Object Name | Description |
---|---|
|
Class decorator which will adapt a given class into a
|
|
Given a class, return the primary |
Remove all mappers from all classes. |
|
Initialize the inter-mapper relationships of all mappers that
have been constructed thus far across all |
|
|
Construct a base class for declarative class definitions. |
|
Mark a class as providing the feature of “declarative mixin”. |
Mark a class-level method as representing the definition of a mapped property or special declarative member name. |
|
|
Given a class, return True if any of the classes it inherits from has a mapped table, otherwise return False. |
|
Generate “identity key” tuples, as are used as keys in the
|
|
Direct constructor for a new |
Define the correlation of class attributes to database table columns. |
|
|
Given an object, return the primary Mapper associated with the object instance. |
|
Create a |
Generalized registry for mapping classes. |
|
|
Decorator that produces an |
sqlalchemy.orm.
registry
(metadata=None, class_registry=None, constructor=<function _declarative_constructor>, _bind=None)¶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 the
declarative_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 a
Mapper
for a class without scanning the class for
declarative class attributes. This method suits the use case historically
provided by the
mapper()
classical mapping function.
New in version 1.4.
See also
Mapping Python Classes - overview of class mapping styles.
sqlalchemy.orm.registry.
__init__
(metadata=None, class_registry=None, constructor=<function _declarative_constructor>, _bind=None)¶Construct a new registry
metadata¶ – An optional MetaData
instance. All
Table
objects generated using declarative
table mapping will make use of this MetaData
collection. If this argument is left at its default of None
,
a blank MetaData
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. If None
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.
sqlalchemy.orm.registry.
as_declarative_base
(**kw)¶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(object):
@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 to registry.generate_base()
.
sqlalchemy.orm.registry.
configure
(cascade=False)¶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 the
MapperEvents.before_configured()
and
MapperEvents.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, the configure.cascade
flag
should be set to True
. 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
function configure_mappers()
function may be used to ensure
configuration is complete for all registry
objects in
memory. This is generally simpler to use and also predates the usage of
registry
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.
sqlalchemy.orm.registry.
dispose
(cascade=False)¶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-wide clear_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, their registry.dispose()
method will
also be called, if the dispose.cascade
flag
is set to True
; otherwise, an error is raised if those registries
were not already disposed.
New in version 1.4.0b2.
See also
sqlalchemy.orm.registry.
generate_base
(mapper=None, cls=<class 'object'>, name='Base', metaclass=<class 'sqlalchemy.orm.decl_api.DeclarativeMeta'>)¶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
The registry.generate_base()
method provides the
implementation for the declarative_base()
function, which
creates the registry
and base class all at once.
See the section Declarative Mapping for background and examples.
mapper¶ – An optional callable, defaults to mapper()
.
This function is used to generate new Mapper
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.
sqlalchemy.orm.registry.
map_declaratively
(cls: type) → Mapper¶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 from
registry.generate_base()
.
See the section Declarative Mapping for complete details and examples.
See also
registry.mapped()
- more common decorator interface
to this function.
sqlalchemy.orm.registry.
map_imperatively
(class_, local_table=None, **kw)¶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 classic
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 (a.k.a. Classical) Mappings for complete background and usage examples.
class_¶ – The class to be mapped. Corresponds to the
mapper.class_
parameter.
local_table¶ – the Table
or other
FromClause
object that is the subject of the mapping.
Corresponds to the
mapper.local_table
parameter.
**kw¶ – all other keyword arguments are passed to the
mapper()
function directly.
sqlalchemy.orm.registry.
mapped
(cls)¶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.
cls¶ – class to be mapped.
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.
sqlalchemy.orm.registry.
mappers
¶read only collection of all Mapper
objects.
sqlalchemy.orm.
declarative_base
(bind=None, metadata=None, mapper=None, cls=<class 'object'>, name='Base', constructor=<function _declarative_constructor>, class_registry=None, metaclass=<class 'sqlalchemy.orm.decl_api.DeclarativeMeta'>)¶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 appropriate mapper()
calls based on the
information provided declaratively in the class and any subclasses
of the class.
The declarative_base()
function is a shorthand version
of using the registry.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
and registry.generate_base()
for more details.
Changed in version 1.4: The declarative_base()
function is now a specialization of the more generic
registry
class. The function also moves to the
sqlalchemy.orm
package from the declarative.ext
package.
bind¶ –
An optional
Connectable
, will be assigned
the bind
attribute on the MetaData
instance.
