In the preceding sections we’ve discussed a variety of schema constructs
including Table
,
ForeignKeyConstraint
,
CheckConstraint
, and
Sequence
. Throughout, we’ve relied upon the
create()
and create_all()
methods of
Table
and MetaData
in
order to issue data definition language (DDL) for all constructs. When issued,
a pre-determined order of operations is invoked, and DDL to create each table
is created unconditionally including all constraints and other objects
associated with it. For more complex scenarios where database-specific DDL is
required, SQLAlchemy offers two techniques which can be used to add any DDL
based on any condition, either accompanying the standard generation of tables
or by itself.
Custom DDL phrases are most easily achieved using the
DDL
construct. This construct works like all the
other DDL elements except it accepts a string which is the text to be emitted:
event.listen(
metadata,
"after_create",
DDL("ALTER TABLE users ADD CONSTRAINT "
"cst_user_name_length "
" CHECK (length(user_name) >= 8)")
)
A more comprehensive method of creating libraries of DDL constructs is to use custom compilation - see Custom SQL Constructs and Compilation Extension for details.
The DDL
construct introduced previously also has the
ability to be invoked conditionally based on inspection of the
database. This feature is available using the DDLElement.execute_if()
method. For example, if we wanted to create a trigger but only on
the PostgreSQL backend, we could invoke this as:
mytable = Table(
'mytable', metadata,
Column('id', Integer, primary_key=True),
Column('data', String(50))
)
trigger = DDL(
"CREATE TRIGGER dt_ins BEFORE INSERT ON mytable "
"FOR EACH ROW BEGIN SET NEW.data='ins'; END"
)
event.listen(
mytable,
'after_create',
trigger.execute_if(dialect='postgresql')
)
The DDLElement.execute_if.dialect
keyword also accepts a tuple
of string dialect names:
event.listen(
mytable,
"after_create",
trigger.execute_if(dialect=('postgresql', 'mysql'))
)
event.listen(
mytable,
"before_drop",
trigger.execute_if(dialect=('postgresql', 'mysql'))
)
The DDLElement.execute_if()
method can also work against a callable
function that will receive the database connection in use. In the
example below, we use this to conditionally create a CHECK constraint,
first looking within the PostgreSQL catalogs to see if it exists:
def should_create(ddl, target, connection, **kw):
row = connection.execute(
"select conname from pg_constraint where conname='%s'" %
ddl.element.name).scalar()
return not bool(row)
def should_drop(ddl, target, connection, **kw):
return not should_create(ddl, target, connection, **kw)
event.listen(
users,
"after_create",
DDL(
"ALTER TABLE users ADD CONSTRAINT "
"cst_user_name_length CHECK (length(user_name) >= 8)"
).execute_if(callable_=should_create)
)
event.listen(
users,
"before_drop",
DDL(
"ALTER TABLE users DROP CONSTRAINT cst_user_name_length"
).execute_if(callable_=should_drop)
)
sqlusers.create(engine)
CREATE TABLE users (
user_id SERIAL NOT NULL,
user_name VARCHAR(40) NOT NULL,
PRIMARY KEY (user_id)
)
select conname from pg_constraint where conname='cst_user_name_length'
ALTER TABLE users ADD CONSTRAINT cst_user_name_length CHECK (length(user_name) >= 8)
sqlusers.drop(engine)
select conname from pg_constraint where conname='cst_user_name_length'
ALTER TABLE users DROP CONSTRAINT cst_user_name_length
DROP TABLE users
The sqlalchemy.schema
package contains SQL expression constructs that
provide DDL expressions. For example, to produce a CREATE TABLE
statement:
from sqlalchemy.schema import CreateTable
sqlengine.execute(CreateTable(mytable))
CREATE TABLE mytable (
col1 INTEGER,
col2 INTEGER,
col3 INTEGER,
col4 INTEGER,
col5 INTEGER,
col6 INTEGER
)
Above, the CreateTable
construct works like any
other expression construct (such as select()
, table.insert()
, etc.).
All of SQLAlchemy’s DDL oriented constructs are subclasses of
the DDLElement
base class; this is the base of all the
objects corresponding to CREATE and DROP as well as ALTER,
not only in SQLAlchemy but in Alembic Migrations as well.
