Customizing DDL¶

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¶

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.

Controlling DDL Sequences¶

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 ExecutableDDLElement.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)),
)

func = DDL(
    "CREATE FUNCTION my_func() "
    "RETURNS TRIGGER AS $$ "
    "BEGIN "
    "NEW.data := 'ins'; "
    "RETURN NEW; "
    "END; $$ LANGUAGE PLPGSQL"
)

trigger = DDL(
    "CREATE TRIGGER dt_ins BEFORE INSERT ON mytable "
    "FOR EACH ROW EXECUTE PROCEDURE my_func();"
)

event.listen(mytable, "after_create", func.execute_if(dialect="postgresql"))

event.listen(mytable, "after_create", trigger.execute_if(dialect="postgresql"))

The ExecutableDDLElement.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 ExecutableDDLElement.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:

defshould_create(ddl,target,connection,**kw):row=connection.execute("select conname from pg_constraint where conname='%s'"%ddl.element.name).scalar()returnnotbool(row)defshould_drop(ddl,target,connection,**kw):returnnotshould_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),)users.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)
users.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

Using the built-in DDLElement Classes¶

The sqlalchemy.schema package contains SQL expression constructs that provide DDL expressions, all of which extend from the common base ExecutableDDLElement. For example, to produce a CREATE TABLE statement, one can use the CreateTable construct:

fromsqlalchemy.schemaimportCreateTablewithengine.connect()asconn:conn.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 ExecutableDDLElement 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 ExecutableDDLElement itself. The documentation in Custom SQL Constructs and Compilation Extension has several examples of this.

Controlling DDL Generation of Constraints and Indexes¶

New in version 2.0.

While the previously mentioned ExecutableDDLElement.execute_if() method is useful for custom DDL classes which need to invoke conditionally, there is also a common need for elements that are typically related to a particular Table, namely constraints and indexes, to also be subject to “conditional” rules, such as an index that includes features that are specific to a particular backend such as PostgreSQL or SQL Server. For this use case, the Constraint.ddl_if() and Index.ddl_if() methods may be used against constructs such as CheckConstraint, UniqueConstraint and Index, accepting the same arguments as the ExecutableDDLElement.execute_if() method in order to control whether or not their DDL will be emitted in terms of their parent Table object. These methods may be used inline when creating the definition for a Table (or similarly, when using the __table_args__ collection in an ORM declarative mapping), such as:

from sqlalchemy import CheckConstraint, Index
from sqlalchemy import MetaData, Table, Column
from sqlalchemy import Integer, String

meta = MetaData()

my_table = Table(
    "my_table",
    meta,
    Column("id", Integer, primary_key=True),
    Column("num", Integer),
    Column("data", String),
    Index("my_pg_index", "data").ddl_if(dialect="postgresql"),
    CheckConstraint("num > 5").ddl_if(dialect="postgresql"),
)

In the above example, the Table construct refers to both an Index and a CheckConstraint construct, both which indicate .ddl_if(dialect="postgresql"), which indicates that these elements will be included in the CREATE TABLE sequence only against the PostgreSQL dialect. If we run meta.create_all() against the SQLite dialect, for example, neither construct will be included:

>>> fromsqlalchemyimportcreate_engine>>> sqlite_engine=create_engine("sqlite+pysqlite://",echo=True)>>> meta.create_all(sqlite_engine)BEGIN (implicit)
PRAGMA main.table_info("my_table")
[raw sql] ()
PRAGMA temp.table_info("my_table")
[raw sql] ()

CREATE TABLE my_table (
    id INTEGER NOT NULL,
    num INTEGER,
    data VARCHAR,
    PRIMARY KEY (id)
)

However, if we run the same commands against a PostgreSQL database, we will see inline DDL for the CHECK constraint as well as a separate CREATE statement emitted for the index:

>>> fromsqlalchemyimportcreate_engine>>> postgresql_engine=create_engine(...     "postgresql+psycopg2://scott:tiger@localhost/test", echo=True... )>>> meta.create_all(postgresql_engine)BEGIN (implicit)
select relname from pg_class c join pg_namespace n on n.oid=c.relnamespace where pg_catalog.pg_table_is_visible(c.oid) and relname=%(name)s
[generated in 0.00009s] {'name': 'my_table'}