Deprecated since version 1.4: The “bind” argument to declarative_base is deprecated and will be removed in SQLAlchemy 2.0.
metadata¶ – An optional MetaData
instance. All
Table
objects implicitly declared by
subclasses of the base will share this MetaData. A MetaData instance
will be created if none is provided. The
MetaData
instance will be available via the
metadata
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. If None
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.
metaclass¶ – Defaults to DeclarativeMeta
. A metaclass or __metaclass__
compatible callable to use as the meta type of the generated
declarative base class.
See also
sqlalchemy.orm.
declarative_mixin
(cls)¶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.
sqlalchemy.orm.
as_declarative
(**kw)¶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 a registry
automatically
and then invoking the decorator.
E.g.:
from sqlalchemy.orm import as_declarative
@as_declarative()
class Base(object):
@declared_attr
def __tablename__(cls):
return cls.__name__.lower()
id = Column(Integer, primary_key=True)
class MyMappedClass(Base):
# ...
See also
sqlalchemy.orm.
declared_attr
(fget, cascading=False, _is_dataclass=False)¶Mark a class-level method as representing the definition of a mapped property or special declarative member name.
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 these declared_attr
callables as it scans classe,
and assumes any attribute marked with declared_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 is also used to define Column
objects that
include the ForeignKey
construct, as these cannot be
easily reused across different mappings. The example below illustrates
both:
class ProvidesUser(object):
"A mixin that adds a 'user' relationship to classes."
@declared_attr
def user_id(self):
return Column(ForeignKey("user_account.id"))
@declared_attr
def user(self):
return relationship("User")
declared_attr
can also be applied to mapped classes, such as
to provide a “polymorphic” scheme for inheritance:
class Employee(Base):
id = Column(Integer, primary_key=True)
type = Column(String(50), nullable=False)
@declared_attr
def __tablename__(cls):
return cls.__name__.lower()
@declared_attr
def __mapper_args__(cls):
if cls.__name__ == 'Employee':
return {
"polymorphic_on":cls.type,
"polymorphic_identity":"Employee"
}
else:
return {"polymorphic_identity":cls.__name__}
To use declared_attr
inside of a Python dataclass
as discussed at Example Two - Dataclasses with Declarative Table,
it may be placed directly inside the field metadata using a lambda:
@dataclass
class AddressMixin:
__sa_dataclass_metadata_key__ = "sa"
user_id: int = field(
init=False, metadata={"sa": declared_attr(lambda: Column(ForeignKey("user.id")))}
)
user: User = field(
init=False, metadata={"sa": declared_attr(lambda: relationship(User))}
)
declared_attr
also may be omitted from this form using a
lambda directly, as in:
user: User = field(
init=False, metadata={"sa": lambda: relationship(User)}
)
See also
Composing Mapped Hierarchies with Mixins - illustrates how to use Declarative Mixins
which is the primary use case for declared_attr
Using Declarative Mixins with Dataclasses - illustrates special forms for use with Python dataclasses
Class signature
class sqlalchemy.orm.declared_attr
(sqlalchemy.orm.base._MappedAttribute
, builtins.property
)
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(object):
@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 own id
column as well as that of
MyClass
underneath the attribute named some_id
.
sqlalchemy.orm.
has_inherited_table
(cls)¶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.
sqlalchemy.orm.
synonym_for
(name, map_column=False)¶Decorator that produces an synonym()
attribute in conjunction with a Python descriptor.
The function being decorated is passed to synonym()
as the
synonym.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 function
Using Descriptors and Hybrids - The Hybrid Attribute extension provides an updated approach to augmenting attribute behavior more flexibly than can be achieved with synonyms.
sqlalchemy.orm.
mapper
(class_, local_table=None, properties=None, primary_key=None, non_primary=False, inherits=None, inherit_condition=None, inherit_foreign_keys=None, always_refresh=False, version_id_col=None, version_id_generator=None, polymorphic_on=None, _polymorphic_map=None, polymorphic_identity=None, concrete=False, with_polymorphic=None, polymorphic_load=None, allow_partial_pks=True, batch=True, column_prefix=None, include_properties=None, exclude_properties=None, passive_updates=True, passive_deletes=False, confirm_deleted_rows=True, eager_defaults=False, legacy_is_orphan=False, _compiled_cache_size=100)¶Direct constructor for a new Mapper
object.
The mapper()
function is normally invoked through the
use of the registry
object through either the
Declarative or
Imperative mapping styles.
