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|
# ext/declarative/api.py
# Copyright (C) 2005-2022 the SQLAlchemy authors and contributors
# <see AUTHORS file>
#
# This module is part of SQLAlchemy and is released under
# the MIT License: https://www.opensource.org/licenses/mit-license.php
"""Public API functions and helpers for declarative."""
from __future__ import absolute_import
import itertools
import re
import weakref
from . import attributes
from . import clsregistry
from . import exc as orm_exc
from . import instrumentation
from . import interfaces
from . import mapper as mapperlib
from .base import _inspect_mapped_class
from .decl_base import _add_attribute
from .decl_base import _as_declarative
from .decl_base import _declarative_constructor
from .decl_base import _DeferredMapperConfig
from .decl_base import _del_attribute
from .decl_base import _mapper
from .descriptor_props import SynonymProperty as _orm_synonym
from .. import exc
from .. import inspection
from .. import util
from ..sql.schema import MetaData
from ..util import hybridmethod
from ..util import hybridproperty
def 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.
.. seealso::
:ref:`decl_mixin_inheritance`
"""
for class_ in cls.__mro__[1:]:
if getattr(class_, "__table__", None) is not None:
return True
return False
class DeclarativeMeta(type):
def __init__(cls, classname, bases, dict_, **kw):
# use cls.__dict__, which can be modified by an
# __init_subclass__() method (#7900)
dict_ = cls.__dict__
# early-consume registry from the initial declarative base,
# assign privately to not conflict with subclass attributes named
# "registry"
reg = getattr(cls, "_sa_registry", None)
if reg is None:
reg = dict_.get("registry", None)
if not isinstance(reg, registry):
raise exc.InvalidRequestError(
"Declarative base class has no 'registry' attribute, "
"or registry is not a sqlalchemy.orm.registry() object"
)
else:
cls._sa_registry = reg
if not cls.__dict__.get("__abstract__", False):
_as_declarative(reg, cls, dict_)
type.__init__(cls, classname, bases, dict_)
def __setattr__(cls, key, value):
_add_attribute(cls, key, value)
def __delattr__(cls, key):
_del_attribute(cls, key)
def synonym_for(name, map_column=False):
"""Decorator that produces an :func:`_orm.synonym`
attribute in conjunction with a Python descriptor.
The function being decorated is passed to :func:`_orm.synonym` as the
:paramref:`.orm.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 :ref:`hybrid properties <mapper_hybrids>` feature of SQLAlchemy
is typically preferred instead of synonyms, which is a more legacy
feature.
.. seealso::
:ref:`synonyms` - Overview of synonyms
:func:`_orm.synonym` - the mapper-level function
:ref:`mapper_hybrids` - The Hybrid Attribute extension provides an
updated approach to augmenting attribute behavior more flexibly than
can be achieved with synonyms.
"""
def decorate(fn):
return _orm_synonym(name, map_column=map_column, descriptor=fn)
return decorate
class declared_attr(interfaces._MappedAttribute, property):
"""Mark a class-level method as representing the definition of
a mapped property or special declarative member name.
:class:`_orm.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 :class:`_orm.declared_attr` callables as it scans classes,
and assumes any attribute marked with :class:`_orm.declared_attr` will be a
callable that will produce an object specific to the Declarative mapping or
table configuration.
:class:`_orm.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 :class:`_schema.Column` objects that
include the :class:`_schema.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")
:class:`_orm.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 :class:`_orm.declared_attr` inside of a Python dataclass
as discussed at :ref:`orm_declarative_dataclasses_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))}
)
:class:`_orm.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)}
)
.. seealso::
:ref:`orm_mixins_toplevel` - illustrates how to use Declarative Mixins
which is the primary use case for :class:`_orm.declared_attr`
:ref:`orm_declarative_dataclasses_mixin` - illustrates special forms
for use with Python dataclasses
""" # noqa: E501
def __init__(self, fget, cascading=False):
super(declared_attr, self).__init__(fget)
self.__doc__ = fget.__doc__
self._cascading = cascading
def __get__(desc, self, cls):
