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()
 return not bool(row)
defshould_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
 ),
)
users.create(engine)
CREATETABLEusers( user_idSERIALNOTNULL, user_nameVARCHAR(40)NOTNULL, PRIMARYKEY(user_id) ) SELECTconnameFROMpg_constraintWHEREconname='cst_user_name_length' ALTERTABLEusersADDCONSTRAINTcst_user_name_lengthCHECK(length(user_name)>=8)
users.drop(engine)
SELECTconnameFROMpg_constraintWHEREconname='cst_user_name_length' ALTERTABLEusersDROPCONSTRAINTcst_user_name_length DROPTABLEusers

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.schemaimport CreateTable
with engine.connect() as conn:
 conn.execute(CreateTable(mytable))
CREATETABLEmytable( col1INTEGER, col2INTEGER, col3INTEGER, col4INTEGER, col5INTEGER, col6INTEGER )

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

Added 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:

fromsqlalchemyimport CheckConstraint, Index
fromsqlalchemyimport MetaData, Table, Column
fromsqlalchemyimport 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:

>>> fromsqlalchemyimport create_engine
>>> sqlite_engine = create_engine("sqlite+pysqlite://", echo=True)
>>> meta.create_all(sqlite_engine)
BEGIN(implicit) PRAGMAmain.table_info("my_table") [rawsql]() PRAGMAtemp.table_info("my_table") [rawsql]() CREATETABLEmy_table( idINTEGERNOTNULL, numINTEGER, dataVARCHAR, PRIMARYKEY(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:

>>> fromsqlalchemyimport create_engine
>>> postgresql_engine = create_engine(
... "postgresql+psycopg2://scott:tiger@localhost/test", echo=True
... )
>>> meta.create_all(postgresql_engine)
BEGIN(implicit) selectrelnamefrompg_classcjoinpg_namespacenonn.oid=c.relnamespacewherepg_catalog.pg_table_is_visible(c.oid)andrelname=%(name)s [generatedin0.00009s]{'name':'my_table'} CREATETABLEmy_table( idSERIALNOTNULL, numINTEGER, dataVARCHAR, PRIMARYKEY(id), CHECK(num>5) ) [nokey0.00007s]{} CREATEINDEXmy_pg_indexONmy_table(data) [nokey0.00013s]{} 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:

defonly_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),
)

DDL Expression Constructs API

Object Name Description

_CreateDropBase

AddConstraint

BaseDDLElement

CheckFirst

CreateColumn

CreateIndex

CreateSchema

CreateSequence

CreateTable

DDL

DropConstraint

DropIndex

DropSchema

DropSequence

DropTable

ExecutableDDLElement

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.

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()

classsqlalchemy.schema.BaseDDLElement

The root of DDL constructs, including those that are sub-elements within the "create table" and other processes.

Added in version 2.0.

classsqlalchemy.schema.ExecutableDDLElement

inherits from sqlalchemy.sql.roles.DDLRole, sqlalchemy.sql.expression.Executable, sqlalchemy.schema.BaseDDLElement

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"),
)
Member Name Description

__call__()

Execute the DDL as a ddl_listener.

against()

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

execute_if()

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

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

classsqlalchemy.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:

fromsqlalchemyimport 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.

Member Name Description

__init__()

Create a DDL statement.

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

classsqlalchemy.schema.CheckFirst

inherits from enum.Flag

Enumeration for the MetaData.create_all.checkfirst parameter passed to methods like MetaData.create_all(), MetaData.drop_all(), Table.create(), Table.drop() and others.

This enumeration indicates what kinds of objects should be "checked" with a separate query before emitting CREATE or DROP for that object.

Can use CheckFirst(bool_value) to convert from a boolean value.

Added in version 2.1.

Member Name Description

INDEXES

Check for indexes

NONE

No items should be checked

SEQUENCES

Check for sequences

TABLES

Check for tables

TYPES

Check for custom datatypes that are created server-side

attribute sqlalchemy.schema.CheckFirst. INDEXES=4

Check for indexes

attribute sqlalchemy.schema.CheckFirst. NONE=0

No items should be checked

attribute sqlalchemy.schema.CheckFirst. SEQUENCES=8

Check for sequences

attribute sqlalchemy.schema.CheckFirst. TABLES=2

Check for tables

attribute sqlalchemy.schema.CheckFirst. TYPES=16

Check for custom datatypes that are created server-side

This is currently used by PostgreSQL.

classsqlalchemy.schema._CreateDropBase

inherits from sqlalchemy.schema.ExecutableDDLElement, typing.Generic

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.

classsqlalchemy.schema.CreateTable

inherits from sqlalchemy.schema._CreateBase

Represent a CREATE TABLE statement.

