Class Mapping API¶
Object Name | Description |
---|---|
add_mapped_attribute(target, key, attr) |
Add a new mapped attribute to an ORM mapped class. |
as_declarative(**kw) |
Class decorator which will adapt a given class into a
|
class_mapper(class_[, configure]) |
Given a class, return the primary |
Remove all mappers from all classes. |
|
column_property(column, *additional_columns, [group, deferred, raiseload, comparator_factory, init, repr, default, default_factory, compare, kw_only, active_history, expire_on_flush, info, doc]) |
Provide a column-level property for use with a mapping. |
Initialize the inter-mapper relationships of all mappers that
have been constructed thus far across all |
|
declarative_base(*, [metadata, mapper, cls, name, class_registry, type_annotation_map, constructor, metaclass]) |
Construct a base class for declarative class definitions. |
declarative_mixin(cls) |
Mark a class as providing the feature of “declarative mixin”. |
Base class used for declarative class definitions. |
|
Same as |
|
Mark a class-level method as representing the definition of a mapped property or Declarative directive. |
|
has_inherited_table(cls) |
Given a class, return True if any of the classes it inherits from has a mapped table, otherwise return False. |
identity_key([class_, ident], *, [instance, row, identity_token]) |
Generate “identity key” tuples, as are used as keys in the
|
mapped_column([__name_pos, __type_pos], *args, [init, repr, default, default_factory, compare, kw_only, nullable, primary_key, deferred, deferred_group, deferred_raiseload, use_existing_column, name, type_, autoincrement, doc, key, index, unique, info, onupdate, insert_default, server_default, server_onupdate, active_history, quote, system, comment, sort_order], **kw) |
declare a new ORM-mapped |
Mixin class to indicate when mapping this class, also convert it to be a dataclass. |
|
A protocol representing a SQLAlchemy mapped class. |
|
Defines an association between a Python class and a database table or other relational structure, so that ORM operations against the class may proceed. |
|
object_mapper(instance) |
Given an object, return the primary Mapper associated with the object instance. |
orm_insert_sentinel([name, type_], *, [default, omit_from_statements]) |
Provides a surrogate |
polymorphic_union(table_map, typecolname[, aliasname, cast_nulls]) |
Create a |
reconstructor(fn) |
Decorate a method as the ‘reconstructor’ hook. |
Generalized registry for mapping classes. |
|
synonym_for(name[, map_column]) |
Decorator that produces an |
- class sqlalchemy.orm.registry¶
Generalized registry for mapping classes.
The
registry
serves as the basis for maintaining a collection of mappings, and provides configurational hooks used to map classes.The three general kinds of mappings supported are Declarative Base, Declarative Decorator, and Imperative Mapping. All of these mapping styles may be used interchangeably:
registry.generate_base()
returns a new declarative base class, and is the underlying implementation of thedeclarative_base()
function.registry.mapped()
provides a class decorator that will apply declarative mapping to a class without the use of a declarative base class.registry.map_imperatively()
will produce aMapper
for a class without scanning the class for declarative class attributes. This method suits the use case historically provided by thesqlalchemy.orm.mapper()
classical mapping function, which is removed as of SQLAlchemy 2.0.
New in version 1.4.
Members
__init__(), as_declarative_base(), configure(), dispose(), generate_base(), map_declaratively(), map_imperatively(), mapped(), mapped_as_dataclass(), mappers, update_type_annotation_map()
See also
ORM Mapped Class Overview - overview of class mapping styles.
-
method
sqlalchemy.orm.registry.
__init__(*, metadata: Optional[MetaData] = None, class_registry: Optional[clsregistry._ClsRegistryType] = None, type_annotation_map: Optional[_TypeAnnotationMapType] = None, constructor: Callable[..., None] = <function _declarative_constructor>)¶ Construct a new
registry
- Parameters:
metadata – An optional
MetaData
instance. AllTable
objects generated using declarative table mapping will make use of thisMetaData
collection. If this argument is left at its default ofNone
, a blankMetaData
collection is created.constructor – Specify the implementation for the
__init__
function on a mapped class that has no__init__
of its own. Defaults to an implementation that assigns **kwargs for declared fields and relationships to an instance. IfNone
is supplied, no __init__ will be provided and construction will fall back to cls.__init__ by way of the normal Python semantics.class_registry – optional dictionary that will serve as the registry of class names-> mapped classes when string names are used to identify classes inside of
relationship()
and others. Allows two or more declarative base classes to share the same registry of class names for simplified inter-base relationships.type_annotation_map –
optional dictionary of Python types to SQLAlchemy
TypeEngine
classes or instances. The provided dict will update the default type mapping. This is used exclusively by theMappedColumn
construct to produce column types based on annotations within theMapped
type.New in version 2.0.
See also
-
method
sqlalchemy.orm.registry.
as_declarative_base(**kw: Any) Callable[[Type[_T]], Type[_T]] ¶ Class decorator which will invoke
registry.generate_base()
for a given base class.E.g.:
from sqlalchemy.orm import registry mapper_registry = registry() @mapper_registry.as_declarative_base() class Base: @declared_attr def __tablename__(cls): return cls.__name__.lower() id = Column(Integer, primary_key=True) class MyMappedClass(Base): # ...
All keyword arguments passed to
registry.as_declarative_base()
are passed along toregistry.generate_base()
.
-
method
sqlalchemy.orm.registry.
configure(cascade: bool = False) None ¶ Configure all as-yet unconfigured mappers in this
registry
.The configure step is used to reconcile and initialize the
relationship()
linkages between mapped classes, as well as to invoke configuration events such as theMapperEvents.before_configured()
andMapperEvents.after_configured()
, which may be used by ORM extensions or user-defined extension hooks.If one or more mappers in this registry contain
relationship()
constructs that refer to mapped classes in other registries, this registry is said to be dependent on those registries. In order to configure those dependent registries automatically, theconfigure.cascade
flag should be set toTrue
. Otherwise, if they are not configured, an exception will be raised. The rationale behind this behavior is to allow an application to programmatically invoke configuration of registries while controlling whether or not the process implicitly reaches other registries.As an alternative to invoking
registry.configure()
, the ORM functionconfigure_mappers()
function may be used to ensure configuration is complete for allregistry
objects in memory. This is generally simpler to use and also predates the usage ofregistry
objects overall. However, this function will impact all mappings throughout the running Python process and may be more memory/time consuming for an application that has many registries in use for different purposes that may not be needed immediately.See also
New in version 1.4.0b2.
-
method
sqlalchemy.orm.registry.
dispose(cascade: bool = False) None ¶ Dispose of all mappers in this
registry
.After invocation, all the classes that were mapped within this registry will no longer have class instrumentation associated with them. This method is the per-
registry
analogue to the application-wideclear_mappers()
function.If this registry contains mappers that are dependencies of other registries, typically via
relationship()
links, then those registries must be disposed as well. When such registries exist in relation to this one, theirregistry.dispose()
method will also be called, if thedispose.cascade
flag is set toTrue
; otherwise, an error is raised if those registries were not already disposed.New in version 1.4.0b2.
See also
-
method
sqlalchemy.orm.registry.
generate_base(mapper: ~typing.Optional[~typing.Callable[[...], ~sqlalchemy.orm.mapper.Mapper[~typing.Any]]] = None, cls: ~typing.Type[~typing.Any] = <class 'object'>, name: str = 'Base', metaclass: ~typing.Type[~typing.Any] = <class 'sqlalchemy.orm.decl_api.DeclarativeMeta'>) Any ¶ Generate a declarative base class.
Classes that inherit from the returned class object will be automatically mapped using declarative mapping.
E.g.:
from sqlalchemy.orm import registry mapper_registry = registry() Base = mapper_registry.generate_base() class MyClass(Base): __tablename__ = "my_table" id = Column(Integer, primary_key=True)
The above dynamically generated class is equivalent to the non-dynamic example below:
from sqlalchemy.orm import registry from sqlalchemy.orm.decl_api import DeclarativeMeta mapper_registry = registry() class Base(metaclass=DeclarativeMeta): __abstract__ = True registry = mapper_registry metadata = mapper_registry.metadata __init__ = mapper_registry.constructor
Changed in version 2.0: Note that the
registry.generate_base()
method is superseded by the newDeclarativeBase
class, which generates a new “base” class using subclassing, rather than return value of a function. This allows an approach that is compatible with PEP 484 typing tools.The
registry.generate_base()
method provides the implementation for thedeclarative_base()
function, which creates theregistry
and base class all at once.See the section Declarative Mapping for background and examples.
- Parameters:
mapper – An optional callable, defaults to
Mapper
. This function is used to generate newMapper
objects.cls – Defaults to
object
. A type to use as the base for the generated declarative base class. May be a class or tuple of classes.name – Defaults to
Base
. The display name for the generated class. Customizing this is not required, but can improve clarity in tracebacks and debugging.metaclass – Defaults to
DeclarativeMeta
. A metaclass or __metaclass__ compatible callable to use as the meta type of the generated declarative base class.
-
method
sqlalchemy.orm.registry.
map_declaratively(cls: Type[_O]) Mapper[_O] ¶ Map a class declaratively.
In this form of mapping, the class is scanned for mapping information, including for columns to be associated with a table, and/or an actual table object.
Returns the
Mapper
object.E.g.:
from sqlalchemy.orm import registry mapper_registry = registry() class Foo: __tablename__ = 'some_table' id = Column(Integer, primary_key=True) name = Column(String) mapper = mapper_registry.map_declaratively(Foo)
This function is more conveniently invoked indirectly via either the
registry.mapped()
class decorator or by subclassing a declarative metaclass generated fromregistry.generate_base()
.See the section Declarative Mapping for complete details and examples.
- Parameters:
cls – class to be mapped.
- Returns:
a
Mapper
object.
See also
registry.mapped()
- more common decorator interface to this function.
-
method
sqlalchemy.orm.registry.
map_imperatively(class_: Type[_O], local_table: Optional[FromClause] = None, **kw: Any) Mapper[_O] ¶ Map a class imperatively.
In this form of mapping, the class is not scanned for any mapping information. Instead, all mapping constructs are passed as arguments.
