 INTEGER,
col3 INTEGER,
col4 INTEGER,
col5 INTEGER,
col6 INTEGER
)
CREATE INDEX ix_mytable_col1 ON mytable (col1)
CREATE UNIQUE INDEX ix_mytable_col2 ON mytable (col2)
CREATE UNIQUE INDEX myindex ON mytable (col5, col6)
CREATE INDEX idx_col34 ON mytable (col3, col4){stop}
Note in the example above, the :class:`.Index` construct is created
externally to the table which it corresponds, using :class:`.Column`
objects directly. :class:`.Index` also supports
"inline" definition inside the :class:`.Table`, using string names to
identify columns::
meta = MetaData()
mytable = Table('mytable', meta,
Column('col1', Integer),
Column('col2', Integer),
Column('col3', Integer),
Column('col4', Integer),
# place an index on col1, col2
Index('idx_col12', 'col1', 'col2'),
# place a unique index on col3, col4
Index('idx_col34', 'col3', 'col4', unique=True)
)
.. versionadded:: 0.7
Support of "inline" definition inside the :class:`.Table`
for :class:`.Index`\ .
The :class:`~sqlalchemy.schema.Index` object also supports its own ``create()`` method:
.. sourcecode:: python+sql
i = Index('someindex', mytable.c.col5)
{sql}i.create(engine)
CREATE INDEX someindex ON mytable (col5){stop}
.. _schema_indexes_functional:
Functional Indexes
~~~~~~~~~~~~~~~~~~~
:class:`.Index` supports SQL and function expressions, as supported by the
target backend. To create an index against a column using a descending
value, the :meth:`.ColumnElement.desc` modifier may be used::
from sqlalchemy import Index
Index('someindex', mytable.c.somecol.desc())
Or with a backend that supports functional indexes such as Postgresql,
a "case insensitive" index can be created using the ``lower()`` function::
from sqlalchemy import func, Index
Index('someindex', func.lower(mytable.c.somecol))
.. versionadded:: 0.8 :class:`.Index` supports SQL expressions and functions
as well as plain columns.
Index API
---------
.. autoclass:: Index
:members:
:inherited-members:
|