CREATE TABLE my_table (
    id SERIAL NOT NULL,
    num INTEGER,
    data VARCHAR,
    PRIMARY KEY (id),
    CHECK (num > 5)
)
[no key 0.00007s] {}
CREATE INDEX my_pg_index ON my_table (data)
[no key 0.00013s] {}
COMMIT

The Constraint.ddl_if() and Index.ddl_if() methods create an event hook that may be consulted not just at DDL execution time, as is the behavior with ExecutableDDLElement.execute_if(), but also within the SQL compilation phase of the CreateTable object, which is responsible for rendering the CHECK (num > 5) DDL inline within the CREATE TABLE statement. As such, the event hook that is received by the ddl_if.callable_() parameter has a richer argument set present, including that there is a dialect keyword argument passed, as well as an instance of DDLCompiler via the compiler keyword argument for the “inline rendering” portion of the sequence. The bind argument is not present when the event is triggered within the DDLCompiler sequence, so a modern event hook that wishes to inspect the database versioning information would best use the given Dialect object, such as to test PostgreSQL versioning:

def only_pg_14(ddl_element, target, bind, dialect, **kw):
    return dialect.name == "postgresql" and dialect.server_version_info >= (14,)


my_table = Table(
    "my_table",
    meta,
    Column("id", Integer, primary_key=True),
    Column("num", Integer),
    Column("data", String),
    Index("my_pg_index", "data").ddl_if(callable_=only_pg_14),
)

See also

Constraint.ddl_if()

Index.ddl_if()

DDL Expression Constructs API¶

Object Name	Description
_CreateDropBase	Base class for DDL constructs that represent CREATE and DROP or equivalents.
AddConstraint	Represent an ALTER TABLE ADD CONSTRAINT statement.
BaseDDLElement	The root of DDL constructs, including those that are sub-elements within the “create table” and other processes.
CreateColumn	Represent a `Column` as rendered in a CREATE TABLE statement, via the `CreateTable` construct.
CreateIndex	Represent a CREATE INDEX statement.
CreateSchema	Represent a CREATE SCHEMA statement.
CreateSequence	Represent a CREATE SEQUENCE statement.
CreateTable	Represent a CREATE TABLE statement.
DDL	A literal DDL statement.
DropConstraint	Represent an ALTER TABLE DROP CONSTRAINT statement.
DropIndex	Represent a DROP INDEX statement.
DropSchema	Represent a DROP SCHEMA statement.
DropSequence	Represent a DROP SEQUENCE statement.
DropTable	Represent a DROP TABLE statement.
ExecutableDDLElement	Base class for standalone executable DDL expression constructs.
sort_tables(tables[, skip_fn, extra_dependencies])	Sort a collection of `Table` objects based on dependency.
sort_tables_and_constraints(tables[, filter_fn, extra_dependencies, _warn_for_cycles])	Sort a collection of `Table` / `ForeignKeyConstraint` objects.

function sqlalchemy.schema.sort_tables(tables: Iterable[TableClause], skip_fn: Callable[[ForeignKeyConstraint], bool] | None = None, extra_dependencies: typing_Sequence[Tuple[TableClause, TableClause]] | None = None) → List[Table]¶

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. When these cycles are detected, the foreign keys of these tables are omitted from consideration in the sort. A warning is emitted when this condition occurs, which will be an exception raise in a future release. Tables which are not part of the cycle will still be returned in dependency order.

To resolve these cycles, the ForeignKeyConstraint.use_alter parameter may be applied to those constraints which create a cycle. Alternatively, the sort_tables_and_constraints() function will automatically return foreign key constraints in a separate collection when cycles are detected so that they may be applied to a schema separately.

Changed in version 1.3.17: - a warning is emitted when sort_tables() cannot perform a proper sort due to cyclical dependencies. This will be an exception in a future release. Additionally, the sort will continue to return other tables not involved in the cycle in dependency order which was not the case previously.

Parameters:

tables – a sequence of Table objects.
skip_fn – optional callable which will be passed a ForeignKeyConstraint 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.