This method is intended to be fully equivalent to the now-removed SQLAlchemy
mapper()
function, except that it’s in terms of a particular registry.E.g.:
from sqlalchemy.orm import registry mapper_registry = registry() my_table = Table( "my_table", mapper_registry.metadata, Column('id', Integer, primary_key=True) ) class MyClass: pass mapper_registry.map_imperatively(MyClass, my_table)
See the section Imperative Mapping for complete background and usage examples.
- Parameters:
class_ – The class to be mapped. Corresponds to the
Mapper.class_
parameter.local_table – the
Table
or otherFromClause
object that is the subject of the mapping. Corresponds to theMapper.local_table
parameter.**kw – all other keyword arguments are passed to the
Mapper
constructor directly.
-
method
sqlalchemy.orm.registry.
mapped(cls: Type[_O]) Type[_O] ¶ Class decorator that will apply the Declarative mapping process to a given class.
E.g.:
from sqlalchemy.orm import registry mapper_registry = registry() @mapper_registry.mapped class Foo: __tablename__ = 'some_table' id = Column(Integer, primary_key=True) name = Column(String)
See the section Declarative Mapping for complete details and examples.
- Parameters:
cls – class to be mapped.
- Returns:
the class that was passed.
See also
registry.generate_base()
- generates a base class that will apply Declarative mapping to subclasses automatically using a Python metaclass.See also
-
method
sqlalchemy.orm.registry.
mapped_as_dataclass(_registry__cls: Optional[Type[_O]] = None, *, init: Union[_NoArg, bool] = _NoArg.NO_ARG, repr: Union[_NoArg, bool] = _NoArg.NO_ARG, eq: Union[_NoArg, bool] = _NoArg.NO_ARG, order: Union[_NoArg, bool] = _NoArg.NO_ARG, unsafe_hash: Union[_NoArg, bool] = _NoArg.NO_ARG, match_args: Union[_NoArg, bool] = _NoArg.NO_ARG, kw_only: Union[_NoArg, bool] = _NoArg.NO_ARG, dataclass_callable: Union[_NoArg, Callable[..., Type[Any]]] = _NoArg.NO_ARG) Union[Type[_O], Callable[[Type[_O]], Type[_O]]] ¶ Class decorator that will apply the Declarative mapping process to a given class, and additionally convert the class to be a Python dataclass.
See also
Declarative Dataclass Mapping - complete background on SQLAlchemy native dataclass mapping
New in version 2.0.
-
attribute
sqlalchemy.orm.registry.
mappers¶ read only collection of all
Mapper
objects.
-
method
sqlalchemy.orm.registry.
update_type_annotation_map(type_annotation_map: _TypeAnnotationMapType) None ¶ update the
registry.type_annotation_map
with new values.
- function sqlalchemy.orm.add_mapped_attribute(target: Type[_O], key: str, attr: MapperProperty[Any]) None ¶
Add a new mapped attribute to an ORM mapped class.
E.g.:
add_mapped_attribute(User, "addresses", relationship(Address))
This may be used for ORM mappings that aren’t using a declarative metaclass that intercepts attribute set operations.
New in version 2.0.
- function sqlalchemy.orm.column_property(column: _ORMColumnExprArgument[_T], *additional_columns: _ORMColumnExprArgument[Any], group: Optional[str] = None, deferred: bool = False, raiseload: bool = False, comparator_factory: Optional[Type[PropComparator[_T]]] = None, init: Union[_NoArg, bool] = _NoArg.NO_ARG, repr: Union[_NoArg, bool] = _NoArg.NO_ARG, default: Optional[Any] = _NoArg.NO_ARG, default_factory: Union[_NoArg, Callable[[], _T]] = _NoArg.NO_ARG, compare: Union[_NoArg, bool] = _NoArg.NO_ARG, kw_only: Union[_NoArg, bool] = _NoArg.NO_ARG, active_history: bool = False, expire_on_flush: bool = True, info: Optional[_InfoType] = None, doc: Optional[str] = None) MappedSQLExpression[_T] ¶
Provide a column-level property for use with a mapping.
With Declarative mappings,
column_property()
is used to map read-only SQL expressions to a mapped class.When using Imperative mappings,
column_property()
also takes on the role of mapping table columns with additional features. When using fully Declarative mappings, themapped_column()
construct should be used for this purpose.With Declarative Dataclass mappings,
column_property()
is considered to be read only, and will not be included in the Dataclass__init__()
constructor.The
column_property()
function returns an instance ofColumnProperty
.See also
Using column_property - general use of
column_property()
to map SQL expressionsApplying Load, Persistence and Mapping Options for Imperative Table Columns - usage of
column_property()
with Imperative Table mappings to apply additional options to a plainColumn
object- Parameters:
*cols – list of Column objects to be mapped.
active_history=False – Used only for Imperative Table mappings, or legacy-style Declarative mappings (i.e. which have not been upgraded to
mapped_column()
), for column-based attributes that are expected to be writeable; usemapped_column()
withmapped_column.active_history
for Declarative mappings. See that parameter for functional details.comparator_factory – a class which extends
Comparator
which provides custom SQL clause generation for comparison operations.group – a group name for this property when marked as deferred.
deferred – when True, the column property is “deferred”, meaning that it does not load immediately, and is instead loaded when the attribute is first accessed on an instance. See also
deferred()
.doc – optional string that will be applied as the doc on the class-bound descriptor.
expire_on_flush=True – Disable expiry on flush. A column_property() which refers to a SQL expression (and not a single table-bound column) is considered to be a “read only” property; populating it has no effect on the state of data, and it can only return database state. For this reason a column_property()’s value is expired whenever the parent object is involved in a flush, that is, has any kind of “dirty” state within a flush. Setting this parameter to
False
will have the effect of leaving any existing value present after the flush proceeds. Note that theSession
with default expiration settings still expires all attributes after aSession.commit()
call, however.info – Optional data dictionary which will be populated into the
MapperProperty.info
attribute of this object.raiseload –
if True, indicates the column should raise an error when undeferred, rather than loading the value. This can be altered at query time by using the
deferred()
option with raiseload=False.New in version 1.4.
init –
Deprecated since version 1.4: The
column_property.init
parameter is deprecated forcolumn_property()
. This parameter applies to a writeable-attribute in a Declarative Dataclasses configuration only, andcolumn_property()
is treated as a read-only attribute in this context.default –
Deprecated since version 1.4: The
column_property.default
parameter is deprecated forcolumn_property()
. This parameter applies to a writeable-attribute in a Declarative Dataclasses configuration only, andcolumn_property()
is treated as a read-only attribute in this context.default_factory –
Deprecated since version 1.4: The
column_property.default_factory
parameter is deprecated forcolumn_property()
. This parameter applies to a writeable-attribute in a Declarative Dataclasses configuration only, andcolumn_property()
is treated as a read-only attribute in this context.kw_only –
Deprecated since version 1.4: The
column_property.kw_only
parameter is deprecated forcolumn_property()
. This parameter applies to a writeable-attribute in a Declarative Dataclasses configuration only, andcolumn_property()
is treated as a read-only attribute in this context.
- function sqlalchemy.orm.declarative_base(*, metadata: Optional[MetaData] = None, mapper: Optional[Callable[..., Mapper[Any]]] = None, cls: Type[Any] = <class 'object'>, name: str = 'Base', class_registry: Optional[clsregistry._ClsRegistryType] = None, type_annotation_map: Optional[_TypeAnnotationMapType] = None, constructor: Callable[..., None] = <function _declarative_constructor>, metaclass: Type[Any] = <class 'sqlalchemy.orm.decl_api.DeclarativeMeta'>) Any ¶
Construct a base class for declarative class definitions.
The new base class will be given a metaclass that produces appropriate
Table
objects and makes the appropriateMapper
calls based on the information provided declaratively in the class and any subclasses of the class.Changed in version 2.0: Note that the
declarative_base()
function is superseded by the newDeclarativeBase
class, which generates a new “base” class using subclassing, rather than return value of a function. This allows an approach that is compatible with PEP 484 typing tools.The
declarative_base()
function is a shorthand version of using theregistry.generate_base()
method. That is, the following:from sqlalchemy.orm import declarative_base Base = declarative_base()
Is equivalent to:
from sqlalchemy.orm import registry mapper_registry = registry() Base = mapper_registry.generate_base()
See the docstring for
registry
andregistry.generate_base()
for more details.Changed in version 1.4: The
declarative_base()
function is now a specialization of the more genericregistry
class. The function also moves to thesqlalchemy.orm
package from thedeclarative.ext
package.- Parameters:
metadata – An optional
MetaData
instance. AllTable
objects implicitly declared by subclasses of the base will share this MetaData. A MetaData instance will be created if none is provided. TheMetaData
instance will be available via themetadata
attribute of the generated declarative base class.mapper – An optional callable, defaults to
Mapper
. Will be used to map subclasses to their Tables.cls – Defaults to
object
. A type to use as the base for the generated declarative base class. May be a class or tuple of classes.name – Defaults to
Base
. The display name for the generated class. Customizing this is not required, but can improve clarity in tracebacks and debugging.constructor – Specify the implementation for the
__init__
function on a mapped class that has no__init__
of its own. Defaults to an implementation that assigns **kwargs for declared fields and relationships to an instance. IfNone
is supplied, no __init__ will be provided and construction will fall back to cls.__init__ by way of the normal Python semantics.class_registry – optional dictionary that will serve as the registry of class names-> mapped classes when string names are used to identify classes inside of
relationship()
and others. Allows two or more declarative base classes to share the same registry of class names for simplified inter-base relationships.type_annotation_map –
optional dictionary of Python types to SQLAlchemy
TypeEngine
classes or instances. This is used exclusively by theMappedColumn
construct to produce column types based on annotations within theMapped
type.New in version 2.0.
See also
metaclass – Defaults to
DeclarativeMeta
. A metaclass or __metaclass__ compatible callable to use as the meta type of the generated declarative base class.
See also
- function sqlalchemy.orm.declarative_mixin(cls: Type[_T]) Type[_T] ¶
Mark a class as providing the feature of “declarative mixin”.