A full reference of available constructs is in DDL Expression Constructs API.
User-defined DDL constructs may also be created as subclasses of
DDLElement
itself. The documentation in
Custom SQL Constructs and Compilation Extension has several examples of this.
The event-driven DDL system described in the previous section
Controlling DDL Sequences is available with other DDLElement
objects as well. However, when dealing with the built-in constructs
such as CreateIndex
, CreateSequence
, etc, the event
system is of limited use, as methods like Table.create()
and
MetaData.create_all()
will invoke these constructs unconditionally.
In a future SQLAlchemy release, the DDL event system including conditional
execution will taken into account for built-in constructs that currently
invoke in all cases.
We can illustrate an event-driven
example with the AddConstraint
and DropConstraint
constructs, as the event-driven system will work for CHECK and UNIQUE
constraints, using these as we did in our previous example of
DDLElement.execute_if()
:
def should_create(ddl, target, connection, **kw):
row = connection.execute(
"select conname from pg_constraint where conname='%s'" %
ddl.element.name).scalar()
return not bool(row)
def should_drop(ddl, target, connection, **kw):
return not should_create(ddl, target, connection, **kw)
event.listen(
users,
"after_create",
AddConstraint(constraint).execute_if(callable_=should_create)
)
event.listen(
users,
"before_drop",
DropConstraint(constraint).execute_if(callable_=should_drop)
)
sqlusers.create(engine)
CREATE TABLE users (
user_id SERIAL NOT NULL,
user_name VARCHAR(40) NOT NULL,
PRIMARY KEY (user_id)
)
select conname from pg_constraint where conname='cst_user_name_length'
ALTER TABLE users ADD CONSTRAINT cst_user_name_length CHECK (length(user_name) >= 8)
sqlusers.drop(engine)
select conname from pg_constraint where conname='cst_user_name_length'
ALTER TABLE users DROP CONSTRAINT cst_user_name_length
DROP TABLE users
While the above example is against the built-in AddConstraint
and DropConstraint
objects, the main usefulness of DDL events
for now remains focused on the use of the DDL
construct itself,
as well as with user-defined subclasses of DDLElement
that aren’t
already part of the MetaData.create_all()
, Table.create()
,
and corresponding “drop” processes.
sqlalchemy.schema.
sort_tables
(tables, skip_fn=None, extra_dependencies=None)¶sort a collection of Table
objects based on dependency.
This is a dependency-ordered sort which will emit Table
objects such that they will follow their dependent Table
objects.
Tables are dependent on another based on the presence of
ForeignKeyConstraint
objects as well as explicit dependencies
added by Table.add_is_dependent_on()
.
Warning
The sort_tables()
function cannot by itself accommodate
automatic resolution of dependency cycles between tables, which
are usually caused by mutually dependent foreign key constraints.
To resolve these cycles, either the
ForeignKeyConstraint.use_alter
parameter may be applied
to those constraints, or use the
sql.sort_tables_and_constraints()
function which will break
out foreign key constraints involved in cycles separately.
skip_fn¶ – optional callable which will be passed a
ForeignKey
object; if it returns True, this
constraint will not be considered as a dependency. Note this is
different from the same parameter in
sort_tables_and_constraints()
, which is
instead passed the owning ForeignKeyConstraint
object.
extra_dependencies¶ – a sequence of 2-tuples of tables which will also be considered as dependent on each other.
sqlalchemy.schema.
sort_tables_and_constraints
(tables, filter_fn=None, extra_dependencies=None)¶sort a collection of Table
/ ForeignKeyConstraint
objects.
This is a dependency-ordered sort which will emit tuples of
(Table, [ForeignKeyConstraint, ...])
such that each
Table
follows its dependent Table
objects.
Remaining ForeignKeyConstraint
objects that are separate due to
dependency rules not satisfied by the sort are emitted afterwards
as (None, [ForeignKeyConstraint ...])
.