Member Name Description

__init__()

Create a CreateTable construct.

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

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.

    Added in version 1.4.0b2.

classsqlalchemy.schema.DropTable

inherits from sqlalchemy.schema._DropBase

Represent a DROP TABLE statement.

Member Name Description

__init__()

Create a DropTable construct.

method sqlalchemy.schema.DropTable. __init__(element:Table , if_exists:bool=False) None

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.

    Added in version 1.4.0b2.

classsqlalchemy.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:

fromsqlalchemyimport schema
fromsqlalchemy.ext.compilerimport compiles
@compiles(schema.CreateColumn)
defcompile(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:

fromsqlalchemyimport Table, Metadata, Column, Integer, String
fromsqlalchemyimport 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:

CREATETABLEmytable(
xSPECIALDIRECTIVEINTEGERNOTNULL,
yVARCHAR(50),
zSPECIALDIRECTIVEVARCHAR(20),
PRIMARYKEY(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:

fromsqlalchemy.schemaimport CreateColumn
@compiles(CreateColumn, "postgresql")
defskip_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.

classsqlalchemy.schema.CreateSequence

inherits from sqlalchemy.schema._CreateBase

Represent a CREATE SEQUENCE statement.

classsqlalchemy.schema.DropSequence

inherits from sqlalchemy.schema._DropBase

Represent a DROP SEQUENCE statement.

classsqlalchemy.schema.CreateIndex

inherits from sqlalchemy.schema._CreateBase

Represent a CREATE INDEX statement.

Member Name Description

__init__()

Create a Createindex construct.

method sqlalchemy.schema.CreateIndex. __init__(element:Index , if_not_exists:bool=False) None

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.

    Added in version 1.4.0b2.

classsqlalchemy.schema.DropIndex

inherits from sqlalchemy.schema._DropBase

Represent a DROP INDEX statement.

Member Name Description

__init__()

Create a DropIndex construct.

method sqlalchemy.schema.DropIndex. __init__(element:Index , if_exists:bool=False) None

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.

    Added in version 1.4.0b2.

classsqlalchemy.schema.AddConstraint

inherits from sqlalchemy.schema._CreateBase

Represent an ALTER TABLE ADD CONSTRAINT statement.

Member Name Description

__init__()

Construct a new AddConstraint construct.

method sqlalchemy.schema.AddConstraint. __init__(element:Constraint , *, isolate_from_table:bool=True) None

Construct a new AddConstraint construct.

Parameters:
  • element – a Constraint object

  • isolate_from_table

    optional boolean, defaults to True. Has the effect of the incoming constraint being isolated from being included in a CREATE TABLE sequence when associated with a Table.

    Added in version 2.0.39: - added AddConstraint.isolate_from_table, defaulting to True. Previously, the behavior of this parameter was implicitly turned on in all cases.

classsqlalchemy.schema.DropConstraint

inherits from sqlalchemy.schema._DropBase

Represent an ALTER TABLE DROP CONSTRAINT statement.

Member Name Description

__init__()

Construct a new DropConstraint construct.

method sqlalchemy.schema.DropConstraint. __init__(element:Constraint , *, cascade:bool=False, if_exists:bool=False, isolate_from_table:bool=True, **kw:Any) None

Construct a new DropConstraint construct.

Parameters:
  • element – a Constraint object

  • cascade – optional boolean, indicates backend-specific "CASCADE CONSTRAINT" directive should be rendered if available

  • if_exists – optional boolean, indicates backend-specific "IF EXISTS" directive should be rendered if available

  • isolate_from_table

    optional boolean, defaults to True. Has the effect of the incoming constraint being isolated from being included in a CREATE TABLE sequence when associated with a Table.

    Added in version 2.0.39: - added DropConstraint.isolate_from_table, defaulting to True. Previously, the behavior of this parameter was implicitly turned on in all cases.

classsqlalchemy.schema.CreateSchema

inherits from sqlalchemy.schema._CreateBase

Represent a CREATE SCHEMA statement.

The argument here is the string name of the schema.

Member Name Description

__init__()

Create a new CreateSchema construct.

method sqlalchemy.schema.CreateSchema. __init__(name:str, if_not_exists:bool=False) None

Create a new CreateSchema construct.

classsqlalchemy.schema.DropSchema

inherits from sqlalchemy.schema._DropBase

Represent a DROP SCHEMA statement.

The argument here is the string name of the schema.

Member Name Description

__init__()

Create a new DropSchema construct.

method sqlalchemy.schema.DropSchema. __init__(name:str, cascade:bool=False, if_exists:bool=False) None

Create a new DropSchema construct.