# the declared_attr needs to make use of a cache that exists
# for the span of the declarative scan_attributes() phase.
# to achieve this we look at the class manager that's configured.
manager = attributes.manager_of_class(cls)
if manager is None:
if not re.match(r"^__.+__$", desc.fget.__name__):
# if there is no manager at all, then this class hasn't been
# run through declarative or mapper() at all, emit a warning.
util.warn(
"Unmanaged access of declarative attribute %s from "
"non-mapped class %s" % (desc.fget.__name__, cls.__name__)
)
return desc.fget(cls)
elif manager.is_mapped:
# the class is mapped, which means we're outside of the declarative
# scan setup, just run the function.
return desc.fget(cls)
# here, we are inside of the declarative scan. use the registry
# that is tracking the values of these attributes.
declarative_scan = manager.declarative_scan()
assert declarative_scan is not None
reg = declarative_scan.declared_attr_reg
if desc in reg:
return reg[desc]
else:
reg[desc] = obj = desc.fget(cls)
return obj
@hybridmethod
def _stateful(cls, **kw):
return _stateful_declared_attr(**kw)
@hybridproperty
def cascading(cls):
"""Mark a :class:`.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 :attr:`.declared_attr.cascading` modifier has several
limitations:
* The flag **only** applies to the use of :class:`.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``.
.. seealso::
:ref:`declarative_inheritance`
:ref:`mixin_inheritance_columns`
"""
return cls._stateful(cascading=True)
class _stateful_declared_attr(declared_attr):
def __init__(self, **kw):
self.kw = kw
def _stateful(self, **kw):
new_kw = self.kw.copy()
new_kw.update(kw)
return _stateful_declared_attr(**new_kw)
def __call__(self, fn):
return declared_attr(fn, **self.kw)
def 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 :func:`_orm.declarative_mixin` decorator currently does not modify
the given class in any way; it's current purpose is strictly to assist
the :ref:`Mypy plugin <mypy_toplevel>` in being able to identify
SQLAlchemy declarative mixin classes when no other context is present.
.. versionadded:: 1.4.6
.. seealso::
:ref:`orm_mixins_toplevel`
:ref:`mypy_declarative_mixins` - in the
:ref:`Mypy plugin documentation <mypy_toplevel>`
""" # noqa: E501
return cls
def declarative_base(
bind=None,
metadata=None,
mapper=None,
cls=object,
name="Base",
constructor=_declarative_constructor,
class_registry=None,
metaclass=DeclarativeMeta,
):
r"""Construct a base class for declarative class definitions.
The new base class will be given a metaclass that produces
appropriate :class:`~sqlalchemy.schema.Table` objects and makes
the appropriate :func:`~sqlalchemy.orm.mapper` calls based on the
information provided declaratively in the class and any subclasses
of the class.
The :func:`_orm.declarative_base` function is a shorthand version
of using the :meth:`_orm.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 :class:`_orm.registry`
and :meth:`_orm.registry.generate_base`
for more details.
.. versionchanged:: 1.4 The :func:`_orm.declarative_base`
function is now a specialization of the more generic
:class:`_orm.registry` class. The function also moves to the
``sqlalchemy.orm`` package from the ``declarative.ext`` package.
:param bind: An optional
:class:`~sqlalchemy.engine.Connectable`, will be assigned
the ``bind`` attribute on the :class:`~sqlalchemy.schema.MetaData`
instance.
.. deprecated:: 1.4 The "bind" argument to declarative_base is
deprecated and will be removed in SQLAlchemy 2.0.
:param metadata:
An optional :class:`~sqlalchemy.schema.MetaData` instance. All
:class:`~sqlalchemy.schema.Table` objects implicitly declared by
subclasses of the base will share this MetaData. A MetaData instance
will be created if none is provided. The
:class:`~sqlalchemy.schema.MetaData` instance will be available via the
``metadata`` attribute of the generated declarative base class.
:param mapper:
An optional callable, defaults to :func:`~sqlalchemy.orm.mapper`. Will
be used to map subclasses to their Tables.
