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decl_base.py
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# orm/decl_base.py # Copyright (C) 2005-2024 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 """Internal implementation for declarative.""" from __future__ import annotations import collections import dataclasses import re from typing import Any from typing import Callable from typing import cast from typing import Dict from typing import Iterable from typing import List from typing import Mapping from typing import NamedTuple from typing import NoReturn from typing import Optional from typing import Sequence from typing import Tuple from typing import Type from typing import TYPE_CHECKING from typing import TypeVar from typing import Union import weakref from . import attributes from . import clsregistry from . import exc as orm_exc from . import instrumentation from . import mapperlib from ._typing import _O from ._typing import attr_is_internal_proxy from .attributes import InstrumentedAttribute from .attributes import QueryableAttribute from .base import _is_mapped_class from .base import InspectionAttr from .descriptor_props import CompositeProperty from .descriptor_props import SynonymProperty from .interfaces import _AttributeOptions from .interfaces import _DCAttributeOptions from .interfaces import _IntrospectsAnnotations from .interfaces import _MappedAttribute from .interfaces import _MapsColumns from .interfaces import MapperProperty from .mapper import Mapper from .properties import ColumnProperty from .properties import MappedColumn from .util import _extract_mapped_subtype from .util import _is_mapped_annotation from .util import class_mapper from .util import de_stringify_annotation from .. import event from .. import exc from .. import util from ..sql import expression from ..sql.base import _NoArg from ..sql.schema import Column from ..sql.schema import Table from ..util import topological from ..util.typing import _AnnotationScanType from ..util.typing import is_fwd_ref from ..util.typing import is_literal from ..util.typing import Protocol from ..util.typing import TypedDict from ..util.typing import typing_get_args if TYPE_CHECKING: from ._typing import _ClassDict from ._typing import _RegistryType from .base import Mapped from .decl_api import declared_attr from .instrumentation import ClassManager from ..sql.elements import NamedColumn from ..sql.schema import MetaData from ..sql.selectable import FromClause _T = TypeVar("_T", bound=Any) _MapperKwArgs = Mapping[str, Any] _TableArgsType = Union[Tuple[Any, ...], Dict[str, Any]] class MappedClassProtocol(Protocol[_O]): """A protocol representing a SQLAlchemy mapped class. The protocol is generic on the type of class, use ``MappedClassProtocol[Any]`` to allow any mapped class. """ __name__: str __mapper__: Mapper[_O] __table__: FromClause def __call__(self, **kw: Any) -> _O: ... class _DeclMappedClassProtocol(MappedClassProtocol[_O], Protocol): "Internal more detailed version of ``MappedClassProtocol``." metadata: MetaData __tablename__: str __mapper_args__: _MapperKwArgs __table_args__: Optional[_TableArgsType] _sa_apply_dc_transforms: Optional[_DataclassArguments] def __declare_first__(self) -> None: ... def __declare_last__(self) -> None: ... class _DataclassArguments(TypedDict): init: Union[_NoArg, bool] repr: Union[_NoArg, bool] eq: Union[_NoArg, bool] order: Union[_NoArg, bool] unsafe_hash: Union[_NoArg, bool] match_args: Union[_NoArg, bool] kw_only: Union[_NoArg, bool] dataclass_callable: Union[_NoArg, Callable[..., Type[Any]]] def _declared_mapping_info( cls: Type[Any], ) -> Optional[Union[_DeferredMapperConfig, Mapper[Any]]]: # deferred mapping if _DeferredMapperConfig.has_cls(cls): return _DeferredMapperConfig.config_for_cls(cls) # regular mapping elif _is_mapped_class(cls): return class_mapper(cls, configure=False) else: return None def _is_supercls_for_inherits(cls: Type[Any]) -> bool: """return True if this class will be used as a superclass to set in 'inherits'. This includes deferred mapper configs that aren't mapped yet, however does not include classes with _sa_decl_prepare_nocascade (e.g. ``AbstractConcreteBase``); these concrete-only classes are not set up as "inherits" until after mappers are configured using mapper._set_concrete_base() """ if _DeferredMapperConfig.has_cls(cls): return not _get_immediate_cls_attr( cls, "_sa_decl_prepare_nocascade", strict=True ) # regular mapping elif _is_mapped_class(cls): return True else: return False def _resolve_for_abstract_or_classical(cls: Type[Any]) -> Optional[Type[Any]]: if cls is object: return None sup: Optional[Type[Any]] if cls.__dict__.get("__abstract__", False): for base_ in cls.__bases__: sup = _resolve_for_abstract_or_classical(base_) if sup is not None: return sup else: return None else: clsmanager = _dive_for_cls_manager(cls) if clsmanager: return clsmanager.class_ else: return cls def _get_immediate_cls_attr( cls: Type[Any], attrname: str, strict: bool = False ) -> Optional[Any]: """return an attribute of the class that is either present directly on the class, e.g. not on a superclass, or is from a superclass but this superclass is a non-mapped mixin, that is, not a descendant of the declarative base and is also not classically mapped. This is used to detect attributes that indicate something about a mapped class independently from any mapped classes that it may inherit from. """ # the rules are different for this name than others, # make sure we've moved it out. transitional assert attrname != "__abstract__" if not issubclass(cls, object): return None if attrname in cls.__dict__: return getattr(cls, attrname) for base in cls.__mro__[1:]: _is_classical_inherits = _dive_for_cls_manager(base) is not None if attrname in base.__dict__ and ( base is cls or ( (base in cls.__bases__ if strict else True) and not _is_classical_inherits ) ): return getattr(base, attrname) else: return None def _dive_for_cls_manager(cls: Type[_O]) -> Optional[ClassManager[_O]]: # because the class manager registration is pluggable, # we need to do the search for every class in the hierarchy, # rather than just a simple "cls._sa_class_manager" for base in cls.__mro__: manager: Optional[ClassManager[_O]] = attributes.opt_manager_of_class( base ) if manager: return manager return None def _as_declarative( registry: _RegistryType, cls: Type[Any], dict_: _ClassDict ) -> Optional[_MapperConfig]: # declarative scans the class for attributes. no table or mapper # args passed separately. return _MapperConfig.setup_mapping(registry, cls, dict_, None, {}) def _mapper( registry: _RegistryType, cls: Type[_O], table: Optional[FromClause], mapper_kw: _MapperKwArgs, ) -> Mapper[_O]: _ImperativeMapperConfig(registry, cls, table, mapper_kw) return cast("MappedClassProtocol[_O]", cls).