Tables are dependent on another based on the presence of
ForeignKeyConstraint
objects, explicit dependencies
added by Table.add_is_dependent_on()
, as well as dependencies
stated here using the skip_fn
and/or extra_dependencies
parameters.
filter_fn¶ – optional callable which will be passed a
ForeignKeyConstraint
object, and returns a value based on
whether this constraint should definitely be included or excluded as
an inline constraint, or neither. If it returns False, the constraint
will definitely be included as a dependency that cannot be subject
to ALTER; if True, it will only be included as an ALTER result at
the end. Returning None means the constraint is included in the
table-based result unless it is detected as part of a dependency cycle.
extra_dependencies¶ – a sequence of 2-tuples of tables which will also be considered as dependent on each other.
New in version 1.0.0.
See also
sqlalchemy.schema.
DDLElement
¶Bases: sqlalchemy.sql.expression.Executable
, sqlalchemy.schema._DDLCompiles
Base class for DDL expression constructs.
This class is the base for the general purpose DDL
class,
as well as the various create/drop clause constructs such as
CreateTable
, DropTable
, AddConstraint
,
etc.
DDLElement
integrates closely with SQLAlchemy events,
introduced in Events. An instance of one is
itself an event receiving callable:
event.listen(
users,
'after_create',
AddConstraint(constraint).execute_if(dialect='postgresql')
)
__call__
(target, bind, **kw)¶Execute the DDL as a ddl_listener.
against
(target)¶Return a copy of this DDL against a specific schema item.
bind
¶Returns the Engine
or Connection
to
which this Executable
is bound, or None if none found.
This is a traversal which checks locally, then checks among the “from” clauses of associated objects until a bound engine or connection is found.
callable_
= None¶dialect
= None¶execute
(bind=None, target=None)¶Execute this DDL immediately.
Executes the DDL statement in isolation using the supplied
Connectable
or
Connectable
assigned to the .bind
property, if not supplied. If the DDL has a conditional on
criteria, it will be invoked with None as the event.
bind¶ – Optional, an Engine
or Connection
. If not supplied, a valid
Connectable
must be present in the
.bind
property.
target¶ – Optional, defaults to None. The target SchemaItem for the
execute call. Will be passed to the on
callable if any,
and may also provide string expansion data for the
statement. See execute_at
for more information.
execute_at
(event_name, target)¶Link execution of this DDL to the DDL lifecycle of a SchemaItem.
Deprecated since version 0.7: The DDLElement.execute_at()
method is deprecated and will be removed in a future release. Please use the DDLEvents
listener interface in conjunction with the DDLElement.execute_if()
method.
Links this DDLElement
to a Table
or MetaData
instance,
executing it when that schema item is created or dropped. The DDL
statement will be executed using the same Connection and transactional
context as the Table create/drop itself. The .bind
property of
this statement is ignored.
A DDLElement instance can be linked to any number of schema items.
execute_at
builds on the append_ddl_listener
interface of
MetaData
and Table
objects.
Caveat: Creating or dropping a Table in isolation will also trigger
any DDL set to execute_at
that Table’s MetaData. This may change
in a future release.
execute_if
(dialect=None, callable_=None, state=None)¶Return a callable that will execute this DDLElement conditionally.
Used to provide a wrapper for event listening:
event.listen(
metadata,
'before_create',
DDL("my_ddl").execute_if(dialect='postgresql')
)
dialect¶ –
May be a string, tuple or a callable predicate. If a string, it will be compared to the name of the executing database dialect:
DDL('something').execute_if(dialect='postgresql')
If a tuple, specifies multiple dialect names:
DDL('something').execute_if(dialect=('postgresql', 'mysql'))
callable_¶ –
A callable, which will be invoked with four positional arguments as well as optional keyword arguments:
- ddl
This DDL element.
- target
The
Table
orMetaData
object which is the target of this event. May be None if the DDL is executed explicitly.- bind
The
Connection
being used for DDL execution- tables
Optional keyword argument - a list of Table objects which are to be created/ dropped within a MetaData.create_all() or drop_all() method call.
- state
Optional keyword argument - will be the
state
argument passed to this function.- checkfirst
Keyword argument, will be True if the ‘checkfirst’ flag was set during the call to
create()
,create_all()
,drop()
,drop_all()
.
If the callable returns a true value, the DDL statement will be executed.
state¶ – any value which will be passed to the callable_
as the state
keyword argument.
on
= None¶target
= None¶sqlalchemy.schema.