:param cls:
Defaults to :class:`object`. A type to use as the base for the generated
declarative base class. May be a class or tuple of classes.
:param name:
Defaults to ``Base``. The display name for the generated
class. Customizing this is not required, but can improve clarity in
tracebacks and debugging.
:param 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.
:param 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 :func:`_orm.relationship`
and others. Allows two or more declarative base classes
to share the same registry of class names for simplified
inter-base relationships.
:param metaclass:
Defaults to :class:`.DeclarativeMeta`. A metaclass or __metaclass__
compatible callable to use as the meta type of the generated
declarative base class.
.. seealso::
:class:`_orm.registry`
"""
if bind is not None:
# util.deprecated_params does not work
util.warn_deprecated_20(
"The ``bind`` argument to declarative_base is "
"deprecated and will be removed in SQLAlchemy 2.0.",
)
return registry(
_bind=bind,
metadata=metadata,
class_registry=class_registry,
constructor=constructor,
).generate_base(
mapper=mapper,
cls=cls,
name=name,
metaclass=metaclass,
)
class registry(object):
"""Generalized registry for mapping classes.
The :class:`_orm.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:
* :meth:`_orm.registry.generate_base` returns a new declarative base
class, and is the underlying implementation of the
:func:`_orm.declarative_base` function.
* :meth:`_orm.registry.mapped` provides a class decorator that will
apply declarative mapping to a class without the use of a declarative
base class.
* :meth:`_orm.registry.map_imperatively` will produce a
:class:`_orm.Mapper` for a class without scanning the class for
declarative class attributes. This method suits the use case historically
provided by the
:func:`_orm.mapper` classical mapping function.
.. versionadded:: 1.4
.. seealso::
:ref:`orm_mapping_classes_toplevel` - overview of class mapping
styles.
"""
def __init__(
self,
metadata=None,
class_registry=None,
constructor=_declarative_constructor,
_bind=None,
):
r"""Construct a new :class:`_orm.registry`
:param metadata:
An optional :class:`_schema.MetaData` instance. All
:class:`_schema.Table` objects generated using declarative
table mapping will make use of this :class:`_schema.MetaData`
collection. If this argument is left at its default of ``None``,
a blank :class:`_schema.MetaData` collection is created.
:param 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.
:param 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 :func:`_orm.relationship`
and others. Allows two or more declarative base classes
to share the same registry of class names for simplified
inter-base relationships.
"""
lcl_metadata = metadata or MetaData()
if _bind:
lcl_metadata.bind = _bind
if class_registry is None:
class_registry = weakref.WeakValueDictionary()
self._class_registry = class_registry
self._managers = weakref.WeakKeyDictionary()
self._non_primary_mappers = weakref.WeakKeyDictionary()
self.metadata = lcl_metadata
self.constructor = constructor
self._dependents = set()
self._dependencies = set()
self._new_mappers = False
with mapperlib._CONFIGURE_MUTEX:
mapperlib._mapper_registries[self] = True
@property
def mappers(self):
"""read only collection of all :class:`_orm.Mapper` objects."""