__mapper__ @util.preload_module("sqlalchemy.orm.decl_api") def _is_declarative_props(obj: Any) -> bool: _declared_attr_common = util.preloaded.orm_decl_api._declared_attr_common return isinstance(obj, (_declared_attr_common, util.classproperty)) def _check_declared_props_nocascade( obj: Any, name: str, cls: Type[_O] ) -> bool: if _is_declarative_props(obj): if getattr(obj, "_cascading", False): util.warn( "@declared_attr.cascading is not supported on the %s " "attribute on class %s. This attribute invokes for " "subclasses in any case." % (name, cls) ) return True else: return False class _MapperConfig: __slots__ = ( "cls", "classname", "properties", "declared_attr_reg", "__weakref__", ) cls: Type[Any] classname: str properties: util.OrderedDict[ str, Union[ Sequence[NamedColumn[Any]], NamedColumn[Any], MapperProperty[Any] ], ] declared_attr_reg: Dict[declared_attr[Any], Any] @classmethod def setup_mapping( cls, registry: _RegistryType, cls_: Type[_O], dict_: _ClassDict, table: Optional[FromClause], mapper_kw: _MapperKwArgs, ) -> Optional[_MapperConfig]: manager = attributes.opt_manager_of_class(cls) if manager and manager.class_ is cls_: raise exc.InvalidRequestError( f"Class {cls!r} already has been instrumented declaratively" ) if cls_.__dict__.get("__abstract__", False): return None defer_map = _get_immediate_cls_attr( cls_, "_sa_decl_prepare_nocascade", strict=True ) or hasattr(cls_, "_sa_decl_prepare") if defer_map: return _DeferredMapperConfig( registry, cls_, dict_, table, mapper_kw ) else: return _ClassScanMapperConfig( registry, cls_, dict_, table, mapper_kw ) def __init__( self, registry: _RegistryType, cls_: Type[Any], mapper_kw: _MapperKwArgs, ): self.cls = util.assert_arg_type(cls_, type, "cls_") self.classname = cls_.__name__ self.properties = util.OrderedDict() self.declared_attr_reg = {} if not mapper_kw.get("non_primary", False): instrumentation.register_class( self.cls, finalize=False, registry=registry, declarative_scan=self, init_method=registry.constructor, ) else: manager = attributes.opt_manager_of_class(self.cls) if not manager or not manager.is_mapped: raise exc.InvalidRequestError( "Class %s has no primary mapper configured. Configure " "a primary mapper first before setting up a non primary " "Mapper." % self.cls ) def set_cls_attribute(self, attrname: str, value: _T) -> _T: manager = instrumentation.manager_of_class(self.cls) manager.install_member(attrname, value) return value def map(self, mapper_kw: _MapperKwArgs = ...) -> Mapper[Any]: raise NotImplementedError() def _early_mapping(self, mapper_kw: _MapperKwArgs) -> None: self.map(mapper_kw) class _ImperativeMapperConfig(_MapperConfig): __slots__ = ("local_table", "inherits") def __init__( self, registry: _RegistryType, cls_: Type[_O], table: Optional[FromClause], mapper_kw: _MapperKwArgs, ): super().__init__(registry, cls_, mapper_kw) self.local_table = self.set_cls_attribute("__table__", table) with mapperlib._CONFIGURE_MUTEX: if not mapper_kw.get("non_primary", False): clsregistry.add_class( self.classname, self.cls, registry._class_registry ) self._setup_inheritance(mapper_kw) self._early_mapping(mapper_kw) def map(self, mapper_kw: _MapperKwArgs = util.EMPTY_DICT) -> Mapper[Any]: mapper_cls = Mapper return self.set_cls_attribute( "__mapper__", mapper_cls(self.cls, self.local_table, **mapper_kw), ) def _setup_inheritance(self, mapper_kw: _MapperKwArgs) -> None: cls = self.cls inherits = mapper_kw.get("inherits", None) if inherits is None: # since we search for classical mappings now, search for # multiple mapped bases as well and raise an error. inherits_search = [] for base_ in cls.__bases__: c = _resolve_for_abstract_or_classical(base_) if c is None: continue if _is_supercls_for_inherits(c) and c not in inherits_search: inherits_search.append(c) if inherits_search: if len(inherits_search) > 1: raise exc.InvalidRequestError( "Class %s has multiple mapped bases: %r" % (cls, inherits_search) ) inherits = inherits_search[0] elif isinstance(inherits, Mapper): inherits = inherits.class_ self.inherits = inherits class _CollectedAnnotation(NamedTuple): raw_annotation: _AnnotationScanType mapped_container: Optional[Type[Mapped[Any]]] extracted_mapped_annotation: Union[Type[Any], str] is_dataclass: bool attr_value: Any originating_module: str originating_class: Type[Any] class _ClassScanMapperConfig(_MapperConfig): __slots__ = ( "registry", "clsdict_view", "collected_attributes", "collected_annotations", "local_table", "persist_selectable", "declared_columns", "column_ordering", "column_copies", "table_args", "tablename", "mapper_args", "mapper_args_fn", "table_fn", "inherits", "single", "allow_dataclass_fields", "dataclass_setup_arguments", "is_dataclass_prior_to_mapping", "allow_unmapped_annotations", ) is_deferred = False registry: _RegistryType clsdict_view: _ClassDict collected_annotations: Dict[str, _CollectedAnnotation] collected_attributes: Dict[str, Any] local_table: Optional[FromClause] persist_selectable: Optional[FromClause] declared_columns: util.OrderedSet[Column[Any]] column_ordering: Dict[Column[Any], int] column_copies: Dict[ Union[MappedColumn[Any], Column[Any]], Union[MappedColumn[Any], Column[Any]], ] tablename: Optional[str] mapper_args: Mapping[str, Any] table_args: Optional[_TableArgsType] mapper_args_fn: Optional[Callable[[], Dict[str, Any]]] inherits: Optional[Type[Any]] single: bool is_dataclass_prior_to_mapping: bool allow_unmapped_annotations: bool dataclass_setup_arguments: Optional[_DataclassArguments] """if the class has SQLAlchemy native dataclass parameters, where we will turn the class into a dataclass within the declarative mapping process. """ allow_dataclass_fields: bool """if true, look for dataclass-processed Field objects on the target class as well as superclasses and extract ORM mapping directives from the "metadata" attribute of each Field. if False, dataclass fields can still be used, however they won't be mapped. """ def __init__( self, registry: _RegistryType, cls_: Type[_O], dict_: _ClassDict, table: Optional[FromClause], mapper_kw: _MapperKwArgs, ): # grab class dict before the instrumentation manager has been added. # reduces cycles self.clsdict_view = ( util.immutabledict(dict_) if dict_ else util.EMPTY_DICT ) super().__init__(registry, cls_, mapper_kw) self.registry = registry self.persist_selectable = None self.collected_attributes = {} self.collected_annotations = {} self.declared_columns = util.OrderedSet() self.column_ordering = {} self.column_copies = {} self.single = False self.dataclass_setup_arguments = dca = getattr( self.cls, "_sa_apply_dc_transforms", None ) self.allow_unmapped_annotations = getattr( self.cls, "__allow_unmapped__", False ) or bool(self.dataclass_setup_arguments) self.is_dataclass_prior_to_mapping = cld = dataclasses.is_dataclass( cls_ ) sdk = _get_immediate_cls_attr(cls_, "__sa_dataclass_metadata_key__") # we don't want to consume Field objects from a not-already-dataclass. # the Field objects won't have their "name" or "type" populated, # and while it seems like we could just set these on Field as we # read them, Field is documented as "user read only" and we need to # stay far away from any off-label use of dataclasses APIs. if (not cld or dca) and sdk: raise exc.InvalidRequestError( "SQLAlchemy mapped dataclasses can't consume mapping " "information from dataclass.Field() objects if the immediate " "class is not already a dataclass." ) # if already a dataclass, and __sa_dataclass_metadata_key__ present, # then also look inside of dataclass.Field() objects yielded by # dataclasses.get_fields(cls) when scanning for attributes self.allow_dataclass_fields = bool(sdk and cld) self._setup_declared_events() self._scan_attributes() self._setup_dataclasses_transforms() with mapperlib._CONFIGURE_MUTEX: clsregistry.add_class( self.classname, self.cls, registry._class_registry ) self._setup_inheriting_mapper(mapper_kw) self._extract_mappable_attributes() self._extract_declared_columns() self._setup_table(table) self._setup_inheriting_columns(mapper_kw) self._early_mapping(mapper_kw) def _setup_declared_events(self) -> None: if _get_immediate_cls_attr(self.cls, "__declare_last__"): @event.listens_for(Mapper, "after_configured") def after_configured() -> None: cast( "_DeclMappedClassProtocol[Any]", self.cls ).