See also

sort_tables_and_constraints()

MetaData.sorted_tables - uses this function to sort

function sqlalchemy.schema.sort_tables_and_constraints(tables, filter_fn=None, extra_dependencies=None, _warn_for_cycles=False)¶

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 sort_tables_and_constraints.skip_fn and/or sort_tables_and_constraints.extra_dependencies parameters.

Parameters:

tables – a sequence of Table objects.
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.

See also

sort_tables()

class sqlalchemy.schema.BaseDDLElement¶: The root of DDL constructs, including those that are sub-elements within the “create table” and other processes.

New in version 2.0.

Class signature

class sqlalchemy.schema.BaseDDLElement (sqlalchemy.sql.expression.ClauseElement)

class sqlalchemy.schema.ExecutableDDLElement¶

Base class for standalone executable 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.

Changed in version 2.0: ExecutableDDLElement is renamed from DDLElement, which still exists for backwards compatibility.

ExecutableDDLElement 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')
)

See also

DDL

DDLEvents

Events

Controlling DDL Sequences

Members

__call__(), against(), execute_if()

Class signature

class sqlalchemy.schema.ExecutableDDLElement (sqlalchemy.sql.roles.DDLRole, sqlalchemy.sql.expression.Executable, sqlalchemy.schema.BaseDDLElement)

method sqlalchemy.schema.ExecutableDDLElement.__call__(target, bind, **kw)¶: Execute the DDL as a ddl_listener.

method sqlalchemy.schema.ExecutableDDLElement.against(target: SchemaItem) → Self¶

Return a copy of this ExecutableDDLElement which will include the given target.

This essentially applies the given item to the .target attribute of the returned ExecutableDDLElement object. This target is then usable by event handlers and compilation routines in order to provide services such as tokenization of a DDL string in terms of a particular Table.

When a ExecutableDDLElement object is established as an event handler for the DDLEvents.before_create() or DDLEvents.after_create() events, and the event then occurs for a given target such as a Constraint or Table, that target is established with a copy of the ExecutableDDLElement object using this method, which then proceeds to the ExecutableDDLElement.execute() method in order to invoke the actual DDL instruction.

Parameters:: target – a SchemaItem that will be the subject of a DDL operation.
Returns:: a copy of this ExecutableDDLElement with the .target attribute assigned to the given SchemaItem.

See also

DDL - uses tokenization against the “target” when processing the DDL string.

method sqlalchemy.schema.ExecutableDDLElement.execute_if(dialect: str | None = None, callable_: DDLIfCallable | None = None, state: Any | None = None) → Self¶

Return a callable that will execute this ExecutableDDLElement conditionally within an event handler.

Used to provide a wrapper for event listening:

event.listen(
            metadata,
            'before_create',
            DDL("my_ddl").execute_if(dialect='postgresql')
        )

Parameters:

dialect –
May be a string or tuple of strings. 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 three positional arguments as well as optional keyword arguments:

ddl:

This DDL element.

target:

The Table or MetaData 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. May be None if this construct is being created inline within a table, in which case compiler will be present.

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.

dialect:

keyword argument, but always present - the Dialect involved in the operation.

compiler:

keyword argument. Will be None for an engine level DDL invocation, but will refer to a DDLCompiler if this DDL element is being created inline within a table.

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.

See also

SchemaItem.ddl_if()

DDLEvents

Events

class sqlalchemy.schema.DDL¶

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.

Members

__init__()

Class signature

class sqlalchemy.schema.DDL (sqlalchemy.schema.ExecutableDDLElement)

method sqlalchemy.schema.DDL.__init__(statement, context=None)¶

Create a DDL statement.

Parameters:

statement –
A string or unicode string to be executed. Statements will be processed with Python’s string formatting operator using a fixed set of string substitutions, as well as additional substitutions provided by the optional DDL.context parameter.

A literal ‘%’ in a statement must be escaped as ‘%%’.

SQL bind parameters are not available in DDL statements.
context – Optional dictionary, defaults to None. These values will be available for use in string substitutions on the DDL statement.

See also

DDLEvents

Events

class sqlalchemy.schema._CreateDropBase¶

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.

Class signature

class sqlalchemy.schema._CreateDropBase (sqlalchemy.schema.ExecutableDDLElement)

class sqlalchemy.schema.CreateTable¶

Represent a CREATE TABLE statement.