return frozenset(manager.mapper for manager in self._managers).union(
self._non_primary_mappers
)
def _set_depends_on(self, registry):
if registry is self:
return
registry._dependents.add(self)
self._dependencies.add(registry)
def _flag_new_mapper(self, mapper):
mapper._ready_for_configure = True
if self._new_mappers:
return
for reg in self._recurse_with_dependents({self}):
reg._new_mappers = True
@classmethod
def _recurse_with_dependents(cls, registries):
todo = registries
done = set()
while todo:
reg = todo.pop()
done.add(reg)
# if yielding would remove dependents, make sure we have
# them before
todo.update(reg._dependents.difference(done))
yield reg
# if yielding would add dependents, make sure we have them
# after
todo.update(reg._dependents.difference(done))
@classmethod
def _recurse_with_dependencies(cls, registries):
todo = registries
done = set()
while todo:
reg = todo.pop()
done.add(reg)
# if yielding would remove dependencies, make sure we have
# them before
todo.update(reg._dependencies.difference(done))
yield reg
# if yielding would remove dependencies, make sure we have
# them before
todo.update(reg._dependencies.difference(done))
def _mappers_to_configure(self):
return itertools.chain(
(
manager.mapper
for manager in list(self._managers)
if manager.is_mapped
and not manager.mapper.configured
and manager.mapper._ready_for_configure
),
(
npm
for npm in list(self._non_primary_mappers)
if not npm.configured and npm._ready_for_configure
),
)
def _add_non_primary_mapper(self, np_mapper):
self._non_primary_mappers[np_mapper] = True
def _dispose_cls(self, cls):
clsregistry.remove_class(cls.__name__, cls, self._class_registry)
def _add_manager(self, manager):
self._managers[manager] = True
if manager.registry is not None and manager.is_mapped:
raise exc.ArgumentError(
"Class '%s' already has a primary mapper defined. "
% manager.class_
)
manager.registry = self
def configure(self, cascade=False):
"""Configure all as-yet unconfigured mappers in this
:class:`_orm.registry`.
The configure step is used to reconcile and initialize the
:func:`_orm.relationship` linkages between mapped classes, as well as
to invoke configuration events such as the
:meth:`_orm.MapperEvents.before_configured` and
:meth:`_orm.MapperEvents.after_configured`, which may be used by ORM
extensions or user-defined extension hooks.
If one or more mappers in this registry contain
:func:`_orm.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 :paramref:`_orm.registry.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 :meth:`_orm.registry.configure`, the ORM
function :func:`_orm.configure_mappers` function may be used to ensure
configuration is complete for all :class:`_orm.registry` objects in
memory. This is generally simpler to use and also predates the usage of
:class:`_orm.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.
.. seealso::
:func:`_orm.configure_mappers`
.. versionadded:: 1.4.0b2
"""
mapperlib._configure_registries({self}, cascade=cascade)
def dispose(self, cascade=False):
"""Dispose of all mappers in this :class:`_orm.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-:class:`_orm.registry` analogue to the
application-wide :func:`_orm.clear_mappers` function.
If this registry contains mappers that are dependencies of other
registries, typically via :func:`_orm.relationship` links, then those
registries must be disposed as well. When such registries exist in
relation to this one, their :meth:`_orm.registry.dispose` method will
also be called, if the :paramref:`_orm.registry.dispose.cascade` flag
is set to ``True``; otherwise, an error is raised if those registries
were not already disposed.
.. versionadded:: 1.4.0b2
.. seealso::
:func:`_orm.clear_mappers`
"""
mapperlib._dispose_registries({self}, cascade=cascade)
def _dispose_manager_and_mapper(self, manager):
if "mapper" in manager.__dict__:
mapper = manager.mapper
mapper._set_dispose_flags()
class_ = manager.class_
self._dispose_cls(class_)
instrumentation._instrumentation_factory.unregister(class_)
def generate_base(
self,
mapper=None,
cls=object,
name="Base",
metaclass=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
__init__ = mapper_registry.constructor
The :meth:`_orm.registry.generate_base` method provides the
implementation for the :func:`_orm.declarative_base` function, which
creates the :class:`_orm.registry` and base class all at once.
See the section :ref:`orm_declarative_mapping` for background and
examples.
:param mapper:
An optional callable, defaults to :func:`~sqlalchemy.orm.mapper`.
This function is used to generate new :class:`_orm.Mapper` objects.
:param cls:
Defaults to :class:`object`. A type to use as the base for the
generated declarative base class. May be a class or tuple of classes.
:param name:
Defaults to ``Base``. The display name for the generated
class. Customizing this is not required, but can improve clarity in
tracebacks and debugging.
:param metaclass:
Defaults to :class:`.DeclarativeMeta`. A metaclass or __metaclass__
compatible callable to use as the meta type of the generated
declarative base class.