__declare_last__() if _get_immediate_cls_attr(self.cls, "__declare_first__"): @event.listens_for(Mapper, "before_configured") def before_configured() -> None: cast( "_DeclMappedClassProtocol[Any]", self.cls ).__declare_first__() def _cls_attr_override_checker( self, cls: Type[_O] ) -> Callable[[str, Any], bool]: """Produce a function that checks if a class has overridden an attribute, taking SQLAlchemy-enabled dataclass fields into account. """ if self.allow_dataclass_fields: sa_dataclass_metadata_key = _get_immediate_cls_attr( cls, "__sa_dataclass_metadata_key__" ) else: sa_dataclass_metadata_key = None if not sa_dataclass_metadata_key: def attribute_is_overridden(key: str, obj: Any) -> bool: return getattr(cls, key, obj) is not obj else: all_datacls_fields = { f.name: f.metadata[sa_dataclass_metadata_key] for f in util.dataclass_fields(cls) if sa_dataclass_metadata_key in f.metadata } local_datacls_fields = { f.name: f.metadata[sa_dataclass_metadata_key] for f in util.local_dataclass_fields(cls) if sa_dataclass_metadata_key in f.metadata } absent = object() def attribute_is_overridden(key: str, obj: Any) -> bool: if _is_declarative_props(obj): obj = obj.fget # this function likely has some failure modes still if # someone is doing a deep mixing of the same attribute # name as plain Python attribute vs. dataclass field. ret = local_datacls_fields.get(key, absent) if _is_declarative_props(ret): ret = ret.fget if ret is obj: return False elif ret is not absent: return True all_field = all_datacls_fields.get(key, absent) ret = getattr(cls, key, obj) if ret is obj: return False # for dataclasses, this could be the # 'default' of the field. so filter more specifically # for an already-mapped InstrumentedAttribute if ret is not absent and isinstance( ret, InstrumentedAttribute ): return True if all_field is obj: return False elif all_field is not absent: return True # can't find another attribute return False return attribute_is_overridden _include_dunders = { "__table__", "__mapper_args__", "__tablename__", "__table_args__", } _match_exclude_dunders = re.compile(r"^(?:_sa_|__)") def _cls_attr_resolver( self, cls: Type[Any] ) -> Callable[[], Iterable[Tuple[str, Any, Any, bool]]]: """produce a function to iterate the "attributes" of a class which we want to consider for mapping, adjusting for SQLAlchemy fields embedded in dataclass fields. """ cls_annotations = util.get_annotations(cls) cls_vars = vars(cls) _include_dunders = self._include_dunders _match_exclude_dunders = self._match_exclude_dunders names = [ n for n in util.merge_lists_w_ordering( list(cls_vars), list(cls_annotations) ) if not _match_exclude_dunders.match(n) or n in _include_dunders ] if self.allow_dataclass_fields: sa_dataclass_metadata_key: Optional[str] = _get_immediate_cls_attr( cls, "__sa_dataclass_metadata_key__" ) else: sa_dataclass_metadata_key = None if not sa_dataclass_metadata_key: def local_attributes_for_class() -> ( Iterable[Tuple[str, Any, Any, bool]] ): return ( ( name, cls_vars.get(name), cls_annotations.get(name), False, ) for name in names ) else: dataclass_fields = { field.name: field for field in util.local_dataclass_fields(cls) } fixed_sa_dataclass_metadata_key = sa_dataclass_metadata_key def local_attributes_for_class() -> ( Iterable[Tuple[str, Any, Any, bool]] ): for name in names: field = dataclass_fields.get(name, None) if field and sa_dataclass_metadata_key in field.metadata: yield field.name, _as_dc_declaredattr( field.metadata, fixed_sa_dataclass_metadata_key ), cls_annotations.get(field.name), True else: yield name, cls_vars.get(name), cls_annotations.get( name ), False return local_attributes_for_class def _scan_attributes(self) -> None: cls = self.cls cls_as_Decl = cast("_DeclMappedClassProtocol[Any]", cls) clsdict_view = self.clsdict_view collected_attributes = self.collected_attributes column_copies = self.column_copies _include_dunders = self._include_dunders mapper_args_fn = None table_args = inherited_table_args = None table_fn = None tablename = None fixed_table = "__table__" in clsdict_view attribute_is_overridden = self._cls_attr_override_checker(self.cls) bases = [] for base in cls.__mro__: # collect bases and make sure standalone columns are copied # to be the column they will ultimately be on the class, # so that declared_attr functions use the right columns. # need to do this all the way up the hierarchy first # (see #8190) class_mapped = base is not cls and _is_supercls_for_inherits(base) local_attributes_for_class = self._cls_attr_resolver(base) if not class_mapped and base is not cls: locally_collected_columns = self._produce_column_copies( local_attributes_for_class, attribute_is_overridden, fixed_table, base, ) else: locally_collected_columns = {} bases.append( ( base, class_mapped, local_attributes_for_class, locally_collected_columns, ) ) for ( base, class_mapped, local_attributes_for_class, locally_collected_columns, ) in bases: # this transfer can also take place as we scan each name # for finer-grained control of how collected_attributes is # populated, as this is what impacts column ordering. # however it's simpler to get it out of the way here. collected_attributes.update(locally_collected_columns) for ( name, obj, annotation, is_dataclass_field, ) in local_attributes_for_class(): if name in _include_dunders: if name == "__mapper_args__": check_decl = _check_declared_props_nocascade( obj, name, cls ) if not mapper_args_fn and ( not class_mapped or check_decl ): # don't even invoke __mapper_args__ until # after we've determined everything about the # mapped table. # make a copy of it so a class-level dictionary # is not overwritten when we update column-based # arguments. def _mapper_args_fn() -> Dict[str, Any]: return dict(cls_as_Decl.__mapper_args__) mapper_args_fn = _mapper_args_fn elif name == "__tablename__": check_decl = _check_declared_props_nocascade( obj, name, cls ) if not tablename and (not class_mapped or check_decl): tablename = cls_as_Decl.