E.g.:
from sqlalchemy.orm import declared_attr from sqlalchemy.orm import declarative_mixin @declarative_mixin class MyMixin: @declared_attr def __tablename__(cls): return cls.__name__.lower() __table_args__ = {'mysql_engine': 'InnoDB'} __mapper_args__= {'always_refresh': True} id = Column(Integer, primary_key=True) class MyModel(MyMixin, Base): name = Column(String(1000))
The
declarative_mixin()
decorator currently does not modify the given class in any way; it’s current purpose is strictly to assist the Mypy plugin in being able to identify SQLAlchemy declarative mixin classes when no other context is present.New in version 1.4.6.
- function sqlalchemy.orm.as_declarative(**kw: Any) Callable[[Type[_T]], Type[_T]] ¶
Class decorator which will adapt a given class into a
declarative_base()
.This function makes use of the
registry.as_declarative_base()
method, by first creating aregistry
automatically and then invoking the decorator.E.g.:
from sqlalchemy.orm import as_declarative @as_declarative() class Base: @declared_attr def __tablename__(cls): return cls.__name__.lower() id = Column(Integer, primary_key=True) class MyMappedClass(Base): # ...
See also
- function sqlalchemy.orm.mapped_column(__name_pos: Optional[Union[str, _TypeEngineArgument[Any], SchemaEventTarget]] = None, __type_pos: Optional[Union[_TypeEngineArgument[Any], SchemaEventTarget]] = None, *args: SchemaEventTarget, init: Union[_NoArg, bool] = _NoArg.NO_ARG, repr: Union[_NoArg, bool] = _NoArg.NO_ARG, default: Optional[Any] = _NoArg.NO_ARG, default_factory: Union[_NoArg, Callable[[], _T]] = _NoArg.NO_ARG, compare: Union[_NoArg, bool] = _NoArg.NO_ARG, kw_only: Union[_NoArg, bool] = _NoArg.NO_ARG, nullable: Optional[Union[bool, Literal[SchemaConst.NULL_UNSPECIFIED]]] = SchemaConst.NULL_UNSPECIFIED, primary_key: Optional[bool] = False, deferred: Union[_NoArg, bool] = _NoArg.NO_ARG, deferred_group: Optional[str] = None, deferred_raiseload: bool = False, use_existing_column: bool = False, name: Optional[str] = None, type_: Optional[_TypeEngineArgument[Any]] = None, autoincrement: _AutoIncrementType = 'auto', doc: Optional[str] = None, key: Optional[str] = None, index: Optional[bool] = None, unique: Optional[bool] = None, info: Optional[_InfoType] = None, onupdate: Optional[Any] = None, insert_default: Optional[Any] = _NoArg.NO_ARG, server_default: Optional[_ServerDefaultArgument] = None, server_onupdate: Optional[FetchedValue] = None, active_history: bool = False, quote: Optional[bool] = None, system: bool = False, comment: Optional[str] = None, sort_order: int = 0, **kw: Any) MappedColumn[Any] ¶
declare a new ORM-mapped
Column
construct for use within Declarative Table configuration.The
mapped_column()
function provides an ORM-aware and Python-typing-compatible construct which is used with declarative mappings to indicate an attribute that’s mapped to a CoreColumn
object. It provides the equivalent feature as mapping an attribute to aColumn
object directly when using Declarative, specifically when using Declarative Table configuration.New in version 2.0.
mapped_column()
is normally used with explicit typing along with theMapped
annotation type, where it can derive the SQL type and nullability for the column based on what’s present within theMapped
annotation. It also may be used without annotations as a drop-in replacement for howColumn
is used in Declarative mappings in SQLAlchemy 1.x style.For usage examples of
mapped_column()
, see the documentation at Declarative Table with mapped_column().See also
Declarative Table with mapped_column() - complete documentation
ORM Declarative Models - migration notes for Declarative mappings using 1.x style mappings
- Parameters:
__name – String name to give to the
Column
. This is an optional, positional only argument that if present must be the first positional argument passed. If omitted, the attribute name to which themapped_column()
is mapped will be used as the SQL column name.__type –
TypeEngine
type or instance which will indicate the datatype to be associated with theColumn
. This is an optional, positional-only argument that if present must immediately follow the__name
parameter if present also, or otherwise be the first positional parameter. If omitted, the ultimate type for the column may be derived either from the annotated type, or if aForeignKey
is present, from the datatype of the referenced column.*args – Additional positional arguments include constructs such as
ForeignKey
,CheckConstraint
, andIdentity
, which are passed through to the constructedColumn
.nullable – Optional bool, whether the column should be “NULL” or “NOT NULL”. If omitted, the nullability is derived from the type annotation based on whether or not
typing.Optional
is present.nullable
defaults toTrue
otherwise for non-primary key columns, andFalse
for primary key columns.primary_key – optional bool, indicates the
Column
would be part of the table’s primary key or not.deferred –
Optional bool - this keyword argument is consumed by the ORM declarative process, and is not part of the
Column
itself; instead, it indicates that this column should be “deferred” for loading as though mapped bydeferred()
.deferred_group –
Implies
mapped_column.deferred
toTrue
, and set thedeferred.group
parameter.See also
deferred_raiseload –
Implies
mapped_column.deferred
toTrue
, and set thedeferred.raiseload
parameter.use_existing_column –
if True, will attempt to locate the given column name on an inherited superclass (typically single inheriting superclass), and if present, will not produce a new column, mapping to the superclass column as though it were omitted from this class. This is used for mixins that add new columns to an inherited superclass.
New in version 2.0.0b4.
default –
Passed directly to the
Column.default
parameter if themapped_column.insert_default
parameter is not present. Additionally, when used with Declarative Dataclass Mapping, indicates a default Python value that should be applied to the keyword constructor within the generated__init__()
method.Note that in the case of dataclass generation when
mapped_column.insert_default
is not present, this means themapped_column.default
value is used in two places, both the__init__()
method as well as theColumn.default
parameter. While this behavior may change in a future release, for the moment this tends to “work out”; a default ofNone
will mean that theColumn
gets no default generator, whereas a default that refers to a non-None
Python or SQL expression value will be assigned up front on the object when__init__()
is called, which is the same value that the CoreInsert
construct would use in any case, leading to the same end result.insert_default – Passed directly to the
Column.default
parameter; will supersede the value ofmapped_column.default
when present, howevermapped_column.default
will always apply to the constructor default for a dataclasses mapping.sort_order –
An integer that indicates how this mapped column should be sorted compared to the others when the ORM is creating a
Table
. Among mapped columns that have the same value the default ordering is used, placing first the mapped columns defined in the main class, then the ones in the super classes. Defaults to 0. The sort is ascending.New in version 2.0.4.
active_history=False –
When
True
, indicates that the “previous” value for a scalar attribute should be loaded when replaced, if not already loaded. Normally, history tracking logic for simple non-primary-key scalar values only needs to be aware of the “new” value in order to perform a flush. This flag is available for applications that make use ofget_history()
orSession.is_modified()
which also need to know the “previous” value of the attribute.New in version 2.0.10.
init – Specific to Declarative Dataclass Mapping, specifies if the mapped attribute should be part of the
__init__()
method as generated by the dataclass process.repr – Specific to Declarative Dataclass Mapping, specifies if the mapped attribute should be part of the
__repr__()
method as generated by the dataclass process.default_factory – Specific to Declarative Dataclass Mapping, specifies a default-value generation function that will take place as part of the
__init__()
method as generated by the dataclass process.compare –
Specific to Declarative Dataclass Mapping, indicates if this field should be included in comparison operations when generating the
__eq__()
and__ne__()
methods for the mapped class.New in version 2.0.0b4.
kw_only – Specific to Declarative Dataclass Mapping, indicates if this field should be marked as keyword-only when generating the
__init__()
.**kw – All remaining keyword arguments are passed through to the constructor for the
Column
.
- class sqlalchemy.orm.declared_attr¶
Mark a class-level method as representing the definition of a mapped property or Declarative directive.
declared_attr
is typically applied as a decorator to a class level method, turning the attribute into a scalar-like property that can be invoked from the uninstantiated class. The Declarative mapping process looks for thesedeclared_attr
callables as it scans classes, and assumes any attribute marked withdeclared_attr
will be a callable that will produce an object specific to the Declarative mapping or table configuration.declared_attr
is usually applicable to mixins, to define relationships that are to be applied to different implementors of the class. It may also be used to define dynamically generated column expressions and other Declarative attributes.Example:
class ProvidesUserMixin: "A mixin that adds a 'user' relationship to classes." user_id: Mapped[int] = mapped_column(ForeignKey("user_table.id")) @declared_attr def user(cls) -> Mapped["User"]: return relationship("User")
When used with Declarative directives such as
__tablename__
, thedeclared_attr.directive()
modifier may be used which indicates to PEP 484 typing tools that the given method is not dealing withMapped
attributes:class CreateTableName: @declared_attr.directive def __tablename__(cls) -> str: return cls.__name__.lower()
declared_attr
can also be applied directly to mapped classes, to allow for attributes that dynamically configure themselves on subclasses when using mapped inheritance schemes. Below illustratesdeclared_attr
to create a dynamic scheme for generating theMapper.polymorphic_identity
parameter for subclasses:class Employee(Base): __tablename__ = 'employee' id: Mapped[int] = mapped_column(primary_key=True) type: Mapped[str] = mapped_column(String(50)) @declared_attr.directive def __mapper_args__(cls) -> Dict[str, Any]: if cls.__name__ == 'Employee': return { "polymorphic_on":cls.type, "polymorphic_identity":"Employee" } else: return {"polymorphic_identity":cls.__name__} class Engineer(Employee): pass
declared_attr
supports decorating functions that are explicitly decorated with@classmethod
. This is never necessary from a runtime perspective, however may be needed in order to support PEP 484 typing tools that don’t otherwise recognize the decorated function as having class-level behaviors for thecls
parameter:class SomethingMixin: x: Mapped[int] y: Mapped[int] @declared_attr @classmethod def x_plus_y(cls) -> Mapped[int]: return column_property(cls.x + cls.y)
New in version 2.0: -
declared_attr
can accommodate a function decorated with@classmethod
to help with PEP 484 integration where needed.See also
Composing Mapped Hierarchies with Mixins - Declarative Mixin documentation with background on use patterns for
declared_attr
.Class signature
class
sqlalchemy.orm.declared_attr
(sqlalchemy.orm.base._MappedAttribute
,sqlalchemy.orm.decl_api._declared_attr_common
)-
attribute
sqlalchemy.orm.declared_attr.
cascading¶ Mark a
declared_attr
as cascading.This is a special-use modifier which indicates that a column or MapperProperty-based declared attribute should be configured distinctly per mapped subclass, within a mapped-inheritance scenario.
