SQLAlchemy 2.0 Documentation
SQLAlchemy Core
- SQL Statements and Expressions API
- Schema Definition Language
- Describing Databases with MetaData
- Reflecting Database Objects
- Column INSERT/UPDATE Defaults
- Defining Constraints and Indexes
- Customizing DDL¶
- Custom DDL
- Controlling DDL Sequences
- Using the built-in DDLElement Classes
- Controlling DDL Generation of Constraints and Indexes
- DDL Expression Constructs API
- SQL Datatype Objects
- Engine and Connection Use
- Core API Basics
Project Versions
- Previous: Defining Constraints and Indexes
- Next: SQL Datatype Objects
- Up: Home
- On this page:
- Customizing DDL
- Custom DDL
- Controlling DDL Sequences
- Using the built-in DDLElement Classes
- Controlling DDL Generation of Constraints and Indexes
- DDL Expression Constructs API
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:
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
),
)
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:
from sqlalchemy.schema import CreateTable
with engine.connect() as conn:
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:
>>> from sqlalchemy import create_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:
>>> from sqlalchemy import create_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),
)
DDL Expression Constructs API¶
Object Name | Description |
---|---|
Base class for DDL constructs that represent CREATE and DROP or equivalents. |
|
Represent an ALTER TABLE ADD CONSTRAINT statement. |
|
The root of DDL constructs, including those that are sub-elements within the “create table” and other processes. |
|
Represent a |
|
Represent a CREATE INDEX statement. |
|
Represent a CREATE SCHEMA statement. |
|
Represent a CREATE SEQUENCE statement. |
|
Represent a CREATE TABLE statement. |
|
A literal DDL statement. |
|
Represent an ALTER TABLE DROP CONSTRAINT statement. |
|
Represent a DROP INDEX statement. |
|
Represent a DROP SCHEMA statement. |
|
Represent a DROP SEQUENCE statement. |
|
Represent a DROP TABLE statement. |
|
Base class for standalone executable DDL expression constructs. |
|
sort_tables(tables[, skip_fn, extra_dependencies]) |
Sort a collection of |
sort_tables_and_constraints(tables[, filter_fn, extra_dependencies, _warn_for_cycles]) |
Sort a collection of |
- 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 dependentTable
objects. Tables are dependent on another based on the presence ofForeignKeyConstraint
objects as well as explicit dependencies added byTable.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, thesort_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:
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 insort_tables_and_constraints()
, which is instead passed the owningForeignKeyConstraint
object.extra_dependencies¶ – a sequence of 2-tuples of tables which will also be considered as dependent on each other.
- 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 eachTable
follows its dependentTable
objects. RemainingForeignKeyConstraint
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 byTable.add_is_dependent_on()
, as well as dependencies stated here using thesort_tables_and_constraints.skip_fn
and/orsort_tables_and_constraints.extra_dependencies
parameters.- 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.
See also
- 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 asCreateTable
,DropTable
,AddConstraint
, etc.Changed in version 2.0:
ExecutableDDLElement
is renamed fromDDLElement
, 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') )
Members
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 returnedExecutableDDLElement
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 particularTable
.When a
ExecutableDDLElement
object is established as an event handler for theDDLEvents.before_create()
orDDLEvents.after_create()
events, and the event then occurs for a given target such as aConstraint
orTable
, that target is established with a copy of theExecutableDDLElement
object using this method, which then proceeds to theExecutableDDLElement.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 givenSchemaItem
.
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
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. May be None if this construct is being created inline within a table, in which casecompiler
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 aDDLCompiler
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.
-
method
- 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 eitherTable
orMetaData
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
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.
-
method
- 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
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:
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.
-
method
- class sqlalchemy.schema.DropTable¶
Represent a DROP TABLE statement.
Members
Class signature
class
sqlalchemy.schema.DropTable
(sqlalchemy.schema._DropBase
)-
method
sqlalchemy.schema.DropTable.
__init__(element: Table, if_exists: bool = False)¶ Create a
DropTable
construct.
-
method
- class sqlalchemy.schema.CreateColumn¶
Represent a
Column
as rendered in a CREATE TABLE statement, via theCreateTable
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 aCREATE TABLE
. This is accomplished by creating a compilation rule that conditionally returnsNone
. This is essentially how to produce the same effect as using thesystem=True
argument onColumn
, which marks a column as an implicitly-present “system” column.For example, suppose we wish to produce a
Table
which skips rendering of the PostgreSQLxmin
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 aCREATE TABLE
which only includes theid
column in the string; thexmin
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
Class signature
class
sqlalchemy.schema.CreateIndex
(sqlalchemy.schema._CreateBase
)-
method
sqlalchemy.schema.CreateIndex.
__init__(element, if_not_exists=False)¶ Create a
Createindex
construct.
-
method
- class sqlalchemy.schema.DropIndex¶
Represent a DROP INDEX statement.
Members
Class signature
class
sqlalchemy.schema.DropIndex
(sqlalchemy.schema._DropBase
)
- 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
Class signature
class
sqlalchemy.schema.CreateSchema
(sqlalchemy.schema._CreateBase
)-
method
sqlalchemy.schema.CreateSchema.
__init__(name: str, if_not_exists: bool = False)¶ Create a new
CreateSchema
construct.
-
method
- class sqlalchemy.schema.DropSchema¶
Represent a DROP SCHEMA statement.
The argument here is the string name of the schema.
Members
Class signature
class
sqlalchemy.schema.DropSchema
(sqlalchemy.schema._DropBase
)-
method
sqlalchemy.schema.DropSchema.
__init__(name: str, cascade: bool = False, if_exists: bool = False)¶ Create a new
DropSchema
construct.
-
method
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