Changed in version 1.4: The mapper()
function should not
be called directly for classical mapping; for a classical mapping
configuration, use the registry.map_imperatively()
method. The mapper()
function may become private in a
future release.
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.
class_¶ – The class to be mapped. When using Declarative, this argument is automatically passed as the declared class itself.
local_table¶ – The Table
or other selectable
to which the class is mapped. May be None
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 the __table__
argument or via the
Table
produced as a result of the __tablename__
and Column
arguments present.
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 a
MapperEvents
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 affect explicitly specified
column-based properties.
See the section Naming All Columns with a Prefix for an example.
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.
New in version 0.9.4: - added
mapper.confirm_deleted_rows
as well as conditional
matched row checking on delete.
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. By default,
this scheme will emit an individual SELECT
statement per row
inserted or updated, which note can add significant performance
overhead. However, if the
target database supports RETURNING, the default values will
be returned inline with the INSERT or UPDATE statement, which can
greatly enhance performance for an application that needs frequent
access to just-generated server defaults.
See also
Changed in version 0.9.0: The eager_defaults
option can now
make use of RETURNING for backends which support it.
exclude_properties¶ –
A list or set of string column names to be excluded from mapping.
See Mapping a Subset of Table Columns for an example.
include_properties¶ –
An inclusive list or set of string column names to map.
See Mapping a Subset of Table Columns for an example.
inherits¶ –
A mapped class or the corresponding
Mapper
of one indicating a superclass to which this Mapper
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 a ForeignKey
configuration, this parameter can be used to specify which columns
are “foreign”. In most cases can be left as None
.
legacy_is_orphan¶ –
Boolean, defaults to False
.
When True
, 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 owning Session
only when it is de-associated
from all parents that specify a delete-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 specify delete-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¶ –
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 the AliasedClass
construct, which can also be used as the target of a relationship()
in 1.3.
See also
Relationship to Aliased Class - the new pattern that removes
the need for the Mapper.non_primary
flag.
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 to False
unless the value is set to True
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.
New in version 1.1.
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 mappers
passive_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 mappers
polymorphic_load¶ –
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.
This value is commonly a Column
object that’s
present in the mapped Table
:
class Employee(Base):
__tablename__ = 'employee'
id = Column(Integer, primary_key=True)
discriminator = 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 = Column(Integer, primary_key=True)
discriminator = 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
configured with column_property()
, or to the
string name of one:
class Employee(Base):
__tablename__ = 'employee'
id = Column(Integer, primary_key=True)
discriminator = Column(String(50))
employee_type = column_property(
case([
(discriminator == "EN", "engineer"),
(discriminator == "MA", "manager"),
], else_="employee")
)
__mapper_args__ = {
"polymorphic_on":employee_type,
"polymorphic_identity":"employee"
}
When setting polymorphic_on
to reference an
attribute or expression that’s not present in the
locally mapped Table
, 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 the discriminator
attribute,
thus persisting the value to the discriminator
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 polymorphic_on
setting. As rows are received, the value corresponding
to the 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 that
Column
objects present in
the mapped Table
are automatically placed into
ColumnProperty
instances upon mapping, unless overridden.
When using Declarative, this argument is passed automatically,
based on all those MapperProperty
instances declared
in the declared class body.
primary_key¶ – A list of Column
objects which define
the primary key to be used against this mapper’s selectable unit.
This is normally simply the primary key of the local_table
, but
can be overridden here.
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, a
StaleDataError
exception is
thrown.
By default, the column must be of Integer
type,
unless version_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.
New in version 0.9.0: version_id_generator
supports
server-side version number generation.
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.
See also
Using with_polymorphic - discussion of polymorphic querying techniques.
sqlalchemy.orm.
object_mapper
(instance)¶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.
sqlalchemy.orm.
class_mapper
(class_, configure=True)¶Given a class, return the primary Mapper
associated
with the key.
Raises UnmappedClassError
if no mapping is configured
on the given class, or ArgumentError
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.
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 the
MapperEvents.before_configured()
and
MapperEvents.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 the registry
involving the target mapper and any related
registry
objects which it may depend on; this is
equivalent to invoking the registry.configure()
method
on a particular registry
.
By contrast, the configure_mappers()
function will invoke the
configuration process on all registry
objects that
exist in memory, and may be useful for scenarios where many individual
registry
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 all registry
objects present and invoking the registry.configure()
method
on each. The registry.configure()
method may be preferred to
limit the configuration of mappers to those local to a particular
registry
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()
or Session.execute()
with an ORM-enabled statement.