Warning
The
declared_attr.cascading
modifier has several limitations:The flag only applies to the use of
declared_attr
on declarative mixin classes and__abstract__
classes; it currently has no effect when used on a mapped class directly.The flag only applies to normally-named attributes, e.g. not any special underscore attributes such as
__tablename__
. On these attributes it has no effect.The flag currently does not allow further overrides down the class hierarchy; if a subclass tries to override the attribute, a warning is emitted and the overridden attribute is skipped. This is a limitation that it is hoped will be resolved at some point.
Below, both MyClass as well as MySubClass will have a distinct
id
Column object established:class HasIdMixin: @declared_attr.cascading def id(cls): if has_inherited_table(cls): return Column(ForeignKey("myclass.id"), primary_key=True) else: return Column(Integer, primary_key=True) class MyClass(HasIdMixin, Base): __tablename__ = "myclass" # ... class MySubClass(MyClass): """ """ # ...
The behavior of the above configuration is that
MySubClass
will refer to both its ownid
column as well as that ofMyClass
underneath the attribute namedsome_id
.
-
attribute
sqlalchemy.orm.declared_attr.
directive¶ Mark a
declared_attr
as decorating a Declarative directive such as__tablename__
or__mapper_args__
.The purpose of
declared_attr.directive
is strictly to support PEP 484 typing tools, by allowing the decorated function to have a return type that is not using theMapped
generic class, as would normally be the case whendeclared_attr
is used for columns and mapped properties. At runtime, thedeclared_attr.directive
returns thedeclared_attr
class unmodified.E.g.:
class CreateTableName: @declared_attr.directive def __tablename__(cls) -> str: return cls.__name__.lower()
New in version 2.0.
-
attribute
- class sqlalchemy.orm.DeclarativeBase¶
Base class used for declarative class definitions.
The
DeclarativeBase
allows for the creation of new declarative bases in such a way that is compatible with type checkers:from sqlalchemy.orm import DeclarativeBase class Base(DeclarativeBase): pass
The above
Base
class is now usable as the base for new declarative mappings. The superclass makes use of the__init_subclass__()
method to set up new classes and metaclasses aren’t used.When first used, the
DeclarativeBase
class instantiates a newregistry
to be used with the base, assuming one was not provided explicitly. TheDeclarativeBase
class supports class-level attributes which act as parameters for the construction of this registry; such as to indicate a specificMetaData
collection as well as a specific value forregistry.type_annotation_map
:from typing_extensions import Annotated from sqlalchemy import BigInteger from sqlalchemy import MetaData from sqlalchemy import String from sqlalchemy.orm import DeclarativeBase bigint = Annotated[int, "bigint"] my_metadata = MetaData() class Base(DeclarativeBase): metadata = my_metadata type_annotation_map = { str: String().with_variant(String(255), "mysql", "mariadb"), bigint: BigInteger() }
Class-level attributes which may be specified include:
- Parameters:
metadata – optional
MetaData
collection. If aregistry
is constructed automatically, thisMetaData
collection will be used to construct it. Otherwise, the localMetaData
collection will supercede that used by an existingregistry
passed using theDeclarativeBase.registry
parameter.type_annotation_map – optional type annotation map that will be passed to the
registry
asregistry.type_annotation_map
.registry – supply a pre-existing
registry
directly.
New in version 2.0: Added
DeclarativeBase
, so that declarative base classes may be constructed in such a way that is also recognized by PEP 484 type checkers. As a result,DeclarativeBase
and other subclassing-oriented APIs should be seen as superseding previous “class returned by a function” APIs, namelydeclarative_base()
andregistry.generate_base()
, where the base class returned cannot be recognized by type checkers without using plugins.__init__ behavior
In a plain Python class, the base-most
__init__()
method in the class hierarchy isobject.__init__()
, which accepts no arguments. However, when theDeclarativeBase
subclass is first declared, the class is given an__init__()
method that links to theregistry.constructor
constructor function, if no__init__()
method is already present; this is the usual declarative constructor that will assign keyword arguments as attributes on the instance, assuming those attributes are established at the class level (i.e. are mapped, or are linked to a descriptor). This constructor is never accessed by a mapped class without being called explicitly via super(), as mapped classes are themselves given an__init__()
method directly which callsregistry.constructor
, so in the default case works independently of what the base-most__init__()
method does.Changed in version 2.0.1:
DeclarativeBase
has a default constructor that links toregistry.constructor
by default, so that calls tosuper().__init__()
can access this constructor. Previously, due to an implementation mistake, this default constructor was missing, and callingsuper().__init__()
would invokeobject.__init__()
.The
DeclarativeBase
subclass may also declare an explicit__init__()
method which will replace the use of theregistry.constructor
function at this level:class Base(DeclarativeBase): def __init__(self, id=None): self.id = id
Mapped classes still will not invoke this constructor implicitly; it remains only accessible by calling
super().__init__()
:class MyClass(Base): def __init__(self, id=None, name=None): self.name = name super().__init__(id=id)
Note that this is a different behavior from what functions like the legacy
declarative_base()
would do; the base created by those functions would always installregistry.constructor
for__init__()
.Members
__mapper__, __mapper_args__, __table__, __table_args__, __tablename__, metadata, registry
Class signature
class
sqlalchemy.orm.DeclarativeBase
(sqlalchemy.inspection.Inspectable
)-
attribute
sqlalchemy.orm.DeclarativeBase.
__mapper__: ClassVar[Mapper[Any]]¶ The
Mapper
object to which a particular class is mapped.May also be acquired using
inspect()
, e.g.inspect(klass)
.
-
attribute
sqlalchemy.orm.DeclarativeBase.
__mapper_args__: Any¶ Dictionary of arguments which will be passed to the
Mapper
constructor.
-
attribute
sqlalchemy.orm.DeclarativeBase.
__table__: ClassVar[FromClause]¶ The
FromClause
to which a particular subclass is mapped.This is usually an instance of
Table
but may also refer to other kinds ofFromClause
such asSubquery
, depending on how the class is mapped.See also
-
attribute
sqlalchemy.orm.DeclarativeBase.
__table_args__: Any¶ A dictionary or tuple of arguments that will be passed to the
Table
constructor. See Declarative Table Configuration for background on the specific structure of this collection.See also
-
attribute
sqlalchemy.orm.DeclarativeBase.
__tablename__: Any¶ String name to assign to the generated
Table
object, if not specified directly viaDeclarativeBase.__table__
.
-
attribute
sqlalchemy.orm.DeclarativeBase.
metadata: ClassVar[MetaData]¶ Refers to the
MetaData
collection that will be used for newTable
objects.See also
-
attribute
sqlalchemy.orm.DeclarativeBase.
registry: ClassVar[registry]¶ Refers to the
registry
in use where newMapper
objects will be associated.
- class sqlalchemy.orm.DeclarativeBaseNoMeta¶
Same as
DeclarativeBase
, but does not use a metaclass to intercept new attributes.The
DeclarativeBaseNoMeta
base may be used when use of custom metaclasses is desirable.New in version 2.0.
Members
__mapper__, __mapper_args__, __table__, __table_args__, __tablename__, metadata, registry
Class signature
class
sqlalchemy.orm.DeclarativeBaseNoMeta
(sqlalchemy.inspection.Inspectable
)-
attribute
sqlalchemy.orm.DeclarativeBaseNoMeta.
__mapper__: ClassVar[Mapper[Any]]¶ The
Mapper
object to which a particular class is mapped.May also be acquired using
inspect()
, e.g.inspect(klass)
.
-
attribute
sqlalchemy.orm.DeclarativeBaseNoMeta.
__mapper_args__: Any¶ Dictionary of arguments which will be passed to the
Mapper
constructor.
-
attribute
sqlalchemy.orm.DeclarativeBaseNoMeta.
__table__: Optional[FromClause]¶ The
FromClause
to which a particular subclass is mapped.This is usually an instance of
Table
but may also refer to other kinds ofFromClause
such asSubquery
, depending on how the class is mapped.See also
-
attribute
sqlalchemy.orm.DeclarativeBaseNoMeta.
__table_args__: Any¶ A dictionary or tuple of arguments that will be passed to the
Table
constructor. See Declarative Table Configuration for background on the specific structure of this collection.See also
-
attribute
sqlalchemy.orm.DeclarativeBaseNoMeta.
__tablename__: Any¶ String name to assign to the generated
Table
object, if not specified directly viaDeclarativeBase.__table__
.
-
attribute
sqlalchemy.orm.DeclarativeBaseNoMeta.
metadata: ClassVar[MetaData]¶ Refers to the
MetaData
collection that will be used for newTable
objects.See also
-
attribute
sqlalchemy.orm.DeclarativeBaseNoMeta.
registry: ClassVar[registry]¶ Refers to the
registry
in use where newMapper
objects will be associated.
-
attribute
- function sqlalchemy.orm.has_inherited_table(cls: Type[_O]) bool ¶
Given a class, return True if any of the classes it inherits from has a mapped table, otherwise return False.
This is used in declarative mixins to build attributes that behave differently for the base class vs. a subclass in an inheritance hierarchy.
- function sqlalchemy.orm.synonym_for(name: str, map_column: bool = False) Callable[[Callable[[...], Any]], Synonym[Any]] ¶
Decorator that produces an
synonym()
attribute in conjunction with a Python descriptor.The function being decorated is passed to
synonym()
as thesynonym.descriptor
parameter:class MyClass(Base): __tablename__ = 'my_table' id = Column(Integer, primary_key=True) _job_status = Column("job_status", String(50)) @synonym_for("job_status") @property def job_status(self): return "Status: %s" % self._job_status
The hybrid properties feature of SQLAlchemy is typically preferred instead of synonyms, which is a more legacy feature.
See also
Synonyms - Overview of synonyms
synonym()
- the mapper-level functionUsing Descriptors and Hybrids - The Hybrid Attribute extension provides an updated approach to augmenting attribute behavior more flexibly than can be achieved with synonyms.
- function sqlalchemy.orm.object_mapper(instance: _T) Mapper[_T] ¶
Given an object, return the primary Mapper associated with the object instance.