DDL
(statement, on=None, context=None, bind=None)¶Bases: sqlalchemy.schema.DDLElement
A literal DDL statement.
Specifies literal SQL DDL to be executed by the database. DDL objects
function as DDL event listeners, and can be subscribed to those events
listed in DDLEvents
, using either Table
or
MetaData
objects as targets. Basic templating support allows
a single DDL instance to handle repetitive tasks for multiple tables.
Examples:
from sqlalchemy import event, DDL
tbl = Table('users', metadata, Column('uid', Integer))
event.listen(tbl, 'before_create', DDL('DROP TRIGGER users_trigger'))
spow = DDL('ALTER TABLE %(table)s SET secretpowers TRUE')
event.listen(tbl, 'after_create', spow.execute_if(dialect='somedb'))
drop_spow = DDL('ALTER TABLE users SET secretpowers FALSE')
connection.execute(drop_spow)
When operating on Table events, the following statement
string substitutions are available:
%(table)s - the Table name, with any required quoting applied
%(schema)s - the schema name, with any required quoting applied
%(fullname)s - the Table name including schema, quoted if needed
The DDL’s “context”, if any, will be combined with the standard substitutions noted above. Keys present in the context will override the standard substitutions.
__init__
(statement, on=None, context=None, bind=None)¶Create a DDL statement.
statement¶ –
A string or unicode string to be executed. Statements will be
processed with Python’s string formatting operator. See the
context
argument and the execute_at
method.
A literal ‘%’ in a statement must be escaped as ‘%%’.
SQL bind parameters are not available in DDL statements.
on¶ –
Deprecated since version 0.7: The DDL.on
parameter is deprecated and will be removed in a future release. Please refer to DDLElement.execute_if()
.
Optional filtering criteria. May be a string, tuple or a callable predicate. If a string, it will be compared to the name of the executing database dialect:
DDL('something', on='postgresql')
If a tuple, specifies multiple dialect names:
DDL('something', on=('postgresql', 'mysql'))
If a callable, it will be invoked with four positional arguments as well as optional keyword arguments:
- ddl
This DDL element.
- event
The name of the event that has triggered this DDL, such as ‘after-create’ Will be None if the DDL is executed explicitly.
- target
The
Table
orMetaData
object which is the target of this event. May be None if the DDL is executed explicitly.- connection
The
Connection
being used for DDL execution- tables
Optional keyword argument - a list of Table objects which are to be created/ dropped within a MetaData.create_all() or drop_all() method call.
If the callable returns a true value, the DDL statement will be executed.
context¶ – Optional dictionary, defaults to None. These values will be available for use in string substitutions on the DDL statement.
bind¶ – Optional. A Connectable
, used by
default when execute()
is invoked without a bind argument.
sqlalchemy.schema.
_CreateDropBase
(element, on=None, bind=None)¶Bases: sqlalchemy.schema.DDLElement
Base class for DDL constructs that represent CREATE and DROP or equivalents.
The common theme of _CreateDropBase is a single
element
attribute which refers to the element
to be created or dropped.
sqlalchemy.schema.
CreateTable
(element, on=None, bind=None, include_foreign_key_constraints=None)¶Bases: sqlalchemy.schema._CreateDropBase
Represent a CREATE TABLE statement.
__init__
(element, on=None, bind=None, include_foreign_key_constraints=None)¶Create a CreateTable
construct.
include_foreign_key_constraints¶ –
optional sequence of
ForeignKeyConstraint
objects that will be included
inline within the CREATE construct; if omitted, all foreign key
constraints that do not specify use_alter=True are included.
New in version 1.0.0.
sqlalchemy.schema.
DropTable
(element, on=None, bind=None)¶Bases: sqlalchemy.schema._CreateDropBase
Represent a DROP TABLE statement.
sqlalchemy.schema.
CreateColumn
(element)¶Bases: sqlalchemy.schema._DDLCompiles
Represent a Column
as rendered in a CREATE TABLE statement,
via the CreateTable
construct.
This is provided to support custom column DDL within the generation
of CREATE TABLE statements, by using the
compiler extension documented in Custom SQL Constructs and Compilation Extension
to extend CreateColumn
.
