This section will discuss SQL constraints and indexes. In SQLAlchemy the key classes include ForeignKeyConstraint and Index.
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 ForeignKey object as an argument to a 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 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 Column object, which as we’ll see later is accessed from an existing 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 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 ForeignKeyConstraint is the only way to define a composite foreign key. While we could also have placed individual 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.
In all the above examples, the ForeignKey object causes the “REFERENCES” keyword to be added inline to a column definition within a “CREATE TABLE” statement when create_all() is issued, and ForeignKeyConstraint invokes the “CONSTRAINT” keyword inline with “CREATE TABLE”. There are some cases where this is undesireable, 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, ForeignKey and 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'
)
)
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 ForeignKey and 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 constraints can be created anonymously on a single column using the unique keyword on Column. Explicitly named unique constraints and/or those with multiple columns are created via the UniqueConstraint table-level construct.
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 constraints can be named or unnamed and can be created at the Column or Table level, using the 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.
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')
)
sqlmytable.create(engine)
CREATE TABLE mytable (
col1 INTEGER CHECK (col1>5),
col2 INTEGER,
col3 INTEGER,
CONSTRAINT check1 CHECK (col2 > col3 + 5)
)
The 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 Declarative extension allows the Table object to be created automatically, given the contents of the table primarily as a mapping of Column objects.
To apply table-level constraint objects such as ForeignKeyConstraint to a table defined using Declarative, use the __table_args__ attribute, described at Table Configuration.
Bases: sqlalchemy.schema.SchemaItem
A table-level SQL constraint.
Bases: sqlalchemy.schema.Constraint
A table- or column-level CHECK constraint.
Can be included in the definition of a Table or Column.
Bases: sqlalchemy.schema.ColumnCollectionMixin, sqlalchemy.schema.Constraint
A constraint that proxies a ColumnCollection.
Bases: sqlalchemy.schema.SchemaItem
Defines a dependency between two columns.
ForeignKey is specified as an argument to a Column object, e.g.:
t = Table("remote_table", metadata,
Column("remote_id", ForeignKey("main_table.id"))
)
Note that ForeignKey is only a marker object that defines a dependency between two columns. The actual constraint is in all cases represented by the ForeignKeyConstraint object. This object will be generated automatically when a ForeignKey is associated with a Column which in turn is associated with a Table. Conversely, when ForeignKeyConstraint is applied to a Table, ForeignKey markers are automatically generated to be present on each associated Column, which are also associated with the constraint object.
Note that you cannot define a “composite” foreign key constraint, that is a constraint between a grouping of multiple parent/child columns, using ForeignKey objects. To define this grouping, the ForeignKeyConstraint object must be used, and applied to the Table. The associated ForeignKey objects are created automatically.
The ForeignKey objects associated with an individual Column object are available in the foreign_keys collection of that column.
Further examples of foreign key configuration are in metadata_foreignkeys.
Construct a column-level FOREIGN KEY.
The ForeignKey object when constructed generates a ForeignKeyConstraint which is associated with the parent Table object’s collection of constraints.
Parameters: |
|
---|
Return the target Column referenced by this ForeignKey.
If this ForeignKey was created using a string-based target column specification, this attribute will on first access initiate a resolution process to locate the referenced remote Column. The resolution process traverses to the parent Column, Table, and MetaData to proceed - if any of these aren’t yet present, an error is raised.
Produce a copy of this ForeignKey object.
The new ForeignKey will not be bound to any Column.
This method is usually used by the internal copy procedures of Column, Table, and MetaData.
Parameters: | schema¶ – The returned ForeignKey will reference the original table and column name, qualified by the given string schema name. |
---|
Return the Column in the given Table referenced by this ForeignKey.
Returns None if this ForeignKey does not reference the given Table.
Return True if the given Table is referenced by this ForeignKey.
Return a string based ‘column specification’ for this ForeignKey.
This is usually the equivalent of the string-based “tablename.colname” argument first passed to the object’s constructor.
Bases: sqlalchemy.schema.Constraint
A table-level FOREIGN KEY constraint.
Defines a single column or composite FOREIGN KEY ... REFERENCES constraint. For a no-frills, single column foreign key, adding a ForeignKey to the definition of a Column is a shorthand equivalent for an unnamed, single column ForeignKeyConstraint.
Examples of foreign key configuration are in metadata_foreignkeys.
Construct a composite-capable FOREIGN KEY.
Parameters: |
|
---|
Bases: sqlalchemy.schema.ColumnCollectionConstraint
A table-level PRIMARY KEY constraint.
Defines a single column or composite PRIMARY KEY constraint. For a no-frills primary key, adding primary_key=True to one or more Column definitions is a shorthand equivalent for an unnamed single- or multiple-column PrimaryKeyConstraint.
Bases: sqlalchemy.schema.ColumnCollectionConstraint
A table-level UNIQUE constraint.
Defines a single column or composite UNIQUE constraint. For a no-frills, single column constraint, adding unique=True to the Column definition is a shorthand equivalent for an unnamed, single column UniqueConstraint.
Indexes can be created anonymously (using an auto-generated name ix_<column label>) for a single column using the inline index keyword on 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 Index construct, which requires a name.
Below we illustrate a Table with several Index objects associated. The DDL for “CREATE INDEX” is issued right after the create statements for the table:
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)
sqlmytable.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)
Note in the example above, the Index construct is created externally to the table which it corresponds, using Column objects directly. Index also supports “inline” definition inside the 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)
)
The Index object also supports its own create() method:
i = Index('someindex', mytable.c.col5)
sqli.create(engine)
CREATE INDEX someindex ON mytable (col5)
Index supports SQL and function expressions, as supported by the target backend. To create an index against a column using a descending value, the 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))
New in version 0.8: Index supports SQL expressions and functions as well as plain columns.
Bases: sqlalchemy.schema.ColumnCollectionMixin, sqlalchemy.schema.SchemaItem
A table-level INDEX.
Defines a composite (one or more column) INDEX.
E.g.:
sometable = Table("sometable", metadata,
Column("name", String(50)),
Column("address", String(100))
)
Index("some_index", sometable.c.name)
For a no-frills, single column index, adding Column also supports index=True:
sometable = Table("sometable", metadata,
Column("name", String(50), index=True)
)
For a composite index, multiple columns can be specified:
Index("some_index", sometable.c.name, sometable.c.address)
Functional indexes are supported as well, keeping in mind that at least one Column must be present:
Index("some_index", func.lower(sometable.c.name))
New in version 0.8: support for functional and expression-based indexes.
See also
Indexes - General information on Index.
Postgresql-Specific Index Options - PostgreSQL-specific options available for the Index construct.
MySQL Specific Index Options - MySQL-specific options available for the Index construct.
MSSQL-Specific Index Options - MSSQL-specific options available for the Index construct.
Construct an index object.
Parameters: |
---|
Return the connectable associated with this Index.
Issue a CREATE statement for this Index, using the given Connectable for connectivity.
See also
Issue a DROP statement for this Index, using the given Connectable for connectivity.
See also