__tablename__ elif name == "__table__": check_decl = _check_declared_props_nocascade( obj, name, cls ) # if a @declared_attr using "__table__" is detected, # wrap up a callable to look for "__table__" from # the final concrete class when we set up a table. # this was fixed by # #11509, regression in 2.0 from version 1.4. if check_decl and not table_fn: # don't even invoke __table__ until we're ready def _table_fn() -> FromClause: return cls_as_Decl.__table__ table_fn = _table_fn elif name == "__table_args__": check_decl = _check_declared_props_nocascade( obj, name, cls ) if not table_args and (not class_mapped or check_decl): table_args = cls_as_Decl.__table_args__ if not isinstance( table_args, (tuple, dict, type(None)) ): raise exc.ArgumentError( "__table_args__ value must be a tuple, " "dict, or None" ) if base is not cls: inherited_table_args = True else: # any other dunder names; should not be here # as we have tested for all four names in # _include_dunders assert False elif class_mapped: if _is_declarative_props(obj) and not obj._quiet: util.warn( "Regular (i.e. not __special__) " "attribute '%s.%s' uses @declared_attr, " "but owning class %s is mapped - " "not applying to subclass %s." % (base.__name__, name, base, cls) ) continue elif base is not cls: # we're a mixin, abstract base, or something that is # acting like that for now. if isinstance(obj, (Column, MappedColumn)): # already copied columns to the mapped class. continue elif isinstance(obj, MapperProperty): raise exc.InvalidRequestError( "Mapper properties (i.e. deferred," "column_property(), relationship(), etc.) must " "be declared as @declared_attr callables " "on declarative mixin classes. For dataclass " "field() objects, use a lambda:" ) elif _is_declarative_props(obj): # tried to get overloads to tell this to # pylance, no luck assert obj is not None if obj._cascading: if name in clsdict_view: # unfortunately, while we can use the user- # defined attribute here to allow a clean # override, if there's another # subclass below then it still tries to use # this. not sure if there is enough # information here to add this as a feature # later on. util.warn( "Attribute '%s' on class %s cannot be " "processed due to " "@declared_attr.cascading; " "skipping" % (name, cls) ) collected_attributes[name] = column_copies[obj] = ( ret ) = obj.__get__(obj, cls) setattr(cls, name, ret) else: if is_dataclass_field: # access attribute using normal class access # first, to see if it's been mapped on a # superclass. note if the dataclasses.field() # has "default", this value can be anything. ret = getattr(cls, name, None) # so, if it's anything that's not ORM # mapped, assume we should invoke the # declared_attr if not isinstance(ret, InspectionAttr): ret = obj.fget() else: # access attribute using normal class access. # if the declared attr already took place # on a superclass that is mapped, then # this is no longer a declared_attr, it will # be the InstrumentedAttribute ret = getattr(cls, name) # correct for proxies created from hybrid_property # or similar. note there is no known case that # produces nested proxies, so we are only # looking one level deep right now. if ( isinstance(ret, InspectionAttr) and attr_is_internal_proxy(ret) and not isinstance( ret.original_property, MapperProperty ) ): ret = ret.descriptor collected_attributes[name] = column_copies[obj] = ( ret ) if ( isinstance(ret, (Column, MapperProperty)) and ret.doc is None ): ret.doc = obj.__doc__ self._collect_annotation( name, obj._collect_return_annotation(), base, True, obj, ) elif _is_mapped_annotation(annotation, cls, base): # Mapped annotation without any object. # product_column_copies should have handled this. # if future support for other MapperProperty, # then test if this name is already handled and # otherwise proceed to generate. if not fixed_table: assert ( name in collected_attributes or attribute_is_overridden(name, None) ) continue else: # here, the attribute is some other kind of # property that we assume is not part of the # declarative mapping. however, check for some # more common mistakes self._warn_for_decl_attributes(base, name, obj) elif is_dataclass_field and ( name not in clsdict_view or clsdict_view[name] is not obj ): # here, we are definitely looking at the target class # and not a superclass. this is currently a # dataclass-only path. if the name is only # a dataclass field and isn't in local cls.__dict__, # put the object there. # assert that the dataclass-enabled resolver agrees # with what we are seeing assert not attribute_is_overridden(name, obj) if _is_declarative_props(obj): obj = obj.fget() collected_attributes[name] = obj self._collect_annotation( name, annotation, base, False, obj ) else: collected_annotation = self._collect_annotation( name, annotation, base, None, obj ) is_mapped = ( collected_annotation is not None and collected_annotation.mapped_container is not None ) generated_obj = ( collected_annotation.attr_value if collected_annotation is not None else obj ) if obj is None and not fixed_table and is_mapped: collected_attributes[name] = ( generated_obj if generated_obj is not None else MappedColumn() ) elif name in clsdict_view: collected_attributes[name] = obj # else if the name is not in the cls.__dict__, # don't collect it as an attribute. # we will see the annotation only, which is meaningful # both for mapping and dataclasses setup if inherited_table_args and not tablename: table_args = None self.table_args = table_args self.tablename = tablename self.mapper_args_fn = mapper_args_fn self.table_fn = table_fn def _setup_dataclasses_transforms(self) -> None: dataclass_setup_arguments = self.dataclass_setup_arguments if not dataclass_setup_arguments: return # can't use is_dataclass since it uses hasattr if "__dataclass_fields__" in self.cls.__dict__: raise exc.InvalidRequestError( f"Class {self.cls} is already a dataclass; ensure that " "base classes / decorator styles of establishing dataclasses " "are not being mixed. " "This can happen if a class that inherits from " "'MappedAsDataclass', even indirectly, is been mapped with " "'@registry.mapped_as_dataclass'" ) warn_for_non_dc_attrs = collections.defaultdict(list) def _allow_dataclass_field( key: str, originating_class: Type[Any] ) -> bool: if ( originating_class is not self.cls and "__dataclass_fields__" not in originating_class.