The mapper configure process, whether invoked by
configure_mappers()
or from registry.configure()
,
provides several event hooks that can be used to augment the mapper
configuration step. These hooks include:
MapperEvents.before_configured()
- called once before
configure_mappers()
or registry.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 individual
Mapper
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 after
configure_mappers()
or registry.configure()
is
complete; at this stage, all Mapper
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 other registry
collections not part of the
current scope of configuration.
sqlalchemy.orm.
clear_mappers
()¶Remove all mappers from all classes.
Changed in version 1.4: This function now locates all
registry
objects and calls upon the
registry.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.
sqlalchemy.orm.util.
identity_key
(*args, **kwargs)¶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)
mapped class (must be a positional argument)
primary key, may be a scalar or tuple argument.
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.
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
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)
mapped class (must be a positional argument)
Row
row returned by a CursorResult
(must be given as a keyword arg)
optional identity token
New in version 1.2: added identity_token
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.
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.
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.
sqlalchemy.orm.
Mapper
(class_, local_table=None, properties=None, primary_key=None, non_primary=False, inherits=None, inherit_condition=None, inherit_foreign_keys=None, always_refresh=False, version_id_col=None, version_id_generator=None, polymorphic_on=None, _polymorphic_map=None, polymorphic_identity=None, concrete=False, with_polymorphic=None, polymorphic_load=None, allow_partial_pks=True, batch=True, column_prefix=None, include_properties=None, exclude_properties=None, passive_updates=True, passive_deletes=False, confirm_deleted_rows=True, eager_defaults=False, legacy_is_orphan=False, _compiled_cache_size=100)¶Define the correlation of class attributes to database table columns.
The Mapper
object is instantiated using the
mapper()
function. For information
about instantiating new Mapper
objects, see
that function’s documentation.
When mapper()
is used
explicitly to link a user defined class with table
metadata, this is referred to as classical mapping.
Modern SQLAlchemy usage tends to favor the
sqlalchemy.ext.declarative
extension for class
configuration, which
makes usage of mapper()
behind the scenes.
Given a particular class known to be mapped by the ORM,
the Mapper
which maintains it can be acquired
using the inspect()
function:
from sqlalchemy import inspect
mapper = inspect(MyClass)
A class which was mapped by the sqlalchemy.ext.declarative
extension will also have its mapper available via the __mapper__
attribute.
Class signature
class sqlalchemy.orm.Mapper
(sqlalchemy.orm.ORMFromClauseRole
, sqlalchemy.orm.ORMEntityColumnsClauseRole
, sqlalchemy.sql.traversals.MemoizedHasCacheKey
, sqlalchemy.orm.base.InspectionAttr
)
sqlalchemy.orm.Mapper.
__init__
(class_, local_table=None, properties=None, primary_key=None, non_primary=False, inherits=None, inherit_condition=None, inherit_foreign_keys=None, always_refresh=False, version_id_col=None, version_id_generator=None, polymorphic_on=None, _polymorphic_map=None, polymorphic_identity=None, concrete=False, with_polymorphic=None, polymorphic_load=None, allow_partial_pks=True, batch=True, column_prefix=None, include_properties=None, exclude_properties=None, passive_updates=True, passive_deletes=False, confirm_deleted_rows=True, eager_defaults=False, legacy_is_orphan=False, _compiled_cache_size=100)¶Construct a new Mapper
object.
This constructor is mirrored as a public API function; see sqlalchemy.orm.mapper()
for a full usage and argument description.
sqlalchemy.orm.Mapper.
add_properties
(dict_of_properties)¶Add the given dictionary of properties to this mapper, using add_property.
sqlalchemy.orm.Mapper.
add_property
(key, prop)¶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.
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 includes
QueryableAttribute
, as well as extension types such as
hybrid_property
, hybrid_method
and
AssociationProxy
.
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
, the
QueryableAttribute.property
attribute refers to the
MapperProperty
property, which is what you get when
referring to the collection of mapped properties via
Mapper.attrs
.
Warning
The Mapper.all_orm_descriptors
accessor namespace is an
instance of OrderedProperties
. This is
a dictionary-like object which includes a small number of
named methods such as OrderedProperties.items()
and OrderedProperties.values()
. When
accessing attributes dynamically, favor using the dict-access
scheme, e.g. mapper.all_orm_descriptors[somename]
over
getattr(mapper.all_orm_descriptors, somename)
to avoid name
collisions.