Members

__init__()

Class signature

class sqlalchemy.schema.CreateTable (sqlalchemy.schema._CreateBase)

method sqlalchemy.schema.CreateTable.__init__(element: Table, include_foreign_key_constraints: typing_Sequence[ForeignKeyConstraint] | None = None, if_not_exists: bool = False)¶

Create a CreateTable construct.

Parameters:

element – a Table that’s the subject of the CREATE
on – See the description for ‘on’ in DDL.
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.
if_not_exists –
if True, an IF NOT EXISTS operator will be applied to the construct.

New in version 1.4.0b2.

class sqlalchemy.schema.DropTable¶

Represent a DROP TABLE statement.

Members

__init__()

Class signature

class sqlalchemy.schema.DropTable (sqlalchemy.schema._DropBase)

method sqlalchemy.schema.DropTable.__init__(element: Table, if_exists: bool = False)¶

Create a DropTable construct.

Parameters:

element – a Table that’s the subject of the DROP.
on – See the description for ‘on’ in DDL.
if_exists –
if True, an IF EXISTS operator will be applied to the construct.

New in version 1.4.0b2.

class sqlalchemy.schema.CreateColumn¶

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.

Class signature

class sqlalchemy.schema.CreateColumn (sqlalchemy.schema.BaseDDLElement)

class sqlalchemy.schema.CreateSequence¶: Represent a CREATE SEQUENCE statement.

Class signature

class sqlalchemy.schema.CreateSequence (sqlalchemy.schema._CreateBase)

class sqlalchemy.schema.DropSequence¶: Represent a DROP SEQUENCE statement.

Class signature

class sqlalchemy.schema.DropSequence (sqlalchemy.schema._DropBase)

class sqlalchemy.schema.CreateIndex¶

Represent a CREATE INDEX statement.

Members

__init__()

Class signature

class sqlalchemy.schema.CreateIndex (sqlalchemy.schema._CreateBase)

method sqlalchemy.schema.CreateIndex.__init__(element, if_not_exists=False)¶

Create a Createindex construct.

Parameters:

element – a Index that’s the subject of the CREATE.
if_not_exists –
if True, an IF NOT EXISTS operator will be applied to the construct.

New in version 1.4.0b2.

class sqlalchemy.schema.DropIndex¶

Represent a DROP INDEX statement.

Members

__init__()

Class signature

class sqlalchemy.schema.DropIndex (sqlalchemy.schema._DropBase)

method sqlalchemy.schema.DropIndex.__init__(element, if_exists=False)¶

Create a DropIndex construct.

Parameters:

element – a Index that’s the subject of the DROP.
if_exists –
if True, an IF EXISTS operator will be applied to the construct.

New in version 1.4.0b2.

class sqlalchemy.schema.AddConstraint¶: Represent an ALTER TABLE ADD CONSTRAINT statement.

Class signature

class sqlalchemy.schema.AddConstraint (sqlalchemy.schema._CreateBase)

class sqlalchemy.schema.DropConstraint¶: Represent an ALTER TABLE DROP CONSTRAINT statement.

Class signature

class sqlalchemy.schema.DropConstraint (sqlalchemy.schema._DropBase)

class sqlalchemy.schema.CreateSchema¶

Represent a CREATE SCHEMA statement.

The argument here is the string name of the schema.

Members

__init__()

Class signature

class sqlalchemy.schema.CreateSchema (sqlalchemy.schema._CreateBase)

method sqlalchemy.schema.CreateSchema.__init__(name, if_not_exists=False)¶: Create a new CreateSchema construct.

class sqlalchemy.schema.DropSchema¶

Represent a DROP SCHEMA statement.

The argument here is the string name of the schema.

Members

__init__()

Class signature

class sqlalchemy.schema.DropSchema (sqlalchemy.schema._DropBase)

method sqlalchemy.schema.DropSchema.__init__(name, cascade=False, if_exists=False)¶: Create a new DropSchema construct.

SQLAlchemy 2.0 Documentation

SQLAlchemy 2.0 Documentation

SQLAlchemy Core

Customizing DDL¶

Custom DDL¶

Controlling DDL Sequences¶

Using the built-in DDLElement Classes¶

Controlling DDL Generation of Constraints and Indexes¶

DDL Expression Constructs API¶