__dict__ ): warn_for_non_dc_attrs[originating_class].append(key) return True manager = instrumentation.manager_of_class(self.cls) assert manager is not None field_list = [ _AttributeOptions._get_arguments_for_make_dataclass( key, anno, mapped_container, self.collected_attributes.get(key, _NoArg.NO_ARG), ) for key, anno, mapped_container in ( ( key, mapped_anno if mapped_anno else raw_anno, mapped_container, ) for key, ( raw_anno, mapped_container, mapped_anno, is_dc, attr_value, originating_module, originating_class, ) in self.collected_annotations.items() if _allow_dataclass_field(key, originating_class) and ( key not in self.collected_attributes # issue #9226; check for attributes that we've collected # which are already instrumented, which we would assume # mean we are in an ORM inheritance mapping and this # attribute is already mapped on the superclass. Under # no circumstance should any QueryableAttribute be sent to # the dataclass() function; anything that's mapped should # be Field and that's it or not isinstance( self.collected_attributes[key], QueryableAttribute ) ) ) ] if warn_for_non_dc_attrs: for ( originating_class, non_dc_attrs, ) in warn_for_non_dc_attrs.items(): util.warn_deprecated( f"When transforming {self.cls} to a dataclass, " f"attribute(s) " f"{', '.join(repr(key) for key in non_dc_attrs)} " f"originates from superclass " f"{originating_class}, which is not a dataclass. This " f"usage is deprecated and will raise an error in " f"SQLAlchemy 2.1. When declaring SQLAlchemy Declarative " f"Dataclasses, ensure that all mixin classes and other " f"superclasses which include attributes are also a " f"subclass of MappedAsDataclass.", "2.0", code="dcmx", ) annotations = {} defaults = {} for item in field_list: if len(item) == 2: name, tp = item elif len(item) == 3: name, tp, spec = item defaults[name] = spec else: assert False annotations[name] = tp for k, v in defaults.items(): setattr(self.cls, k, v) self._apply_dataclasses_to_any_class( dataclass_setup_arguments, self.cls, annotations ) @classmethod def _update_annotations_for_non_mapped_class( cls, klass: Type[_O] ) -> Mapping[str, _AnnotationScanType]: cls_annotations = util.get_annotations(klass) new_anno = {} for name, annotation in cls_annotations.items(): if _is_mapped_annotation(annotation, klass, klass): extracted = _extract_mapped_subtype( annotation, klass, klass.__module__, name, type(None), required=False, is_dataclass_field=False, expect_mapped=False, ) if extracted: inner, _ = extracted new_anno[name] = inner else: new_anno[name] = annotation return new_anno @classmethod def _apply_dataclasses_to_any_class( cls, dataclass_setup_arguments: _DataclassArguments, klass: Type[_O], use_annotations: Mapping[str, _AnnotationScanType], ) -> None: cls._assert_dc_arguments(dataclass_setup_arguments) dataclass_callable = dataclass_setup_arguments["dataclass_callable"] if dataclass_callable is _NoArg.NO_ARG: dataclass_callable = dataclasses.dataclass restored: Optional[Any] if use_annotations: # apply constructed annotations that should look "normal" to a # dataclasses callable, based on the fields present. This # means remove the Mapped[] container and ensure all Field # entries have an annotation restored = getattr(klass, "__annotations__", None) klass.__annotations__ = cast("Dict[str, Any]", use_annotations) else: restored = None try: dataclass_callable( klass, **{ k: v for k, v in dataclass_setup_arguments.items() if v is not _NoArg.NO_ARG and k != "dataclass_callable" }, ) except (TypeError, ValueError) as ex: raise exc.InvalidRequestError( f"Python dataclasses error encountered when creating " f"dataclass for {klass.__name__!r}: " f"{ex!r}. Please refer to Python dataclasses " "documentation for additional information.", code="dcte", ) from ex finally: # restore original annotations outside of the dataclasses # process; for mixins and __abstract__ superclasses, SQLAlchemy # Declarative will need to see the Mapped[] container inside the # annotations in order to map subclasses if use_annotations: if restored is None: del klass.__annotations__ else: klass.__annotations__ = restored @classmethod def _assert_dc_arguments(cls, arguments: _DataclassArguments) -> None: allowed = { "init", "repr", "order", "eq", "unsafe_hash", "kw_only", "match_args", "dataclass_callable", } disallowed_args = set(arguments).difference(allowed) if disallowed_args: msg = ", ".join(f"{arg!r}" for arg in sorted(disallowed_args)) raise exc.ArgumentError( f"Dataclass argument(s) {msg} are not accepted" ) def _collect_annotation( self, name: str, raw_annotation: _AnnotationScanType, originating_class: Type[Any], expect_mapped: Optional[bool], attr_value: Any, ) -> Optional[_CollectedAnnotation]: if name in self.collected_annotations: return self.collected_annotations[name] if raw_annotation is None: return None is_dataclass = self.is_dataclass_prior_to_mapping allow_unmapped = self.allow_unmapped_annotations if expect_mapped is None: is_dataclass_field = isinstance(attr_value, dataclasses.Field) expect_mapped = ( not is_dataclass_field and not allow_unmapped and ( attr_value is None or isinstance(attr_value, _MappedAttribute) ) ) else: is_dataclass_field = False is_dataclass_field = False extracted = _extract_mapped_subtype( raw_annotation, self.cls, originating_class.__module__, name, type(attr_value), required=False, is_dataclass_field=is_dataclass_field, expect_mapped=expect_mapped and not is_dataclass, # self.allow_dataclass_fields, ) if extracted is None: # ClassVar can come out here return None extracted_mapped_annotation, mapped_container = extracted if attr_value is None and not is_literal(extracted_mapped_annotation): for elem in typing_get_args(extracted_mapped_annotation): if isinstance(elem, str) or is_fwd_ref( elem, check_generic=True ): elem = de_stringify_annotation( self.cls, elem, originating_class.__module__, include_generic=True, ) # look in Annotated[...] for an ORM construct, # such as Annotated[int, mapped_column(primary_key=True)] if isinstance(elem, _IntrospectsAnnotations): attr_value = elem.found_in_pep593_annotated() self.collected_annotations[name] = ca = _CollectedAnnotation( raw_annotation, mapped_container, extracted_mapped_annotation, is_dataclass, attr_value, originating_class.__module__, originating_class, ) return ca def _warn_for_decl_attributes( self, cls: Type[Any], key: str, c: Any ) -> None: if isinstance(c, expression.ColumnElement): util.warn( f"Attribute '{key}' on class {cls} appears to " "be a non-schema SQLAlchemy expression " "object; this won't be part of the declarative mapping. " "To map arbitrary expressions, use ``column_property()`` " "or a similar function such as ``deferred()``, " "``query_expression()`` etc. " ) def _produce_column_copies( self, attributes_for_class: Callable[ [], Iterable[Tuple[str, Any, Any, bool]] ], attribute_is_overridden: Callable[[str, Any], bool], fixed_table: bool, originating_class: Type[Any], ) -> Dict[str, Union[Column[Any], MappedColumn[Any]]]: cls = self.cls dict_ = self.clsdict_view locally_collected_attributes = {} column_copies = self.column_copies # copy mixin columns to the mapped class for name, obj, annotation, is_dataclass in attributes_for_class(): if ( not fixed_table and obj is None and _is_mapped_annotation(annotation, cls, originating_class) ): # obj is None means this is the annotation only path if attribute_is_overridden(name, obj): # perform same "overridden" check as we do for # Column/MappedColumn, this is how a mixin col is not # applied to an inherited subclass that does not have # the mixin. the anno-only path added here for # #9564 continue collected_annotation = self._collect_annotation( name, annotation, originating_class, True, obj ) obj = ( collected_annotation.attr_value if collected_annotation is not None else obj ) if obj is None: obj = MappedColumn() locally_collected_attributes[name] = obj setattr(cls, name, obj) elif