.. seealso::
:ref:`orm_declarative_mapping`
:func:`_orm.declarative_base`
"""
metadata = self.metadata
bases = not isinstance(cls, tuple) and (cls,) or cls
class_dict = dict(registry=self, metadata=metadata)
if isinstance(cls, type):
class_dict["__doc__"] = cls.__doc__
if self.constructor:
class_dict["__init__"] = self.constructor
class_dict["__abstract__"] = True
if mapper:
class_dict["__mapper_cls__"] = mapper
if hasattr(cls, "__class_getitem__"):
def __class_getitem__(cls, key):
# allow generic classes in py3.9+
return cls
class_dict["__class_getitem__"] = __class_getitem__
return metaclass(name, bases, class_dict)
def mapped(self, 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 :ref:`orm_declarative_mapping` for complete
details and examples.
:param cls: class to be mapped.
:return: the class that was passed.
.. seealso::
:ref:`orm_declarative_mapping`
:meth:`_orm.registry.generate_base` - generates a base class
that will apply Declarative mapping to subclasses automatically
using a Python metaclass.
"""
_as_declarative(self, cls, cls.__dict__)
return cls
def as_declarative_base(self, **kw):
"""
Class decorator which will invoke
:meth:`_orm.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
:meth:`_orm.registry.as_declarative_base` are passed
along to :meth:`_orm.registry.generate_base`.
"""
def decorate(cls):
kw["cls"] = cls
kw["name"] = cls.__name__
return self.generate_base(**kw)
return decorate
def map_declaratively(self, cls):
"""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 :class:`_orm.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
:meth:`_orm.registry.mapped` class decorator or by subclassing a
declarative metaclass generated from
:meth:`_orm.registry.generate_base`.
See the section :ref:`orm_declarative_mapping` for complete
details and examples.
:param cls: class to be mapped.
:return: a :class:`_orm.Mapper` object.
.. seealso::
:ref:`orm_declarative_mapping`
:meth:`_orm.registry.mapped` - more common decorator interface
to this function.
:meth:`_orm.registry.map_imperatively`
"""
return _as_declarative(self, cls, cls.__dict__)
def map_imperatively(self, class_, local_table=None, **kw):
r"""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 :func:`_orm.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 :ref:`orm_imperative_mapping` for complete background
and usage examples.
:param class\_: The class to be mapped. Corresponds to the
:paramref:`_orm.mapper.class_` parameter.
:param local_table: the :class:`_schema.Table` or other
:class:`_sql.FromClause` object that is the subject of the mapping.
Corresponds to the
:paramref:`_orm.mapper.local_table` parameter.
:param \**kw: all other keyword arguments are passed to the
:func:`_orm.mapper` function directly.
.. seealso::
:ref:`orm_imperative_mapping`
:ref:`orm_declarative_mapping`
"""
return _mapper(self, class_, local_table, kw)
mapperlib._legacy_registry = registry()
@util.deprecated_params(
bind=(
"2.0",
"The ``bind`` argument to as_declarative is "
"deprecated and will be removed in SQLAlchemy 2.0.",
)
)
def as_declarative(**kw):
"""
Class decorator which will adapt a given class into a
:func:`_orm.declarative_base`.
This function makes use of the :meth:`_orm.registry.as_declarative_base`
method, by first creating a :class:`_orm.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):
# ...
.. seealso::
:meth:`_orm.registry.as_declarative_base`
"""
bind, metadata, class_registry = (
kw.pop("bind", None),
kw.pop("metadata", None),
kw.pop("class_registry", None),
)
return registry(
_bind=bind, metadata=metadata, class_registry=class_registry
).as_declarative_base(**kw)
@inspection._inspects(DeclarativeMeta)
def _inspect_decl_meta(cls):
mp = _inspect_mapped_class(cls)
if mp is None:
if _DeferredMapperConfig.has_cls(cls):
_DeferredMapperConfig.raise_unmapped_for_cls(cls)
raise orm_exc.UnmappedClassError(
cls,
msg="Class %s has a deferred mapping on it. It is not yet "
"usable as a mapped class." % orm_exc._safe_cls_name(cls),
)
return mp
|