See also
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 has User.name
attribute would
provide mapper.attrs.name
, which would be the
ColumnProperty
representing the name
column. The namespace object can also be iterated,
which would yield each MapperProperty
.
Mapper
has several pre-filtered views
of this attribute which limit the types of properties
returned, including synonyms
, column_attrs
,
relationships
, and composites
.
Warning
The Mapper.attrs
accessor namespace is an
instance of OrderedProperties
. This is
a dictionary-like object which includes a small number of
named methods such as OrderedProperties.items()
and OrderedProperties.values()
. When
accessing attributes dynamically, favor using the dict-access
scheme, e.g. mapper.attrs[somename]
over
getattr(mapper.attrs, somename)
to avoid name collisions.
See also
sqlalchemy.orm.Mapper.
base_mapper
= None¶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
the Mapper
which is parent to all other Mapper
objects in the inheritance chain.
This is a read only attribute determined during mapper construction. Behavior is undefined if directly modified.
sqlalchemy.orm.Mapper.
c
= None¶A synonym for Mapper.columns
.
sqlalchemy.orm.Mapper.
cascade_iterator
(type_, state, halt_on=None)¶Iterate each element and its mapper in an object graph, for all relationships that meet the given cascade rule.
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.
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.
sqlalchemy.orm.Mapper.
class_
= None¶The Python class which this Mapper
maps.
This is a read only attribute determined during mapper construction. Behavior is undefined if directly modified.
sqlalchemy.orm.Mapper.
class_manager
= None¶The ClassManager
which maintains event listeners
and class-bound descriptors for this Mapper
.
This is a read only attribute determined during mapper construction. Behavior is undefined if directly modified.
sqlalchemy.orm.Mapper.
column_attrs
¶Return a namespace of all ColumnProperty
properties maintained by this Mapper
.
See also
Mapper.attrs
- namespace of all
MapperProperty
objects.
sqlalchemy.orm.Mapper.
columns
= None¶A collection of Column
or other scalar expression
objects maintained by this Mapper
.
The collection behaves the same as that of the c
attribute on
any Table
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 the key
attribute of the
Column
itself. Additionally, scalar expressions mapped
by column_property()
are also present here.
This is a read only attribute determined during mapper construction. Behavior is undefined if directly modified.
sqlalchemy.orm.Mapper.
common_parent
(other)¶Return true if the given mapper shares a common inherited parent as this mapper.
sqlalchemy.orm.Mapper.
composites
¶Return a namespace of all CompositeProperty
properties maintained by this Mapper
.
See also
Mapper.attrs
- namespace of all
MapperProperty
objects.
sqlalchemy.orm.Mapper.
concrete
= None¶Represent True
if this Mapper
is a concrete
inheritance mapper.
This is a read only attribute determined during mapper construction. Behavior is undefined if directly modified.
sqlalchemy.orm.Mapper.
configured
= False¶Represent True
if this Mapper
has been configured.
This is a read only attribute determined during mapper construction. Behavior is undefined if directly modified.
See also
sqlalchemy.orm.Mapper.
entity
¶Part of the inspection API.
Returns self.class_.
sqlalchemy.orm.Mapper.
get_property
(key, _configure_mappers=True)¶return a MapperProperty associated with the given key.
sqlalchemy.orm.Mapper.
get_property_by_column
(column)¶Given a Column
object, return the
MapperProperty
which maps this column.
sqlalchemy.orm.Mapper.
identity_key_from_instance
(instance)¶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.
sqlalchemy.orm.Mapper.
identity_key_from_primary_key
(primary_key, identity_token=None)¶Return an identity-map key for use in storing/retrieving an item from an identity map.
primary_key¶ – A list of values indicating the identifier.
sqlalchemy.orm.Mapper.
identity_key_from_row
(row, identity_token=None, adapter=None)¶Return an identity-map key for use in storing/retrieving an item from the identity map.
sqlalchemy.orm.Mapper.
inherits
= None¶References the Mapper
which this Mapper
inherits from, if any.
This is a read only attribute determined during mapper construction. Behavior is undefined if directly modified.
sqlalchemy.orm.Mapper.
is_mapper
= True¶Part of the inspection API.
sqlalchemy.orm.Mapper.
is_sibling
(other)¶return true if the other mapper is an inheriting sibling to this one. common parent but different branch
sqlalchemy.orm.Mapper.
isa
(other)¶Return True if the this mapper inherits from the given mapper.
sqlalchemy.orm.Mapper.
iterate_properties
¶return an iterator of all MapperProperty objects.
sqlalchemy.orm.Mapper.
local_table
= None¶The Selectable
which this Mapper
manages.