isinstance(obj, (Column, MappedColumn)): if attribute_is_overridden(name, obj): # if column has been overridden # (like by the InstrumentedAttribute of the # superclass), skip. don't collect the annotation # either (issue #8718) continue collected_annotation = self._collect_annotation( name, annotation, originating_class, True, obj ) obj = ( collected_annotation.attr_value if collected_annotation is not None else obj ) if name not in dict_ and not ( "__table__" in dict_ and (getattr(obj, "name", None) or name) in dict_["__table__"].c ): if obj.foreign_keys: for fk in obj.foreign_keys: if ( fk._table_column is not None and fk._table_column.table is None ): raise exc.InvalidRequestError( "Columns with foreign keys to " "non-table-bound " "columns must be declared as " "@declared_attr callables " "on declarative mixin classes. " "For dataclass " "field() objects, use a lambda:." ) column_copies[obj] = copy_ = obj._copy() locally_collected_attributes[name] = copy_ setattr(cls, name, copy_) return locally_collected_attributes def _extract_mappable_attributes(self) -> None: cls = self.cls collected_attributes = self.collected_attributes our_stuff = self.properties _include_dunders = self._include_dunders late_mapped = _get_immediate_cls_attr( cls, "_sa_decl_prepare_nocascade", strict=True ) allow_unmapped_annotations = self.allow_unmapped_annotations expect_annotations_wo_mapped = ( allow_unmapped_annotations or self.is_dataclass_prior_to_mapping ) look_for_dataclass_things = bool(self.dataclass_setup_arguments) for k in list(collected_attributes): if k in _include_dunders: continue value = collected_attributes[k] if _is_declarative_props(value): # @declared_attr in collected_attributes only occurs here for a # @declared_attr that's directly on the mapped class; # for a mixin, these have already been evaluated if value._cascading: util.warn( "Use of @declared_attr.cascading only applies to " "Declarative 'mixin' and 'abstract' classes. " "Currently, this flag is ignored on mapped class " "%s" % self.cls ) value = getattr(cls, k) elif ( isinstance(value, QueryableAttribute) and value.class_ is not cls and value.key != k ): # detect a QueryableAttribute that's already mapped being # assigned elsewhere in userland, turn into a synonym() value = SynonymProperty(value.key) setattr(cls, k, value) if ( isinstance(value, tuple) and len(value) == 1 and isinstance(value[0], (Column, _MappedAttribute)) ): util.warn( "Ignoring declarative-like tuple value of attribute " "'%s': possibly a copy-and-paste error with a comma " "accidentally placed at the end of the line?" % k ) continue elif look_for_dataclass_things and isinstance( value, dataclasses.Field ): # we collected a dataclass Field; dataclasses would have # set up the correct state on the class continue elif not isinstance(value, (Column, _DCAttributeOptions)): # using @declared_attr for some object that # isn't Column/MapperProperty/_DCAttributeOptions; remove # from the clsdict_view # and place the evaluated value onto the class. collected_attributes.pop(k) self._warn_for_decl_attributes(cls, k, value) if not late_mapped: setattr(cls, k, value) continue # we expect to see the name 'metadata' in some valid cases; # however at this point we see it's assigned to something trying # to be mapped, so raise for that. # TODO: should "registry" here be also? might be too late # to change that now (2.0 betas) elif k in ("metadata",): raise exc.InvalidRequestError( f"Attribute name '{k}' is reserved when using the " "Declarative API." ) elif isinstance(value, Column): _undefer_column_name( k, self.column_copies.get(value, value) # type: ignore ) else: if isinstance(value, _IntrospectsAnnotations): ( annotation, mapped_container, extracted_mapped_annotation, is_dataclass, attr_value, originating_module, originating_class, ) = self.collected_annotations.get( k, (None, None, None, False, None, None, None) ) # issue #8692 - don't do any annotation interpretation if # an annotation were present and a container such as # Mapped[] etc. were not used. If annotation is None, # do declarative_scan so that the property can raise # for required if ( mapped_container is not None or annotation is None # issue #10516: need to do declarative_scan even with # a non-Mapped annotation if we are doing # __allow_unmapped__, for things like col.name # assignment or allow_unmapped_annotations ): try: value.declarative_scan( self, self.registry, cls, originating_module, k, mapped_container, annotation, extracted_mapped_annotation, is_dataclass, ) except NameError as ne: raise exc.ArgumentError( f"Could not resolve all types within mapped " f'annotation: "{annotation}". Ensure all ' f"types are written correctly and are " f"imported within the module in use." ) from ne else: # assert that we were expecting annotations # without Mapped[] were going to be passed. # otherwise an error should have been raised # by util._extract_mapped_subtype before we got here. assert expect_annotations_wo_mapped if isinstance(value, _DCAttributeOptions): if ( value._has_dataclass_arguments and not look_for_dataclass_things ): if isinstance(value, MapperProperty): argnames = [ "init", "default_factory", "repr", "default", ] else: argnames = ["init", "default_factory", "repr"] args = { a for a in argnames if getattr( value._attribute_options, f"dataclasses_{a}" ) is not _NoArg.NO_ARG } raise exc.ArgumentError( f"Attribute '{k}' on class {cls} includes " f"dataclasses argument(s): " f"{', '.join(sorted(repr(a) for a in args))} but " f"class does not specify " "SQLAlchemy native dataclass configuration." ) if not isinstance(value, (MapperProperty, _MapsColumns)): # filter for _DCAttributeOptions objects that aren't # MapperProperty / mapped_column(). Currently this # includes AssociationProxy. pop it from the things # we're going to map and set it up as a descriptor # on the class. collected_attributes.pop(k) # Assoc Prox (or other descriptor object that may # use _DCAttributeOptions) is usually here, except if # 1. we're a # dataclass, dataclasses would have removed the # attr here or 2. assoc proxy is coming from a # superclass, we want it to be direct here so it # tracks state or 3. assoc prox comes from # declared_attr, uncommon case setattr(cls, k, value) continue our_stuff[k] = value def _extract_declared_columns(self) -> None: our_stuff = self.properties # extract columns from the class dict declared_columns = self.declared_columns column_ordering = self.column_ordering name_to_prop_key = collections.defaultdict(set) for key, c in list(our_stuff.items()): if isinstance(c, _MapsColumns): mp_to_assign = c.mapper_property_to_assign if mp_to_assign: our_stuff[key] = mp_to_assign else: # if no mapper property to assign, this currently means # this is a MappedColumn that will produce a Column for us del our_stuff[key] for col, sort_order in c.columns_to_assign: if not isinstance(c, CompositeProperty): name_to_prop_key[col.name].add(key) declared_columns.add(col) # we would assert this, however we want the below # warning to take effect instead. See #9630 # assert col not in