Typical integration is to examine the incoming Column
object, and to redirect compilation if a particular flag or condition
is found:
from sqlalchemy import schema
from sqlalchemy.ext.compiler import compiles
@compiles(schema.CreateColumn)
def compile(element, compiler, **kw):
column = element.element
if "special" not in column.info:
return compiler.visit_create_column(element, **kw)
text = "%s SPECIAL DIRECTIVE %s" % (
column.name,
compiler.type_compiler.process(column.type)
)
default = compiler.get_column_default_string(column)
if default is not None:
text += " DEFAULT " + default
if not column.nullable:
text += " NOT NULL"
if column.constraints:
text += " ".join(
compiler.process(const)
for const in column.constraints)
return text
The above construct can be applied to a Table
as follows:
from sqlalchemy import Table, Metadata, Column, Integer, String
from sqlalchemy import schema
metadata = MetaData()
table = Table('mytable', MetaData(),
Column('x', Integer, info={"special":True}, primary_key=True),
Column('y', String(50)),
Column('z', String(20), info={"special":True})
)
metadata.create_all(conn)
Above, the directives we’ve added to the Column.info
collection
will be detected by our custom compilation scheme:
CREATE TABLE mytable (
x SPECIAL DIRECTIVE INTEGER NOT NULL,
y VARCHAR(50),
z SPECIAL DIRECTIVE VARCHAR(20),
PRIMARY KEY (x)
)
The CreateColumn
construct can also be used to skip certain
columns when producing a CREATE TABLE
. This is accomplished by
creating a compilation rule that conditionally returns None
.
This is essentially how to produce the same effect as using the
system=True
argument on Column
, which marks a column
as an implicitly-present “system” column.
For example, suppose we wish to produce a Table
which skips
rendering of the PostgreSQL xmin
column against the PostgreSQL
backend, but on other backends does render it, in anticipation of a
triggered rule. A conditional compilation rule could skip this name only
on PostgreSQL:
from sqlalchemy.schema import CreateColumn
@compiles(CreateColumn, "postgresql")
def skip_xmin(element, compiler, **kw):
if element.element.name == 'xmin':
return None
else:
return compiler.visit_create_column(element, **kw)
my_table = Table('mytable', metadata,
Column('id', Integer, primary_key=True),
Column('xmin', Integer)
)
Above, a CreateTable
construct will generate a CREATE TABLE
which only includes the id
column in the string; the xmin
column
will be omitted, but only against the PostgreSQL backend.
sqlalchemy.schema.
CreateSequence
(element, on=None, bind=None)¶Bases: sqlalchemy.schema._CreateDropBase
Represent a CREATE SEQUENCE statement.
sqlalchemy.schema.
DropSequence
(element, on=None, bind=None)¶Bases: sqlalchemy.schema._CreateDropBase
Represent a DROP SEQUENCE statement.
sqlalchemy.schema.
CreateIndex
(element, on=None, bind=None)¶Bases: sqlalchemy.schema._CreateDropBase
Represent a CREATE INDEX statement.
sqlalchemy.schema.
DropIndex
(element, on=None, bind=None)¶Bases: sqlalchemy.schema._CreateDropBase
Represent a DROP INDEX statement.
sqlalchemy.schema.
AddConstraint
(element, *args, **kw)¶Bases: sqlalchemy.schema._CreateDropBase
Represent an ALTER TABLE ADD CONSTRAINT statement.
sqlalchemy.schema.
DropConstraint
(element, cascade=False, **kw)¶Bases: sqlalchemy.schema._CreateDropBase
Represent an ALTER TABLE DROP CONSTRAINT statement.
sqlalchemy.schema.
CreateSchema
(name, quote=None, **kw)¶Bases: sqlalchemy.schema._CreateDropBase
Represent a CREATE SCHEMA statement.
The argument here is the string name of the schema.
__init__
(name, quote=None, **kw)¶Create a new CreateSchema
construct.
sqlalchemy.schema.
DropSchema
(name, quote=None, cascade=False, **kw)¶Bases: sqlalchemy.schema._CreateDropBase
Represent a DROP SCHEMA statement.
The argument here is the string name of the schema.
__init__
(name, quote=None, cascade=False, **kw)¶Create a new DropSchema
construct.