Typically is an instance of Table
or
Alias
.
May also be None
.
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, the local table is the same as the
“mapped” table. For joined-table inheritance mappers, local_table
will be the particular sub-table of the overall “join” which
this Mapper
represents. If this mapper is a
single-table inheriting mapper, local_table will be None
.
See also
sqlalchemy.orm.Mapper.
mapped_table
¶Deprecated since version 1.3: Use .persist_selectable
sqlalchemy.orm.Mapper.
mapper
¶Part of the inspection API.
Returns self.
sqlalchemy.orm.Mapper.
non_primary
= None¶Represent True
if this Mapper
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.
sqlalchemy.orm.Mapper.
persist_selectable
= None¶The Selectable
to which this Mapper
is mapped.
Typically an instance of Table
,
Join
, or Alias
.
The Mapper.persist_selectable
is separate from
Mapper.selectable
in that the former represents columns
that are mapped on this class or its superclasses, whereas the
latter may be a “polymorphic” selectable that contains additional columns
which are in fact mapped on subclasses only.
“persist selectable” is the “thing the mapper writes to” and “selectable” is the “thing the mapper selects from”.
Mapper.persist_selectable
is also separate from
Mapper.local_table
, which represents the set of columns that
are locally mapped on this class directly.
sqlalchemy.orm.Mapper.
polymorphic_identity
= None¶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.
sqlalchemy.orm.Mapper.
polymorphic_iterator
()¶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()
.
sqlalchemy.orm.Mapper.
polymorphic_map
= None¶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.
sqlalchemy.orm.Mapper.
polymorphic_on
= None¶The Column
or SQL expression specified as the
polymorphic_on
argument
for this Mapper
, within an inheritance scenario.
This attribute is normally a Column
instance but
may also be an expression, such as one derived from
cast()
.
This is a read only attribute determined during mapper construction. Behavior is undefined if directly modified.
sqlalchemy.orm.Mapper.
primary_key
= None¶An iterable containing the collection of Column
objects
which comprise the ‘primary key’ of the mapped table, from the
perspective of this Mapper
.
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 a
Join
, the
primary key is determined by all of the primary key columns across all
tables referenced by the Join
.
The list is also not necessarily the same as the primary key column
collection associated with the underlying tables; the Mapper
features a primary_key
argument that can override what the
Mapper
considers as primary key columns.
This is a read only attribute determined during mapper construction. Behavior is undefined if directly modified.
sqlalchemy.orm.Mapper.
primary_key_from_instance
(instance)¶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.
sqlalchemy.orm.Mapper.
primary_mapper
()¶Return the primary mapper corresponding to this mapper’s class key (class).
sqlalchemy.orm.Mapper.
relationships
¶A namespace of all RelationshipProperty
properties
maintained by this Mapper
.
Warning
the Mapper.relationships
accessor namespace is an
instance of OrderedProperties
. This is
a dictionary-like object which includes a small number of
named methods such as OrderedProperties.items()
and OrderedProperties.values()
. When
accessing attributes dynamically, favor using the dict-access
scheme, e.g. mapper.relationships[somename]
over
getattr(mapper.relationships, somename)
to avoid name
collisions.
See also
Mapper.attrs
- namespace of all
MapperProperty
objects.
sqlalchemy.orm.Mapper.
selectable
¶The FromClause
construct this
Mapper
selects from by default.
Normally, this is equivalent to persist_selectable
, unless
the with_polymorphic
feature is in use, in which case the
full “polymorphic” selectable is returned.
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.
sqlalchemy.orm.Mapper.
single
= None¶Represent True
if this Mapper
is a single table
inheritance mapper.
Mapper.local_table
will be None
if this flag is set.
This is a read only attribute determined during mapper construction. Behavior is undefined if directly modified.
sqlalchemy.orm.Mapper.
synonyms
¶Return a namespace of all SynonymProperty
properties maintained by this Mapper
.
See also
Mapper.attrs
- namespace of all
MapperProperty
objects.
sqlalchemy.orm.Mapper.
tables
= None¶An iterable containing the collection of Table
objects
which this Mapper
is aware of.
If the mapper is mapped to a Join
, or an
Alias
representing a Select
, the individual
Table
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.
sqlalchemy.orm.Mapper.
validators
= None¶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.
sqlalchemy.orm.Mapper.
with_polymorphic_mappers
¶The list of Mapper
objects included in the
default “polymorphic” query.
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