Raises
sqlalchemy.orm.exc.UnmappedInstanceError
if no mapping is configured.This function is available via the inspection system as:
inspect(instance).mapper
Using the inspection system will raise
sqlalchemy.exc.NoInspectionAvailable
if the instance is not part of a mapping.
- function sqlalchemy.orm.class_mapper(class_: Type[_O], configure: bool = True) Mapper[_O] ¶
Given a class, return the primary
Mapper
associated with the key.Raises
UnmappedClassError
if no mapping is configured on the given class, orArgumentError
if a non-class object is passed.Equivalent functionality is available via the
inspect()
function as:inspect(some_mapped_class)
Using the inspection system will raise
sqlalchemy.exc.NoInspectionAvailable
if the class is not mapped.
- function sqlalchemy.orm.configure_mappers()¶
Initialize the inter-mapper relationships of all mappers that have been constructed thus far across all
registry
collections.The configure step is used to reconcile and initialize the
relationship()
linkages between mapped classes, as well as to invoke configuration events such as theMapperEvents.before_configured()
andMapperEvents.after_configured()
, which may be used by ORM extensions or user-defined extension hooks.Mapper configuration is normally invoked automatically, the first time mappings from a particular
registry
are used, as well as whenever mappings are used and additional not-yet-configured mappers have been constructed. The automatic configuration process however is local only to theregistry
involving the target mapper and any relatedregistry
objects which it may depend on; this is equivalent to invoking theregistry.configure()
method on a particularregistry
.By contrast, the
configure_mappers()
function will invoke the configuration process on allregistry
objects that exist in memory, and may be useful for scenarios where many individualregistry
objects that are nonetheless interrelated are in use.Changed in version 1.4: As of SQLAlchemy 1.4.0b2, this function works on a per-
registry
basis, locating allregistry
objects present and invoking theregistry.configure()
method on each. Theregistry.configure()
method may be preferred to limit the configuration of mappers to those local to a particularregistry
and/or declarative base class.Points at which automatic configuration is invoked include when a mapped class is instantiated into an instance, as well as when ORM queries are emitted using
Session.query()
orSession.execute()
with an ORM-enabled statement.The mapper configure process, whether invoked by
configure_mappers()
or fromregistry.configure()
, provides several event hooks that can be used to augment the mapper configuration step. These hooks include:MapperEvents.before_configured()
- called once beforeconfigure_mappers()
orregistry.configure()
does any work; this can be used to establish additional options, properties, or related mappings before the operation proceeds.MapperEvents.mapper_configured()
- called as each individualMapper
is configured within the process; will include all mapper state except for backrefs set up by other mappers that are still to be configured.MapperEvents.after_configured()
- called once afterconfigure_mappers()
orregistry.configure()
is complete; at this stage, allMapper
objects that fall within the scope of the configuration operation will be fully configured. Note that the calling application may still have other mappings that haven’t been produced yet, such as if they are in modules as yet unimported, and may also have mappings that are still to be configured, if they are in otherregistry
collections not part of the current scope of configuration.
- function sqlalchemy.orm.clear_mappers() None ¶
Remove all mappers from all classes.
Changed in version 1.4: This function now locates all
registry
objects and calls upon theregistry.dispose()
method of each.This function removes all instrumentation from classes and disposes of their associated mappers. Once called, the classes are unmapped and can be later re-mapped with new mappers.
clear_mappers()
is not for normal use, as there is literally no valid usage for it outside of very specific testing scenarios. Normally, mappers are permanent structural components of user-defined classes, and are never discarded independently of their class. If a mapped class itself is garbage collected, its mapper is automatically disposed of as well. As such,clear_mappers()
is only for usage in test suites that re-use the same classes with different mappings, which is itself an extremely rare use case - the only such use case is in fact SQLAlchemy’s own test suite, and possibly the test suites of other ORM extension libraries which intend to test various combinations of mapper construction upon a fixed set of classes.
- function sqlalchemy.orm.util.identity_key(class_: Optional[Type[_T]] = None, ident: Union[Any, Tuple[Any, ...]] = None, *, instance: Optional[_T] = None, row: Optional[Union[Row[Any], RowMapping]] = None, identity_token: Optional[Any] = None) _IdentityKeyType[_T] ¶
Generate “identity key” tuples, as are used as keys in the
Session.identity_map
dictionary.This function has several call styles:
identity_key(class, ident, identity_token=token)
This form receives a mapped class and a primary key scalar or tuple as an argument.
E.g.:
>>> identity_key(MyClass, (1, 2)) (<class '__main__.MyClass'>, (1, 2), None)
- param class:
mapped class (must be a positional argument)
- param ident:
primary key, may be a scalar or tuple argument.
- param identity_token:
optional identity token
New in version 1.2: added identity_token
identity_key(instance=instance)
This form will produce the identity key for a given instance. The instance need not be persistent, only that its primary key attributes are populated (else the key will contain
None
for those missing values).E.g.:
>>> instance = MyClass(1, 2) >>> identity_key(instance=instance) (<class '__main__.MyClass'>, (1, 2), None)
In this form, the given instance is ultimately run though
Mapper.identity_key_from_instance()
, which will have the effect of performing a database check for the corresponding row if the object is expired.- param instance:
object instance (must be given as a keyword arg)
identity_key(class, row=row, identity_token=token)
This form is similar to the class/tuple form, except is passed a database result row as a
Row
orRowMapping
object.E.g.:
>>> row = engine.execute(\ text("select * from table where a=1 and b=2")\ ).first() >>> identity_key(MyClass, row=row) (<class '__main__.MyClass'>, (1, 2), None)
- param class:
mapped class (must be a positional argument)
- param row:
Row
row returned by aCursorResult
(must be given as a keyword arg)- param identity_token:
optional identity token
New in version 1.2: added identity_token
- function sqlalchemy.orm.polymorphic_union(table_map, typecolname, aliasname='p_union', cast_nulls=True)¶
Create a
UNION
statement used by a polymorphic mapper.See Concrete Table Inheritance for an example of how this is used.
- Parameters:
table_map – mapping of polymorphic identities to
Table
objects.typecolname – string name of a “discriminator” column, which will be derived from the query, producing the polymorphic identity for each row. If
None
, no polymorphic discriminator is generated.aliasname – name of the
alias()
construct generated.cast_nulls – if True, non-existent columns, which are represented as labeled NULLs, will be passed into CAST. This is a legacy behavior that is problematic on some backends such as Oracle - in which case it can be set to False.
- function sqlalchemy.orm.orm_insert_sentinel(name: Optional[str] = None, type_: Optional[_TypeEngineArgument[Any]] = None, *, default: Optional[Any] = None, omit_from_statements: bool = True) MappedColumn[Any] ¶
Provides a surrogate
mapped_column()
that generates a so-called sentinel column, allowing efficient bulk inserts with deterministic RETURNING sorting for tables that don’t otherwise have qualifying primary key configurations.Use of
orm_insert_sentinel()
is analogous to the use of theinsert_sentinel()
construct within a CoreTable
construct.Guidelines for adding this construct to a Declarative mapped class are the same as that of the
insert_sentinel()
construct; the database table itself also needs to have a column with this name present.For background on how this object is used, see the section Configuring Sentinel Columns as part of the section “Insert Many Values” Behavior for INSERT statements.
New in version 2.0.10.
- function sqlalchemy.orm.reconstructor(fn)¶
Decorate a method as the ‘reconstructor’ hook.
Designates a single method as the “reconstructor”, an
__init__
-like method that will be called by the ORM after the instance has been loaded from the database or otherwise reconstituted.Tip
The
reconstructor()
decorator makes use of theInstanceEvents.load()
event hook, which can be used directly.The reconstructor will be invoked with no arguments. Scalar (non-collection) database-mapped attributes of the instance will be available for use within the function. Eagerly-loaded collections are generally not yet available and will usually only contain the first element. ORM state changes made to objects at this stage will not be recorded for the next flush() operation, so the activity within a reconstructor should be conservative.
See also
- class sqlalchemy.orm.Mapper¶
Defines an association between a Python class and a database table or other relational structure, so that ORM operations against the class may proceed.
The
Mapper
object is instantiated using mapping methods present on theregistry
object. For information about instantiating newMapper
objects, see ORM Mapped Class Overview.Members
__init__(), add_properties(), add_property(), all_orm_descriptors, attrs, base_mapper, c, cascade_iterator(), class_, class_manager, column_attrs, columns, common_parent(), composites, concrete, configured, entity, get_property(), get_property_by_column(), identity_key_from_instance(), identity_key_from_primary_key(), identity_key_from_row(), inherits, is_mapper, is_sibling(), isa(), iterate_properties, local_table, mapped_table, mapper, non_primary, persist_selectable, polymorphic_identity, polymorphic_iterator(), polymorphic_map, polymorphic_on, primary_key, primary_key_from_instance(), primary_mapper(), relationships, selectable, self_and_descendants, single, synonyms, tables, validators, with_polymorphic_mappers
Class signature
class
sqlalchemy.orm.Mapper
(sqlalchemy.orm.ORMFromClauseRole
,sqlalchemy.orm.ORMEntityColumnsClauseRole
,sqlalchemy.sql.cache_key.MemoizedHasCacheKey
,sqlalchemy.orm.base.InspectionAttr
,sqlalchemy.log.Identified
,sqlalchemy.inspection.Inspectable
,sqlalchemy.event.registry.EventTarget
,typing.Generic
)-
method
sqlalchemy.orm.Mapper.