column_ordering column_ordering[col] = sort_order # if this is a MappedColumn and the attribute key we # have is not what the column has for its key, map the # Column explicitly under the attribute key name. # otherwise, Mapper will map it under the column key. if mp_to_assign is None and key != col.key: our_stuff[key] = col elif isinstance(c, Column): # undefer previously occurred here, and now occurs earlier. # ensure every column we get here has been named assert c.name is not None name_to_prop_key[c.name].add(key) declared_columns.add(c) # if the column is the same name as the key, # remove it from the explicit properties dict. # the normal rules for assigning column-based properties # will take over, including precedence of columns # in multi-column ColumnProperties. if key == c.key: del our_stuff[key] for name, keys in name_to_prop_key.items(): if len(keys) > 1: util.warn( "On class %r, Column object %r named " "directly multiple times, " "only one will be used: %s. " "Consider using orm.synonym instead" % (self.classname, name, (", ".join(sorted(keys)))) ) def _setup_table(self, table: Optional[FromClause] = None) -> None: cls = self.cls cls_as_Decl = cast("MappedClassProtocol[Any]", cls) tablename = self.tablename table_args = self.table_args clsdict_view = self.clsdict_view declared_columns = self.declared_columns column_ordering = self.column_ordering manager = attributes.manager_of_class(cls) if ( self.table_fn is None and "__table__" not in clsdict_view and table is None ): if hasattr(cls, "__table_cls__"): table_cls = cast( Type[Table], util.unbound_method_to_callable(cls.__table_cls__), # type: ignore # noqa: E501 ) else: table_cls = Table if tablename is not None: args: Tuple[Any, ...] = () table_kw: Dict[str, Any] = {} if table_args: if isinstance(table_args, dict): table_kw = table_args elif isinstance(table_args, tuple): if isinstance(table_args[-1], dict): args, table_kw = table_args[0:-1], table_args[-1] else: args = table_args autoload_with = clsdict_view.get("__autoload_with__") if autoload_with: table_kw["autoload_with"] = autoload_with autoload = clsdict_view.get("__autoload__") if autoload: table_kw["autoload"] = True sorted_columns = sorted( declared_columns, key=lambda c: column_ordering.get(c, 0), ) table = self.set_cls_attribute( "__table__", table_cls( tablename, self._metadata_for_cls(manager), *sorted_columns, *args, **table_kw, ), ) else: if table is None: if self.table_fn: table = self.set_cls_attribute( "__table__", self.table_fn() ) else: table = cls_as_Decl.__table__ if declared_columns: for c in declared_columns: if not table.c.contains_column(c): raise exc.ArgumentError( "Can't add additional column %r when " "specifying __table__" % c.key ) self.local_table = table def _metadata_for_cls(self, manager: ClassManager[Any]) -> MetaData: meta: Optional[MetaData] = getattr(self.cls, "metadata", None) if meta is not None: return meta else: return manager.registry.metadata def _setup_inheriting_mapper(self, mapper_kw: _MapperKwArgs) -> None: cls = self.cls inherits = mapper_kw.get("inherits", None) if inherits is None: # since we search for classical mappings now, search for # multiple mapped bases as well and raise an error. inherits_search = [] for base_ in cls.__bases__: c = _resolve_for_abstract_or_classical(base_) if c is None: continue if _is_supercls_for_inherits(c) and c not in inherits_search: inherits_search.append(c) if inherits_search: if len(inherits_search) > 1: raise exc.InvalidRequestError( "Class %s has multiple mapped bases: %r" % (cls, inherits_search) ) inherits = inherits_search[0] elif isinstance(inherits, Mapper): inherits = inherits.class_ self.inherits = inherits clsdict_view = self.clsdict_view if "__table__" not in clsdict_view and self.tablename is None: self.single = True def _setup_inheriting_columns(self, mapper_kw: _MapperKwArgs) -> None: table = self.local_table cls = self.cls table_args = self.table_args declared_columns = self.declared_columns if ( table is None and self.inherits is None and not _get_immediate_cls_attr(cls, "__no_table__") ): raise exc.InvalidRequestError( "Class %r does not have a __table__ or __tablename__ " "specified and does not inherit from an existing " "table-mapped class." % cls ) elif self.inherits: inherited_mapper_or_config = _declared_mapping_info(self.inherits) assert inherited_mapper_or_config is not None inherited_table = inherited_mapper_or_config.local_table inherited_persist_selectable = ( inherited_mapper_or_config.persist_selectable ) if table is None: # single table inheritance. # ensure no table args if table_args: raise exc.ArgumentError( "Can't place __table_args__ on an inherited class " "with no table." ) # add any columns declared here to the inherited table. if declared_columns and not isinstance(inherited_table, Table): raise exc.ArgumentError( f"Can't declare columns on single-table-inherited " f"subclass {self.cls}; superclass {self.inherits} " "is not mapped to a Table" ) for col in declared_columns: assert inherited_table is not None if col.name in inherited_table.c: if inherited_table.c[col.name] is col: continue raise exc.ArgumentError( f"Column '{col}' on class {cls.__name__} " f"conflicts with existing column " f"'{inherited_table.c[col.name]}'. If using " f"Declarative, consider using the " "use_existing_column parameter of mapped_column() " "to resolve conflicts." ) if col.primary_key: raise exc.ArgumentError( "Can't place primary key columns on an inherited " "class with no table." ) if TYPE_CHECKING: assert isinstance(inherited_table, Table) inherited_table.append_column(col) if ( inherited_persist_selectable is not None and inherited_persist_selectable is not inherited_table ): inherited_persist_selectable._refresh_for_new_column( col ) def _prepare_mapper_arguments(self, mapper_kw: _MapperKwArgs) -> None: properties = self.properties if self.mapper_args_fn: mapper_args = self.mapper_args_fn() else: mapper_args = {} if mapper_kw: mapper_args.update(mapper_kw) if "properties" in mapper_args: properties = dict(properties) properties.update(mapper_args["properties"]) # make sure that column copies are used rather # than the original columns from any mixins for k in ("version_id_col", "polymorphic_on"): if k in mapper_args: v = mapper_args[k] mapper_args[k] = self.column_copies.get(v, v) if "primary_key" in mapper_args: mapper_args["primary_key"] = [ self.column_copies.get(v, v) for v in util.to_list(mapper_args["primary_key"]) ] if "inherits" in mapper_args: inherits_arg = mapper_args["inherits"] if isinstance(inherits_arg, Mapper): inherits_arg = inherits_arg.class_ if inherits_arg is not self.inherits: raise exc.InvalidRequestError( "mapper inherits argument given for non-inheriting " "class %s" % (mapper_args["inherits"]) ) if self.inherits: mapper_args["inherits"] = self.inherits if self.inherits and not mapper_args.get("concrete", False): # note the superclass is expected to have a Mapper assigned and # not be a deferred config, as this is called within map() inherited_mapper = class_mapper(self.inherits, False) inherited_table = inherited_mapper.local_table # single or joined inheritance # exclude any cols on the inherited table which are # not mapped on the parent class, to avoid # mapping columns specific to sibling/nephew classes if "exclude_properties" not in mapper_args: mapper_args["exclude_properties"] = exclude_properties = { c.key for c in inherited_table.c if c not in inherited_mapper._columntoproperty }.union(inherited_mapper.exclude_properties or ()) exclude_properties.difference_update( [c.key for c in self.declared_columns] ) # look through columns in the current mapper that # are keyed to a propname different than the colname # (if names were the same, we'd have popped it out above, # in which case the mapper makes this combination). # See if the superclass has a similar column property. # If so, join them together. for k, col in list(properties.items()): if not isinstance(col, expression.ColumnElement): continue if k in inherited_mapper._props: p = inherited_mapper._props[k] if isinstance(p, ColumnProperty): # note here we place the subclass column # first. See [ticket:1892] for background. properties[k] = [col] + p.columns result_mapper_args = mapper_args.copy() result_mapper_args["properties"] = properties self.mapper_args = result_mapper_args def map(self, mapper_kw: _MapperKwArgs = util.EMPTY_DICT) -> Mapper[Any]: self._prepare_mapper_arguments(mapper_kw) if hasattr(self.cls, "__mapper_cls__"): mapper_cls = cast( "Type[Mapper[Any]]", util.unbound_method_to_callable( self.cls.__mapper_cls__ # type: ignore ), ) else: mapper_cls = Mapper return self.set_cls_attribute( "__mapper__", mapper_cls(self.cls, self.local_table, **self.mapper_args), ) @util.preload_module("sqlalchemy.orm.decl_api") def _as_dc_declaredattr( field_metadata: Mapping[str, Any], sa_dataclass_metadata_key: str ) -> Any: # wrap lambdas inside dataclass fields inside an ad-hoc declared_attr. # we can't write it because field.metadata is immutable :( so we have # to go through extra trouble to compare these decl_api = util.preloaded.orm_decl_api obj = field_metadata[sa_dataclass_metadata_key] if callable(obj) and not isinstance(obj, decl_api.declared_attr): return decl_api.declared_attr(obj) else: return obj class _DeferredMapperConfig(_ClassScanMapperConfig): _cls: weakref.ref[Type[Any]] is_deferred = True _configs: util.OrderedDict[ weakref.ref[Type[Any]], _DeferredMapperConfig ] = util.OrderedDict() def _early_mapping(self, mapper_kw: _MapperKwArgs) -> None: pass # mypy disallows plain property override of variable @property # type: ignore def cls(self) -> Type[Any]: return self._cls() # type: ignore @cls.setter def cls(self, class_: Type[Any]) -> None: self._cls = weakref.ref(class_, self._remove_config_cls) self._configs[self._cls] = self @classmethod def _remove_config_cls(cls, ref: weakref.ref[Type[Any]]) -> None: cls._configs.pop(ref, None) @classmethod def has_cls(cls, class_: Type[Any]) -> bool: # 2.6 fails on weakref if class_ is an old style class return isinstance(class_, type) and weakref.ref(class_) in cls._configs @classmethod def raise_unmapped_for_cls(cls, class_: Type[Any]) -> NoReturn: if hasattr(class_, "_sa_raise_deferred_config"): class_._sa_raise_deferred_config() raise orm_exc.UnmappedClassError( class_, msg=( f"Class {orm_exc._safe_cls_name(class_)} has a deferred " "mapping on it. It is not yet usable as a mapped class." ), ) @classmethod def config_for_cls(cls, class_: Type[Any]) -> _DeferredMapperConfig: return cls._configs[weakref.ref(class_)] @classmethod def classes_for_base( cls, base_cls: Type[Any], sort: bool = True ) -> List[_DeferredMapperConfig]: classes_for_base = [ m for m, cls_ in [(m, m.cls) for m in cls._configs.values()] if cls_ is not None and issubclass(cls_, base_cls) ] if not sort: return classes_for_base all_m_by_cls = {m.cls: m for m in classes_for_base} tuples: List[Tuple[_DeferredMapperConfig, _DeferredMapperConfig]] = [] for m_cls in all_m_by_cls: tuples.extend( (all_m_by_cls[base_cls], all_m_by_cls[m_cls]) for base_cls in m_cls.__bases__ if base_cls in all_m_by_cls ) return list(topological.sort(tuples, classes_for_base)) def map(self, mapper_kw: _MapperKwArgs = util.EMPTY_DICT) -> Mapper[Any]: self._configs.pop(self._cls, None) return super().map(mapper_kw) def _add_attribute( cls: Type[Any], key: str, value: MapperProperty[Any] ) -> None: """add an attribute to an existing declarative class. This runs through the logic to determine MapperProperty, adds it to the Mapper, adds a column to the mapped Table, etc. """ if "__mapper__" in cls.__dict__: mapped_cls = cast("MappedClassProtocol[Any]", cls) def _table_or_raise(mc: MappedClassProtocol[Any]) -> Table: if isinstance(mc.__table__, Table): return mc.__table__ raise exc.InvalidRequestError( f"Cannot add a new attribute to mapped class {mc.__name__!r} " "because it's not mapped against a table." ) if isinstance(value, Column): _undefer_column_name(key, value) _table_or_raise(mapped_cls).append_column( value, replace_existing=True ) mapped_cls.__mapper__.add_property(key, value) elif isinstance(value, _MapsColumns): mp = value.mapper_property_to_assign for col, _ in value.columns_to_assign: _undefer_column_name(key, col) _table_or_raise(mapped_cls).append_column( col, replace_existing=True ) if not mp: mapped_cls.__mapper__.add_property(key, col) if mp: mapped_cls.__mapper__.add_property(key, mp) elif isinstance(value, MapperProperty): mapped_cls.__mapper__.add_property(key, value) elif isinstance(value, QueryableAttribute) and value.key != key: # detect a QueryableAttribute that's already mapped being # assigned elsewhere in userland, turn into a synonym() value = SynonymProperty(value.key) mapped_cls.__mapper__.add_property(key, value) else: type.__setattr__(cls, key, value) mapped_cls.__mapper__._expire_memoizations() else: type.__setattr__(cls, key, value) def _del_attribute(cls: Type[Any], key: str) -> None: if ( "__mapper__" in cls.__dict__ and key in cls.__dict__ and not cast( "MappedClassProtocol[Any]", cls ).__mapper__._dispose_called ): value = cls.__dict__[key] if isinstance( value, (Column, _MapsColumns, MapperProperty, QueryableAttribute) ): raise NotImplementedError( "Can't un-map individual mapped attributes on a mapped class." ) else: type.__delattr__(cls, key) cast( "MappedClassProtocol[Any]", cls ).__mapper__._expire_memoizations() else: type.__delattr__(cls, key) def _declarative_constructor(self: Any, **kwargs: Any) -> None: """A simple constructor that allows initialization from kwargs. Sets attributes on the constructed instance using the names and values in ``kwargs``. Only keys that are present as attributes of the instance's class are allowed. These could be, for example, any mapped columns or relationships. """ cls_ = type(self) for k in kwargs: if not hasattr(cls_, k): raise TypeError( "%r is an invalid keyword argument for %s" % (k, cls_.__name__) ) setattr(self, k, kwargs[k]) _declarative_constructor.__name__ = "__init__" def _undefer_column_name(key: str, column: Column[Any]) -> None: if column.key is None: column.key = key if column.name is None: column.name = key