__init__(class_: Type[_O], local_table: Optional[FromClause] = None, properties: Optional[Mapping[str, MapperProperty[Any]]] = None, primary_key: Optional[Iterable[_ORMColumnExprArgument[Any]]] = None, non_primary: bool = False, inherits: Optional[Union[Mapper[Any], Type[Any]]] = None, inherit_condition: Optional[_ColumnExpressionArgument[bool]] = None, inherit_foreign_keys: Optional[Sequence[_ORMColumnExprArgument[Any]]] = None, always_refresh: bool = False, version_id_col: Optional[_ORMColumnExprArgument[Any]] = None, version_id_generator: Optional[Union[Literal[False], Callable[[Any], Any]]] = None, polymorphic_on: Optional[Union[_ORMColumnExprArgument[Any], str, MapperProperty[Any]]] = None, _polymorphic_map: Optional[Dict[Any, Mapper[Any]]] = None, polymorphic_identity: Optional[Any] = None, concrete: bool = False, with_polymorphic: Optional[_WithPolymorphicArg] = None, polymorphic_abstract: bool = False, polymorphic_load: Optional[Literal['selectin', 'inline']] = None, allow_partial_pks: bool = True, batch: bool = True, column_prefix: Optional[str] = None, include_properties: Optional[Sequence[str]] = None, exclude_properties: Optional[Sequence[str]] = None, passive_updates: bool = True, passive_deletes: bool = False, confirm_deleted_rows: bool = True, eager_defaults: Literal[True, False, 'auto'] = 'auto', legacy_is_orphan: bool = False, _compiled_cache_size: int = 100)¶ Direct constructor for a new
Mapper
object.The
Mapper
constructor is not called directly, and is normally invoked through the use of theregistry
object through either the Declarative or Imperative mapping styles.Changed in version 2.0: The public facing
mapper()
function is removed; for a classical mapping configuration, use theregistry.map_imperatively()
method.Parameters documented below may be passed to either the
registry.map_imperatively()
method, or may be passed in the__mapper_args__
declarative class attribute described at Mapper Configuration Options with Declarative.- Parameters:
class_ – The class to be mapped. When using Declarative, this argument is automatically passed as the declared class itself.
local_table – The
Table
or otherFromClause
(i.e. selectable) to which the class is mapped. May beNone
if this mapper inherits from another mapper using single-table inheritance. When using Declarative, this argument is automatically passed by the extension, based on what is configured via theDeclarativeBase.__table__
attribute or via theTable
produced as a result of theDeclarativeBase.__tablename__
attribute being present.polymorphic_abstract –
Indicates this class will be mapped in a polymorphic hierarchy, but not directly instantiated. The class is mapped normally, except that it has no requirement for a
Mapper.polymorphic_identity
within an inheritance hierarchy. The class however must be part of a polymorphic inheritance scheme which usesMapper.polymorphic_on
at the base.New in version 2.0.
always_refresh – If True, all query operations for this mapped class will overwrite all data within object instances that already exist within the session, erasing any in-memory changes with whatever information was loaded from the database. Usage of this flag is highly discouraged; as an alternative, see the method
Query.populate_existing()
.allow_partial_pks – Defaults to True. Indicates that a composite primary key with some NULL values should be considered as possibly existing within the database. This affects whether a mapper will assign an incoming row to an existing identity, as well as if
Session.merge()
will check the database first for a particular primary key value. A “partial primary key” can occur if one has mapped to an OUTER JOIN, for example.batch – Defaults to
True
, indicating that save operations of multiple entities can be batched together for efficiency. Setting to False indicates that an instance will be fully saved before saving the next instance. This is used in the extremely rare case that aMapperEvents
listener requires being called in between individual row persistence operations.column_prefix –
A string which will be prepended to the mapped attribute name when
Column
objects are automatically assigned as attributes to the mapped class. Does not affectColumn
objects that are mapped explicitly in theMapper.properties
dictionary.This parameter is typically useful with imperative mappings that keep the
Table
object separate. Below, assuming theuser_table
Table
object has columns nameduser_id
,user_name
, andpassword
:class User(Base): __table__ = user_table __mapper_args__ = {'column_prefix':'_'}
The above mapping will assign the
user_id
,user_name
, andpassword
columns to attributes named_user_id
,_user_name
, and_password
on the mappedUser
class.The
Mapper.column_prefix
parameter is uncommon in modern use. For dealing with reflected tables, a more flexible approach to automating a naming scheme is to intercept theColumn
objects as they are reflected; see the section Automating Column Naming Schemes from Reflected Tables for notes on this usage pattern.concrete –
If True, indicates this mapper should use concrete table inheritance with its parent mapper.
See the section Concrete Table Inheritance for an example.
confirm_deleted_rows – defaults to True; when a DELETE occurs of one more rows based on specific primary keys, a warning is emitted when the number of rows matched does not equal the number of rows expected. This parameter may be set to False to handle the case where database ON DELETE CASCADE rules may be deleting some of those rows automatically. The warning may be changed to an exception in a future release.
eager_defaults –
if True, the ORM will immediately fetch the value of server-generated default values after an INSERT or UPDATE, rather than leaving them as expired to be fetched on next access. This can be used for event schemes where the server-generated values are needed immediately before the flush completes.
The fetch of values occurs either by using
RETURNING
inline with theINSERT
orUPDATE
statement, or by adding an additionalSELECT
statement subsequent to theINSERT
orUPDATE
, if the backend does not supportRETURNING
.The use of
RETURNING
is extremely performant in particular forINSERT
statements where SQLAlchemy can take advantage of insertmanyvalues, whereas the use of an additionalSELECT
is relatively poor performing, adding additional SQL round trips which would be unnecessary if these new attributes are not to be accessed in any case.For this reason,
Mapper.eager_defaults
defaults to the string value"auto"
, which indicates that server defaults for INSERT should be fetched usingRETURNING
if the backing database supports it and if the dialect in use supports “insertmanyreturning” for an INSERT statement. If the backing database does not supportRETURNING
or “insertmanyreturning” is not available, server defaults will not be fetched.Changed in version 2.0.0rc1: added the “auto” option for
Mapper.eager_defaults
See also
Changed in version 2.0.0: RETURNING now works with multiple rows INSERTed at once using the insertmanyvalues feature, which among other things allows the
Mapper.eager_defaults
feature to be very performant on supporting backends.exclude_properties –
A list or set of string column names to be excluded from mapping.
See also
include_properties –
An inclusive list or set of string column names to map.
See also
inherits –
A mapped class or the corresponding
Mapper
of one indicating a superclass to which thisMapper
should inherit from. The mapped class here must be a subclass of the other mapper’s class. When using Declarative, this argument is passed automatically as a result of the natural class hierarchy of the declared classes.inherit_condition – For joined table inheritance, a SQL expression which will define how the two tables are joined; defaults to a natural join between the two tables.
inherit_foreign_keys – When
inherit_condition
is used and the columns present are missing aForeignKey
configuration, this parameter can be used to specify which columns are “foreign”. In most cases can be left asNone
.legacy_is_orphan –
Boolean, defaults to
False
. WhenTrue
, specifies that “legacy” orphan consideration is to be applied to objects mapped by this mapper, which means that a pending (that is, not persistent) object is auto-expunged from an owningSession
only when it is de-associated from all parents that specify adelete-orphan
cascade towards this mapper. The new default behavior is that the object is auto-expunged when it is de-associated with any of its parents that specifydelete-orphan
cascade. This behavior is more consistent with that of a persistent object, and allows behavior to be consistent in more scenarios independently of whether or not an orphan object has been flushed yet or not.See the change note and example at The consideration of a “pending” object as an “orphan” has been made more aggressive for more detail on this change.
non_primary –
- Specify that this
Mapper
is in addition to the “primary” mapper, that is, the one used for persistence. The
Mapper
created here may be used for ad-hoc mapping of the class to an alternate selectable, for loading only.Deprecated since version 1.3: The
mapper.non_primary
parameter is deprecated, and will be removed in a future release. The functionality of non primary mappers is now better suited using theAliasedClass
construct, which can also be used as the target of arelationship()
in 1.3.
See also
Relationship to Aliased Class - the new pattern that removes the need for the
Mapper.non_primary
flag.- Specify that this
passive_deletes –
Indicates DELETE behavior of foreign key columns when a joined-table inheritance entity is being deleted. Defaults to
False
for a base mapper; for an inheriting mapper, defaults toFalse
unless the value is set toTrue
on the superclass mapper.When
True
, it is assumed that ON DELETE CASCADE is configured on the foreign key relationships that link this mapper’s table to its superclass table, so that when the unit of work attempts to delete the entity, it need only emit a DELETE statement for the superclass table, and not this table.When
False
, a DELETE statement is emitted for this mapper’s table individually. If the primary key attributes local to this table are unloaded, then a SELECT must be emitted in order to validate these attributes; note that the primary key columns of a joined-table subclass are not part of the “primary key” of the object as a whole.Note that a value of
True
is always forced onto the subclass mappers; that is, it’s not possible for a superclass to specify passive_deletes without this taking effect for all subclass mappers.See also
Using foreign key ON DELETE cascade with ORM relationships - description of similar feature as used with
relationship()
mapper.passive_updates
- supporting ON UPDATE CASCADE for joined-table inheritance mapperspassive_updates –
Indicates UPDATE behavior of foreign key columns when a primary key column changes on a joined-table inheritance mapping. Defaults to
True
.When True, it is assumed that ON UPDATE CASCADE is configured on the foreign key in the database, and that the database will handle propagation of an UPDATE from a source column to dependent columns on joined-table rows.
When False, it is assumed that the database does not enforce referential integrity and will not be issuing its own CASCADE operation for an update. The unit of work process will emit an UPDATE statement for the dependent columns during a primary key change.
See also
Mutable Primary Keys / Update Cascades - description of a similar feature as used with
relationship()
mapper.passive_deletes
- supporting ON DELETE CASCADE for joined-table inheritance mapperspolymorphic_load –
Specifies “polymorphic loading” behavior for a subclass in an inheritance hierarchy (joined and single table inheritance only). Valid values are:
“‘inline’” - specifies this class should be part of the “with_polymorphic” mappers, e.g. its columns will be included in a SELECT query against the base.
“‘selectin’” - specifies that when instances of this class are loaded, an additional SELECT will be emitted to retrieve the columns specific to this subclass. The SELECT uses IN to fetch multiple subclasses at once.
New in version 1.2.
polymorphic_on –
Specifies the column, attribute, or SQL expression used to determine the target class for an incoming row, when inheriting classes are present.
May be specified as a string attribute name, or as a SQL expression such as a
Column
or in a Declarative mapping amapped_column()
object. It is typically expected that the SQL expression corresponds to a column in the base-most mappedTable
:class Employee(Base): __tablename__ = 'employee' id: Mapped[int] = mapped_column(primary_key=True) discriminator: Mapped[str] = mapped_column(String(50)) __mapper_args__ = { "polymorphic_on":discriminator, "polymorphic_identity":"employee" }
It may also be specified as a SQL expression, as in this example where we use the
case()
construct to provide a conditional approach:class Employee(Base): __tablename__ = 'employee' id: Mapped[int] = mapped_column(primary_key=True) discriminator: Mapped[str] = mapped_column(String(50)) __mapper_args__ = { "polymorphic_on":case( (discriminator == "EN", "engineer"), (discriminator == "MA", "manager"), else_="employee"), "polymorphic_identity":"employee" }
It may also refer to any attribute using its string name, which is of particular use when using annotated column configurations:
class Employee(Base): __tablename__ = 'employee' id: Mapped[int] = mapped_column(primary_key=True) discriminator: Mapped[str] __mapper_args__ = { "polymorphic_on": "discriminator", "polymorphic_identity": "employee" }
When setting
polymorphic_on
to reference an attribute or expression that’s not present in the locally mappedTable
, yet the value of the discriminator should be persisted to the database, the value of the discriminator is not automatically set on new instances; this must be handled by the user, either through manual means or via event listeners. A typical approach to establishing such a listener looks like:from sqlalchemy import event from sqlalchemy.orm import object_mapper @event.listens_for(Employee, "init", propagate=True) def set_identity(instance, *arg, **kw): mapper = object_mapper(instance) instance.discriminator = mapper.polymorphic_identity
Where above, we assign the value of
polymorphic_identity
for the mapped class to thediscriminator
attribute, thus persisting the value to thediscriminator
column in the database.Warning
Currently, only one discriminator column may be set, typically on the base-most class in the hierarchy. “Cascading” polymorphic columns are not yet supported.
polymorphic_identity –
Specifies the value which identifies this particular class as returned by the column expression referred to by the
Mapper.polymorphic_on
setting. As rows are received, the value corresponding to theMapper.polymorphic_on
column expression is compared to this value, indicating which subclass should be used for the newly reconstructed object.properties –
A dictionary mapping the string names of object attributes to
MapperProperty
instances, which define the persistence behavior of that attribute. Note thatColumn
objects present in the mappedTable
are automatically placed intoColumnProperty
instances upon mapping, unless overridden. When using Declarative, this argument is passed automatically, based on all thoseMapperProperty
instances declared in the declared class body.See also
The properties dictionary - in the ORM Mapped Class Overview
primary_key –
A list of
Column
objects, or alternatively string names of attribute names which refer toColumn
, which define the primary key to be used against this mapper’s selectable unit. This is normally simply the primary key of thelocal_table
, but can be overridden here.Changed in version 2.0.2:
Mapper.primary_key
arguments may be indicated as string attribute names as well.See also
Mapping to an Explicit Set of Primary Key Columns - background and example use
version_id_col –
A
Column
that will be used to keep a running version id of rows in the table. This is used to detect concurrent updates or the presence of stale data in a flush. The methodology is to detect if an UPDATE statement does not match the last known version id, aStaleDataError
exception is thrown. By default, the column must be ofInteger
type, unlessversion_id_generator
specifies an alternative version generator.See also
Configuring a Version Counter - discussion of version counting and rationale.
version_id_generator –
Define how new version ids should be generated. Defaults to
None
, which indicates that a simple integer counting scheme be employed. To provide a custom versioning scheme, provide a callable function of the form:def generate_version(version): return next_version
Alternatively, server-side versioning functions such as triggers, or programmatic versioning schemes outside of the version id generator may be used, by specifying the value
False
. Please see Server Side Version Counters for a discussion of important points when using this option.with_polymorphic –
A tuple in the form
(<classes>, <selectable>)
indicating the default style of “polymorphic” loading, that is, which tables are queried at once. <classes> is any single or list of mappers and/or classes indicating the inherited classes that should be loaded at once. The special value'*'
may be used to indicate all descending classes should be loaded immediately. The second tuple argument <selectable> indicates a selectable that will be used to query for multiple classes.The
Mapper.polymorphic_load
parameter may be preferable over the use ofMapper.with_polymorphic
in modern mappings to indicate a per-subclass technique of indicating polymorphic loading styles.
-
method
sqlalchemy.orm.Mapper.
add_properties(dict_of_properties)¶ Add the given dictionary of properties to this mapper, using add_property.
-
method
sqlalchemy.orm.Mapper.
add_property(key: str, prop: Union[Column[Any], MapperProperty[Any]]) None ¶ Add an individual MapperProperty to this mapper.
If the mapper has not been configured yet, just adds the property to the initial properties dictionary sent to the constructor. If this Mapper has already been configured, then the given MapperProperty is configured immediately.
-
attribute
sqlalchemy.orm.Mapper.
all_orm_descriptors¶ A namespace of all
InspectionAttr
attributes associated with the mapped class.These attributes are in all cases Python descriptors associated with the mapped class or its superclasses.
This namespace includes attributes that are mapped to the class as well as attributes declared by extension modules. It includes any Python descriptor type that inherits from
InspectionAttr
. This includesQueryableAttribute
, as well as extension types such ashybrid_property
,hybrid_method
andAssociationProxy
.To distinguish between mapped attributes and extension attributes, the attribute
InspectionAttr.extension_type
will refer to a constant that distinguishes between different extension types.The sorting of the attributes is based on the following rules:
Iterate through the class and its superclasses in order from subclass to superclass (i.e. iterate through
cls.__mro__
)For each class, yield the attributes in the order in which they appear in
__dict__
, with the exception of those in step 3 below. In Python 3.6 and above this ordering will be the same as that of the class’ construction, with the exception of attributes that were added after the fact by the application or the mapper.If a certain attribute key is also in the superclass
__dict__
, then it’s included in the iteration for that class, and not the class in which it first appeared.
The above process produces an ordering that is deterministic in terms of the order in which attributes were assigned to the class.
Changed in version 1.3.19: ensured deterministic ordering for
Mapper.all_orm_descriptors()
.When dealing with a
QueryableAttribute
, theQueryableAttribute.property
attribute refers to theMapperProperty
property, which is what you get when referring to the collection of mapped properties viaMapper.attrs
.Warning
The
Mapper.all_orm_descriptors
accessor namespace is an instance ofOrderedProperties
. This is a dictionary-like object which includes a small number of named methods such asOrderedProperties.items()
andOrderedProperties.values()
. When accessing attributes dynamically, favor using the dict-access scheme, e.g.mapper.all_orm_descriptors[somename]
overgetattr(mapper.all_orm_descriptors, somename)
to avoid name collisions.See also
-
attribute
sqlalchemy.orm.Mapper.
attrs¶ A namespace of all
MapperProperty
objects associated this mapper.This is an object that provides each property based on its key name. For instance, the mapper for a
User
class which hasUser.name
attribute would providemapper.attrs.name
, which would be theColumnProperty
representing thename
column. The namespace object can also be iterated, which would yield eachMapperProperty
.Mapper
has several pre-filtered views of this attribute which limit the types of properties returned, includingsynonyms
,column_attrs
,relationships
, andcomposites
.Warning
The
Mapper.attrs
accessor namespace is an instance ofOrderedProperties
. This is a dictionary-like object which includes a small number of named methods such asOrderedProperties.items()
andOrderedProperties.values()
. When accessing attributes dynamically, favor using the dict-access scheme, e.g.mapper.attrs[somename]
overgetattr(mapper.attrs, somename)
to avoid name collisions.See also
-
attribute
sqlalchemy.orm.Mapper.
base_mapper: Mapper[Any]¶ The base-most
Mapper
in an inheritance chain.In a non-inheriting scenario, this attribute will always be this
Mapper
. In an inheritance scenario, it references theMapper
which is parent to all otherMapper
objects in the inheritance chain.This is a read only attribute determined during mapper construction. Behavior is undefined if directly modified.
-
attribute
sqlalchemy.orm.Mapper.
c: ReadOnlyColumnCollection[str, Column[Any]]¶ A synonym for
Mapper.columns
.
-
method
sqlalchemy.orm.Mapper.
cascade_iterator(type_: str, state: InstanceState[_O], halt_on: Optional[Callable[[InstanceState[Any]], bool]] = None) Iterator[Tuple[object, Mapper[Any], InstanceState[Any], _InstanceDict]] ¶ Iterate each element and its mapper in an object graph, for all relationships that meet the given cascade rule.
- Parameters:
type_ –
The name of the cascade rule (i.e.
"save-update"
,"delete"
, etc.).Note
the
"all"
cascade is not accepted here. For a generic object traversal function, see How do I walk all objects that are related to a given object?.state – The lead InstanceState. child items will be processed per the relationships defined for this object’s mapper.
- Returns:
the method yields individual object instances.
See also
How do I walk all objects that are related to a given object? - illustrates a generic function to traverse all objects without relying on cascades.
-
attribute
sqlalchemy.orm.Mapper.
class_: Type[_O]¶ The class to which this
Mapper
is mapped.
-
attribute
sqlalchemy.orm.Mapper.
class_manager: ClassManager[_O]¶ The
ClassManager
which maintains event listeners and class-bound descriptors for thisMapper
.This is a read only attribute determined during mapper construction. Behavior is undefined if directly modified.
-
attribute
sqlalchemy.orm.Mapper.
column_attrs¶ Return a namespace of all
ColumnProperty
properties maintained by thisMapper
.See also
Mapper.attrs
- namespace of allMapperProperty
objects.
-
attribute
sqlalchemy.orm.Mapper.
columns: ReadOnlyColumnCollection[str, Column[Any]]¶ A collection of
Column
or other scalar expression objects maintained by thisMapper
.The collection behaves the same as that of the
c
attribute on anyTable
object, except that only those columns included in this mapping are present, and are keyed based on the attribute name defined in the mapping, not necessarily thekey
attribute of theColumn
itself. Additionally, scalar expressions mapped bycolumn_property()
are also present here.This is a read only attribute determined during mapper construction. Behavior is undefined if directly modified.
-
method
sqlalchemy.orm.Mapper.
common_parent(other: Mapper[Any]) bool ¶ Return true if the given mapper shares a common inherited parent as this mapper.
-
attribute
sqlalchemy.orm.Mapper.
composites¶ Return a namespace of all
Composite
properties maintained by thisMapper
.See also
Mapper.attrs
- namespace of allMapperProperty
objects.
-
attribute
sqlalchemy.orm.Mapper.
concrete: bool¶ Represent
True
if thisMapper
is a concrete inheritance mapper.This is a read only attribute determined during mapper construction. Behavior is undefined if directly modified.
-
attribute
sqlalchemy.orm.Mapper.
configured: bool = False¶ Represent
True
if thisMapper
has been configured.This is a read only attribute determined during mapper construction. Behavior is undefined if directly modified.
See also
-
attribute
sqlalchemy.orm.Mapper.
entity¶ Part of the inspection API.
Returns self.class_.
-
method
sqlalchemy.orm.Mapper.
get_property(key: str, _configure_mappers: bool = False) MapperProperty[Any] ¶ return a MapperProperty associated with the given key.
-
method
sqlalchemy.orm.Mapper.
get_property_by_column(column: ColumnElement[_T]) MapperProperty[_T] ¶ Given a
Column
object, return theMapperProperty
which maps this column.
-
method
sqlalchemy.orm.Mapper.
identity_key_from_instance(instance: _O) _IdentityKeyType[_O] ¶ Return the identity key for the given instance, based on its primary key attributes.
If the instance’s state is expired, calling this method will result in a database check to see if the object has been deleted. If the row no longer exists,
ObjectDeletedError
is raised.This value is typically also found on the instance state under the attribute name key.
-
method
sqlalchemy.orm.Mapper.
identity_key_from_primary_key(primary_key: Tuple[Any, ...], identity_token: Optional[Any] = None) _IdentityKeyType[_O] ¶ Return an identity-map key for use in storing/retrieving an item from an identity map.
- Parameters:
primary_key – A list of values indicating the identifier.
-
method
sqlalchemy.orm.Mapper.
identity_key_from_row(row: Optional[Union[Row[Any], RowMapping]], identity_token: Optional[Any] = None, adapter: Optional[ORMAdapter] = None) _IdentityKeyType[_O] ¶ Return an identity-map key for use in storing/retrieving an item from the identity map.
- Parameters:
row –
A
Row
orRowMapping
produced from a result set that selected from the ORM mapped primary key columns.Changed in version 2.0:
Row
orRowMapping
are accepted for the “row” argument
-
attribute
sqlalchemy.orm.Mapper.
inherits: Optional[Mapper[Any]]¶ References the
Mapper
which thisMapper
inherits from, if any.
-
attribute
sqlalchemy.orm.Mapper.
is_mapper = True¶ Part of the inspection API.
-
method
sqlalchemy.orm.Mapper.
is_sibling(other: Mapper[Any]) bool ¶ return true if the other mapper is an inheriting sibling to this one. common parent but different branch
-
method
sqlalchemy.orm.Mapper.
isa(other: Mapper[Any]) bool ¶ Return True if the this mapper inherits from the given mapper.
-
attribute
sqlalchemy.orm.Mapper.
iterate_properties¶ return an iterator of all MapperProperty objects.
-
attribute
sqlalchemy.orm.Mapper.
local_table: FromClause¶ The immediate
FromClause
which thisMapper
refers towards.Typically is an instance of
Table
, may be anyFromClause
.The “local” table is the selectable that the
Mapper
is directly responsible for managing from an attribute access and flush perspective. For non-inheriting mappers,Mapper.local_table
will be the same asMapper.persist_selectable
. For inheriting mappers,Mapper.local_table
refers to the specific portion ofMapper.persist_selectable
that includes the columns to which thisMapper
is loading/persisting, such as a particularTable
within a join.
-
attribute
sqlalchemy.orm.Mapper.
mapped_table¶ Deprecated since version 1.3: Use .persist_selectable
-
attribute
sqlalchemy.orm.Mapper.
mapper¶ Part of the inspection API.
Returns self.
-
attribute
sqlalchemy.orm.Mapper.
non_primary: bool¶ Represent
True
if thisMapper
is a “non-primary” mapper, e.g. a mapper that is used only to select rows but not for persistence management.This is a read only attribute determined during mapper construction. Behavior is undefined if directly modified.
-
attribute
sqlalchemy.orm.Mapper.
persist_selectable: FromClause¶ The
FromClause
to which thisMapper
is mapped.Typically is an instance of
Table
, may be anyFromClause
.The
Mapper.persist_selectable
is similar toMapper.local_table
, but represents theFromClause
that represents the inheriting class hierarchy overall in an inheritance scenario.:attr.`.Mapper.persist_selectable` is also separate from the
Mapper.selectable
attribute, the latter of which may be an alternate subquery used for selecting columns. :attr.`.Mapper.persist_selectable` is oriented towards columns that will be written on a persist operation.
-
attribute
sqlalchemy.orm.Mapper.
polymorphic_identity: Optional[Any]¶ Represent an identifier which is matched against the
Mapper.polymorphic_on
column during result row loading.Used only with inheritance, this object can be of any type which is comparable to the type of column represented by
Mapper.polymorphic_on
.This is a read only attribute determined during mapper construction. Behavior is undefined if directly modified.
-
method
sqlalchemy.orm.Mapper.
polymorphic_iterator() Iterator[Mapper[Any]] ¶ Iterate through the collection including this mapper and all descendant mappers.
This includes not just the immediately inheriting mappers but all their inheriting mappers as well.
To iterate through an entire hierarchy, use
mapper.base_mapper.polymorphic_iterator()
.
-
attribute
sqlalchemy.orm.Mapper.
polymorphic_map: Dict[Any, Mapper[Any]]¶ A mapping of “polymorphic identity” identifiers mapped to
Mapper
instances, within an inheritance scenario.The identifiers can be of any type which is comparable to the type of column represented by
Mapper.polymorphic_on
.An inheritance chain of mappers will all reference the same polymorphic map object. The object is used to correlate incoming result rows to target mappers.
This is a read only attribute determined during mapper construction. Behavior is undefined if directly modified.
-
attribute
sqlalchemy.orm.Mapper.
polymorphic_on: Optional[KeyedColumnElement[Any]]¶ The
Column
or SQL expression specified as thepolymorphic_on
argument for thisMapper
, within an inheritance scenario.This attribute is normally a
Column
instance but may also be an expression, such as one derived fromcast()
.This is a read only attribute determined during mapper construction. Behavior is undefined if directly modified.
-
attribute
sqlalchemy.orm.Mapper.
primary_key: Tuple[Column[Any], ...]¶ An iterable containing the collection of
Column
objects which comprise the ‘primary key’ of the mapped table, from the perspective of thisMapper
.This list is against the selectable in
Mapper.persist_selectable
. In the case of inheriting mappers, some columns may be managed by a superclass mapper. For example, in the case of aJoin
, the primary key is determined by all of the primary key columns across all tables referenced by theJoin
.The list is also not necessarily the same as the primary key column collection associated with the underlying tables; the
Mapper
features aprimary_key
argument that can override what theMapper
considers as primary key columns.This is a read only attribute determined during mapper construction. Behavior is undefined if directly modified.
-
method
sqlalchemy.orm.Mapper.
primary_key_from_instance(instance: _O) Tuple[Any, ...] ¶ Return the list of primary key values for the given instance.
If the instance’s state is expired, calling this method will result in a database check to see if the object has been deleted. If the row no longer exists,
ObjectDeletedError
is raised.
-
method
sqlalchemy.orm.Mapper.
primary_mapper() Mapper[Any] ¶ Return the primary mapper corresponding to this mapper’s class key (class).
-
attribute
sqlalchemy.orm.Mapper.
relationships¶ A namespace of all
Relationship
properties maintained by thisMapper
.Warning
the
Mapper.relationships
accessor namespace is an instance ofOrderedProperties
. This is a dictionary-like object which includes a small number of named methods such asOrderedProperties.items()
andOrderedProperties.values()
. When accessing attributes dynamically, favor using the dict-access scheme, e.g.mapper.relationships[somename]
overgetattr(mapper.relationships, somename)
to avoid name collisions.See also
Mapper.attrs
- namespace of allMapperProperty
objects.
-
attribute
sqlalchemy.orm.Mapper.
selectable¶ The
FromClause
construct thisMapper
selects from by default.Normally, this is equivalent to
persist_selectable
, unless thewith_polymorphic
feature is in use, in which case the full “polymorphic” selectable is returned.
-
attribute
sqlalchemy.orm.Mapper.
self_and_descendants¶ The collection including this mapper and all descendant mappers.
This includes not just the immediately inheriting mappers but all their inheriting mappers as well.
-
attribute
sqlalchemy.orm.Mapper.
single: bool¶ Represent
True
if thisMapper
is a single table inheritance mapper.Mapper.local_table
will beNone
if this flag is set.This is a read only attribute determined during mapper construction. Behavior is undefined if directly modified.
-
attribute
sqlalchemy.orm.Mapper.
synonyms¶ Return a namespace of all
Synonym
properties maintained by thisMapper
.See also
Mapper.attrs
- namespace of allMapperProperty
objects.
-
attribute
sqlalchemy.orm.Mapper.
tables: Sequence[TableClause]¶ A sequence containing the collection of
Table
orTableClause
objects which thisMapper
is aware of.If the mapper is mapped to a
Join
, or anAlias
representing aSelect
, the individualTable
objects that comprise the full construct will be represented here.This is a read only attribute determined during mapper construction. Behavior is undefined if directly modified.
-
attribute
sqlalchemy.orm.Mapper.
validators: util.immutabledict[str, Tuple[str, Dict[str, Any]]]¶ An immutable dictionary of attributes which have been decorated using the
validates()
decorator.The dictionary contains string attribute names as keys mapped to the actual validation method.
-
attribute
sqlalchemy.orm.Mapper.
with_polymorphic_mappers¶ The list of
Mapper
objects included in the default “polymorphic” query.
-
method
- class sqlalchemy.orm.MappedAsDataclass¶
Mixin class to indicate when mapping this class, also convert it to be a dataclass.
See also
Declarative Dataclass Mapping - complete background on SQLAlchemy native dataclass mapping
New in version 2.0.
- class sqlalchemy.orm.MappedClassProtocol¶
A protocol representing a SQLAlchemy mapped class.
The protocol is generic on the type of class, use
MappedClassProtocol[Any]
to allow any mapped class.Class signature
class
sqlalchemy.orm.MappedClassProtocol
(typing.Protocol
)